What is Carrier Frequency Offset in OFDM?

Carrier Frequency Offset:

Carrier frequency offset (CFO) occurs when the local oscillator signal for down conversion in the receiver does not synchronize with the carrier signal contained in the received signal. This phenomenon can be attributed to two factors: frequency mismatch in the transmitter and the receiver oscillators, and the Doppler effect as the transmitter and/or the receiver is moving. When this occurs, the received signal will be shifted in frequency,

                                             Fig: Carrier Frequency Offset

For an OFDM system, the orthogonality among subcarriers is maintained only if the receiver uses a local oscillation signal that is synchronous with the carrier signal contained in the received signal. Otherwise, mismatch in carrier frequency can result in inter-carrier interference (ICI). Practically, the oscillators in the transmitter and the receiver can never be oscillating at identical frequency. Hence, carrier frequency offset always exists, even if there is no Doppler effect

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What is Guard Interval in OFDM?

Guard Interval?

 

                         which there are two copies of the received waveform–one on time and the other delayed by some time. Inter-symbol interference (ISI) is induced because the tail  part of symbol 1 will interfere with the processing of symbol 2. To eliminate ISI, a guard interval of Ng samples is usually inserted at the beginning of each OFDM symbol

                                                         Fig:Guard Interval

   

The length of the guard interval is made longer than the delay spread of the wireless channel. As a result, the degree of delay spread in the operating  environments must be obtained beforehand. Note that the guard interval actually wastes transmission resources, hence the ratio of the guard interval length to the effective OFDM symbol duration is usually kept below 1/4. During the guard interval, the transmitter can send null waveform. This scheme is called zero padding (ZP) transmission .. A ZP–OFDM system has lower transmission power and a simpler transmitter structure. Unfortunately, the ZP–OFDM scheme introduces ICI, as the orthogonality among subcarriers is destroyed when multiple copies of the time-shifted ZP–OFDM waveform are received. To remove ICI, cyclic prefixing (CP) transmission is preferred. To generate the CP signal, an additional buffer is required in an OFDM   transmitter

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Explian about Cognitive Radios Network?

What Are Cognitive Radio Networks?

          Cognitive (or smart) radio networks  are an innovative approach to wireless engineering in which radios are designed with an unprecedented level of intelligence and agility. This advanced technology enables radio devices to use spectrum (i.e., radio frequencies) in entirely new and sophisticated ways. Cognitive radios have the ability to monitor, sense, and detect the conditions of their operating environment, and dynamically reconfigure their own characteristics to best match those conditions.

Using complex calculations, xMax cognitive radios can identify potential impairments to communications quality, like interference, path loss, shadowing and multipath fading. They can then adjust their transmitting parameters, such as power output, frequency, and modulation to ensure an optimized communications experience for users.

                                                                   Fig:Cognitive Radio Network

Cognitive vs. Conventional:

Conventional, or “dumb” radios, have been designed with the assumption that they were operating in a spectrum band that was free of interference. As a result, there was no requirement to endow these radios with the ability to dynamically change parameters, channels or spectrum bands in response to interference. Not surprisingly, these radios required pristine, dedicated (i.e., licensed) spectrum to operate.

By contrast, xMax cognitive radios have been engineered from the ground up to function in challenging conditions. Unlike their traditional counterparts, they can view their environment in great  detail to identify spectrum that is not being used, and quickly tune to that frequency to transmit and/or receive signals. They also have the ability to instantly find other spectrum if interference is detected on the frequencies being used. In the case of xMax, it samples, detects and determines if interference has reached unacceptable levels up to 33 times a second.

The following image illustrates how xMax cognitive radios operate differently from conventional radios. It shows screen captures of spectrum analyzer readings taken from an xMax network tower in Ft Lauderdale, FL. The frequencies being measured are in the unlicensed 900 MHz ISM band. Because this spectrum is unlicensed (i.e., free of charge for anyone to use) it is used by hundreds, if not thousands of radios in the local area for applications like cordless phones, baby monitors, commercial video security systems, etc.

The figure at the left shows how a conventional radio would view this—as an environment having an unacceptable level of interference for communicating. The figure at the right shows what this same interference looks like to xMax. xMax is able to divide these frequencies into very small time segments (33 milliseconds) and find usable gaps where it can transmit its short and highly efficient signals—at moments when the spectrum is quiet.

 

xMax divides the 900 MHz spectrum block shown into 18 channels—giving it 18 opportunities (windows) every 33 milliseconds to find available spectrum.

In short, the xMax cognitive radio network sees windows of opportunity where other radios see walls of interference.

To reduce “thrashing” and unnecessary channel switching due to temporary and very short-lived interference phenomenon, or degraded network conditions (that do not cause a noticeable impact to performance or quality), actual channel and handovers decisions are made by trending multiple samples and measurements. The system only switches from its current channel when extreme levels of interference exceed its built-in interference mitigation capabilities. This enables xMax to use frequencies and find available bandwidth where other radios can only see static, yet its real-world tuned algorithms reduce signaling overhead and optimize throughput and quality.

Cognitive Radios Improve Spectrum Efficiency:

The ability of xMax cognitive radios to make real-time autonomous decisions and dynamically change frequencies (referred to as dynamic spectrum access, or DSA) allows them to intelligently share spectrum and extract more bandwidth—which improves overall spectrum efficiency. It achieves this by “opportunistic use” of shared frequencies like unlicensed spectrum.

xMax cognitive radio technology was designed to be “frequency agnostic.” That is, its cognitive “Identify and Utilize” spectrum sensing technology can be used to power radios in any frequency band. This is beneficial since the FCC and wireless regulatory bodies around the world are in the process of opening up new spectrum, as well as reclassifying existing spectrum, to be made available for opportunistic use by cognitive radios.

This would allow new market entrants, utilities, public safety, enterprise and even existing wireless operators to offer new services, additional bandwidth and higher capacity without requiring these entities to purchase expensive and scarce wireless spectrum.

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Explain about yagi antenna?

The Yagi antenna was invented in Japan, with results first published in 1926. The work was originally done by Shintaro Uda, but published in Japanese. The work was presented for the first time in English by Yagi (who was either Uda's professor or colleague, my sources are conflicting), who went to America and gave the first English talks on the antenna, which led to its widespread use. Hence, even though the antenna is often called a Yagi antenna, Uda probably invented it. A picture of Professor Yagi with a Yagi-Uda antenna is shown below.

The Yagi antenna consists of a single 'feed' or 'driven' element, typically a dipole or a folded dipole antenna. This is the only member of the above structure that is actually excited (a source voltage or current applied). The rest of the elements are parasitic - they reflect or help to transmit the energy in a particular direction. The length of the feed element is given in Figure 1 as F. The feed antenna is almost always the second from the end, as shown in Figure 1. This feed antenna is often altered in size to make it resonant in the presence of the parasitic elements (typically, 0.45-0.48 wavelengths long for a dipole antenna).

The element to the left of the feed element in Figure 1 is the reflector. The length of this element is given as R and the distance between the feed and the reflector is SR. The reflector element is typically slightly longer than the feed element. There is typically only one reflector; adding more reflectors improves performance very slightly. This element is important in determining the front-to-back ratio of the antenna.

Having the reflector slightly longer than resonant serves two purposes. The first is that the larger the element is, the better of a physical reflector it becomes.

Secondly, if the reflector is longer than its resonant length, the impedance of the reflector will be inductive. Hence, the current on the reflector lags the voltage induced on the reflector. The director elements (those to the right of the feed in Figure 1) will be shorter than resonant, making them capacitive, so that the current leads the voltage. This will cause a phase distribution to occur across the elements, simulating the phase progression of a plane wave across the array of elements. This leads to the array being designated as a travelling wave antenna. By choosing the lengths in this manner, the Yagi-Uda antenna becomes an end-fire array - the radiation is along the +y-axis as

                                              Fig: yagi uda antenna



The rest of the elements (those to the right of the feed antenna as shown in Figure 1) are known as director elements. There can be any number of directors N, which is typically anywhere from N=1 to N=20 directors. Each element is of length Di, and separated from the adjacent director by a length SDi. As alluded to in the previous paragraph, the lengths of the directors are typically less than the resonant length, which encourages wave propagation in the direction of the directors.

The above description is the basic idea of what is going on with the Yagi-Uda antenna. Yagi antenna design is done most often via measurements, and sometimes computer simulations. For instance, let's look at a two-element Yagi antenna (1 reflector, 1 feed element, 0 directors). The feed element is a half-wavelength dipole, shortened to be resonant (gain = 2.15 dB





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Short notes for Helical antenna?

A helical antenna is an antenna consisting of a conducting wire wound in the form of a helix. In most cases, helical antennas are mounted over a ground plane. The feed line is connected between the bottom of the helix and the ground plane. Helical antennas can operate in one of two principal modes — normal mode or axial mode.

                                          Fig:Helical  antenna
                                 

The most popular helical antenna (helix) is a travelling wave antenna in the shape of a corkscrew that produces radiation along the axis of the helix antenna. These helix antennas are referred to as axial-mode helical antennas. The benefits of this helix antenna is it has a wide bandwidth, is easily constructed, has a real input impedance,
Helix antennas for satellite communications

We offer a unique set of helix antennas for satellite communications. Our helix antennas operate across several satellite networks including GPS, Iridium and GLONASS. We also offer several antennas that work across multiple networks.

The antennas are available in different sizes and form factors. We produce both external antennas that come in a range of plastic housings, as well as embedded antennas. Our embedded antennas are custom built to sit perfectly in the devices own housing. 
Helical broadcasting antennas
Specialized normal-mode helical antennas are used for FM radio and television broadcasting on the VHF and UHF bands.




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Antenna basic?

Antennas are an essential part of radio telecommunications equipment, bridging the gap between electronic and electromagnetic signals. The shape and size of an antenna is a strong clue as to its type, as the design dictates the antenna’s purpose. The antenna’s length, for example, corresponds to the length of the radio waves the antenna receives or transmits. The shape affects whether it receives radio waves from different directions or a single direction.

Passive gain amplifies the signal

All antennas exhibit passive gain, which serves to amplify the signal. Passive gain is measured by the quantity dBi, which is the gain referenced to a theoretical isotropic antenna; an isotropic antenna transmits energy equally in all directions, and does not exist in nature. The gain of an ideal half-wave dipole antenna is 2.15 dBi. It should also be noted that as directionality increases, so does gain.

EIRP, or equivalent (or effective) isotropic radiated power, is the measure of the maximum power a theoretical isotropic antenna would emit in the direction of maximum antenna gain. EIRP accounts for losses from transmission lines and connectors, and includes actual antenna gain. EIRP allows calculation of real power output and field strength values, if actual antenna gain and transmitter output power are known.

Directional antenna

Directional and semi-directional antennas focus radiated power into narrow beams, adding a significant amount of gain in the process. Antenna properties are also reciprocal. The characteristics of a transmitting antenna, such as impedance and gain, are also applicable to a receiving antenna. This is why the same antenna can be used for both sending and receiving. The gain of a highly directional parabolic antenna serves to amplify a weak signal; this is one reason why this type of antenna is frequently used for long distance links

Yagi

Building on the principles of the dipole antenna, the Yagi has several pairs of metal tubing elements laid parallel to each other on another long tube that serves as a backbone. One pair of elements functions as a traditional dipole antenna; the others reinforce the incoming radio signal, boosting its strength. Engineers select the lengths of each element and their relative spacing to produce the best radio sensitivity, in effect tuning the antenna to desired wavelengths. The Yagi is the familiar TV antenna you see on the rooftops of homes. It has more directional sensitivity than a dipole, so you aim it in the direction of the radio source.

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HOW TOIMPROVE SPECTRUM EFFICIENCY USING COGNITIVE RADIO NETWORK?

What Are Cognitive Radio Networks?

          Cognitive (or smart) radio networks  are an innovative approach to wireless engineering in which radios are designed with an unprecedented level of intelligence and agility. This advanced technology enables radio devices to use spectrum (i.e., radio frequencies) in entirely new and sophisticated ways. Cognitive radios have the ability to monitor, sense, and detect the conditions of their operating environment, and dynamically reconfigure their own characteristics to best match those conditions.

Using complex calculations, xMax cognitive radios can identify potential impairments to communications quality, like interference, path loss, shadowing and multipath fading. They can then adjust their transmitting parameters, such as power output, frequency, and modulation to ensure an optimized communications experience for users.

                                                                   Fig:Cognitive Radio Network

Cognitive vs. Conventional:

Conventional, or “dumb” radios, have been designed with the assumption that they were operating in a spectrum band that was free of interference. As a result, there was no requirement to endow these radios with the ability to dynamically change parameters, channels or spectrum bands in response to interference. Not surprisingly, these radios required pristine, dedicated (i.e., licensed) spectrum to operate.

By contrast, xMax cognitive radios have been engineered from the ground up to function in challenging conditions. Unlike their traditional counterparts, they can view their environment in great detail to identify spectrum that is not being used, and quickly tune to that frequency to transmit and/or receive signals. They also have the ability to instantly find other spectrum if interference is detected on the frequencies being used. In the case of xMax, it samples, detects and determines if interference has reached unacceptable levels up to 33 times a second.

The following image illustrates how xMax cognitive radios operate differently from conventional radios. It shows screen captures of spectrum analyzer readings taken from an xMax network tower in Ft Lauderdale, FL. The frequencies being measured are in the unlicensed 900 MHz ISM band. Because this spectrum is unlicensed (i.e., free of charge for anyone to use) it is used by hundreds, if not thousands of radios in the local area for applications like cordless phones, baby monitors, commercial video security systems, etc.

The figure at the left shows how a conventional radio would view this—as an environment having an unacceptable level of interference for communicating. The figure at the right shows what this same interference looks like to xMax. xMax is able to divide these frequencies into very small time segments (33 milliseconds) and find usable gaps where it can transmit its short and highly efficient signals—at moments when the spectrum is quiet.

 

xMax divides the 900 MHz spectrum block shown into 18 channels—giving it 18 opportunities (windows) every 33 milliseconds to find available spectrum.

In short, the xMax cognitive radio network sees windows of opportunity where other radios see walls of interference.

To reduce “thrashing” and unnecessary channel switching due to temporary and very short-lived interference phenomenon, or degraded network conditions (that do not cause a noticeable impact to performance or quality), actual channel and handovers decisions are made by trending multiple samples and measurements. The system only switches from its current channel when extreme levels of interference exceed its built-in interference mitigation capabilities. This enables xMax to use frequencies and find available bandwidth where other radios can only see static, yet its real-world tuned algorithms reduce signaling overhead and optimize throughput and quality.

Cognitive Radios Improve Spectrum Efficiency:

The ability of xMax cognitive radios to make real-time autonomous decisions and dynamically change frequencies (referred to as dynamic spectrum access, or DSA) allows them to intelligently share spectrum and extract more bandwidth—which improves overall spectrum efficiency. It achieves this by “opportunistic use” of shared frequencies like unlicensed spectrum.

xMax cognitive radio technology was designed to be “frequency agnostic.” That is, its cognitive “Identify and Utilize” spectrum sensing technology can be used to power radios in any frequency band. This is beneficial since the FCC and wireless regulatory bodies around the world are in the process of opening up new spectrum, as well as reclassifying existing spectrum, to be made available for opportunistic use by cognitive radios.

This would allow new market entrants, utilities, public safety, enterprise and even existing wireless operators to offer new services, additional bandwidth and higher capacity without requiring these entities to purchase expensive and scarce wireless spectrum.

FOR MORE DETAILS CLICK HERE

FREQUENCY SHIFT KEYING(FSK) USING MATLAB?

FSK:

Frequency-shift keying (FSK) is a frequency modulation scheme in which digital information is transmitted through discrete frequency changes of a carrier wave. 
he FSK 

CODING:
 clc;
 close all;
 clear all;
 x=input('enter the binary input = ');
 l=length(x);
 for i=1:1:l
 m(((i-1)*100)+1:i*100)=x(i);
 end
 figure;
 subplot(4,1,1);
 plot(m);
 xlabel('time');
 ylabel('amplitude');
 title('modulating signal');
 f=100;
 t=0:(1/f):(l-(1/f));
 f1=10;
 f2=5;
 c1=sin(2*pi*f1*t);
 y1=m.*c1;
 subplot(4,1,2);
 plot(t,y1);
 xlabel('time');
 ylabel('amplitude');
 for j=1:l
 if x(j)==1
 x(j)=0;
else x(j)=1;
     end
 m1((j-1)*100+1:j*100)=x(j);
end
 c2=sin(2*pi*f2*t);
 y2=m1.*c2;
 subplot(4,1,3);
 plot(t,y2);
 xlabel('time');
 ylabel('amplitude');
 y=y1+y2;
 subplot(4,1,4);
 plot(t,y);
 xlabel('time');
 ylabel('amplitude');
 title('FSK modulated wave');
 r=randn(size(y));
 F=y+r;
 figure;
 subplot(3,1,1);
 plot(F);
 xlabel('time');
 ylabel('amplitude');
 title('noise added FSK signal');
 l1=length(F);
 t1=0:0.01:.99;
 r1=sin(2*pi*f1*t1);
 r1=fliplr(r1);
 l2=length(r1);
 l3=l1+l2-1;
 u=fft(F,l3);
 v=fft(r1,l3);
 k1=u.*v;
 k11=ifft(k1,l3);
 r2=sin(2*pi*f2*t1);
 r2=fliplr(r2);
 w=fft(r2,l3);
 k2=u.*w;
 k22=ifft(k2,l3);
 k=k11-k22;
 subplot(3,1,2);
 plot(k);
 xlabel('time');
 ylabel('amplitude');
   title('correlated signal');
 for z=1:l
t(z)=k(z*100);
 if t(z)>0
 s(z)=1;
 else
 s(z)=0;
 end
 end
 subplot(3,1,3);
 tem(s);
 xlabel('time');
 ylabel('amplitude');
 title('Demodulated output signal'); 

OUTPUT:

 

   
                                                        Fig: FSK Modulation
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MATLAB CODE FOR AMPLITUDE MODULATION

AMPLITUDE MODULATION:

the modulation of a wave by varying its amplitude, used especially as a means of broadcasting an audio signal by combining it with a radio carrier wave.


CODING:

clc;
clear all;
close all;

Ac=2; %carrier amplitude
fc=0.5; %carrier frequency
Am=.5; %message signal amplitude
fm=.05; %message signal frequency
Fs=100; %sampling rate/frequency

ka=1; %modulation coefficient

t=[0:0.1:50]; %defining the time range & disseminating it into samples
ct=Ac*cos(2*pi*fc*t); %defining the carrier signal wave
mt=Am*cos(2*pi*fm*t); %defining the message signal
AM=ct.*(1+ka*mt); %Amplitude Modulated wave, according to the standard definition

subplot(3,1,1); %plotting the message signal wave
plot(mt);
ylabel('Message signal');

subplot(3,1,2); %plotting the carrier signal wave
plot(ct);
ylabel('carrier');

subplot(3,1,3); %plotting the amplitude modulated wave
plot(AM);
ylabel('AM signal');

             
                                                         Fig: Amplitude Modulation









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HOW TO REDUCE OUTAGE PROBABILITY USING RELAY TECHNIQUE?

OUTAGE PERFORMANCE OF AMPLIFY AND FORWARD RELAY:
 
                      The amplify-and-forward relay protocol is a protocol defined for wireless Cooperative communication.An example of a wireless communication network in which cooperation improves the performance of the system is the relay Network In this case, the relay just amplies its received signal, maintaining a fixed average transmit power. selection amplify-and-forward (AF) relaying scheme which has the lower outage probability than that of a conventional AF relaying scheme in  cooperative relay networks. In real wireless environments, as the channel of source-to-destination (SD) link varies with an increase in time, we can also obtain a diversity gain through the SD link by re transmission in common with a conventional AF relaying scheme. Thus, we can expect a performance enhancement by adaptively determining the transmitting node between the relaying and source nodes

                                                                Fig :amplify and forward Relay


      In cooperative relay networks, relaying nodes can forward information from a single antenna terminal to form a virtual antenna array, and thereby achieving space diversity and improving the system performance, hence cooperative communications have attracted much attention. The relaying nodes essentially operate in either amplify and- forward (AF) and decode-and-forward relaying modes, which are basic for various evolved relaying schemes.the adaptive selective relaying scheme which determines the best among multiple AF relaying nodes having the maximum received SNR through the SR link was proposed, and its performances of outage  channel capacity , symbol error rate were analyzed



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ON THE OUTAGE PERFORMANCE OF SELECTION AMPLIFY-AND-FORWARD RELAYING SCHEME

Difference between base band and broadband?

In Baseband, data is sent as digital signals through the media as a single channel that uses the entire bandwidth of the media. Baseband communication is bi-directional, which means that the same channel can be used to send and receive signals. In Baseband, frequency-division multiplexing is not possible. (Multiplexing (short muxing) is a process where multiple analog message signals or digital data streams are combined into one signal over a shared medium.)

Fig:Base band and Broad Band

Broadband sends information in the form of an analog signal. Each transmission is assigned to a portion of the bandwidth, hence multiple transmissions are possible at the same time. Broadband communication is unidirectional, so in order to send and receive, two pathways are needed. This can be accomplished either by assigning a frequency for sending and assigning a frequency for receiving along the same cable or by using two cables, one for sending and one for receiving. In broadband frequency-division multiplexing is possible.

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MUTUAL COUPLING ON THE CHANNEL CAPACITY OF MIMO SYSTEMS?

Channal Capacity:

In modeling a MIMO channel, it is generally assumed that the coefficients of the channel transfer matrix are independent and identically distributed. When the antennas are placed close to one another or when there are fewer scatters in between the transmitting and the receiving arrays, the correlation coefficients will increase and hence the channel capacity will be reduced.

  Mutual coupling:

                           At smaller antenna spacings, the variation of mutual coupling among antennas will affect the channel capacity more significantly. It was reported that mutual coupling may increase the channel capacity by decreasing the spatial correlation coefficients under certain circumferences . In a network theory was used to derive the transfer matrix, which includes the coupling effects among antennas in both the transmitting and the receiving arrays, the multipath propagation channel, the receiver matching network, and the noise in the receiver amplifiers.

                               FIG:CHANNEL CAPACITY IN MIMO SYSTEMS

FOR MORE DETAILS

EFFECT OF MUTUAL COUPLING ON THE CHANNEL CAPACITY OF MIMO SYSTEMS

Amplify and forward Relay for Communication Systems?

AMPLIFY AND FORWARD RELAY:

                      The amplify-and-forward relay protocol is a protocol defined for wireless Cooperative communication.An example of a wireless communication network in which cooperation improves the performance of the system is the relay Network In this case, the relay just amplies its received signal, maintaining a fixed average transmit power. selection amplify-and-forward (AF) relaying scheme which has the lower outage probability than that of a conventional AF relaying scheme in  cooperative relay networks. In real wireless environments, as the channel of source-to-destination (SD) link varies with an increase in time, we can also obtain a diversity gain through the SD link by re transmission in common with a conventional AF relaying scheme. Thus, we can expect a performance enhancement by adaptively determining the transmitting node between the relaying and source nodes

                                                                Fig :amplify and forward Relay


      In cooperative relay networks, relaying nodes can forward information from a single antenna terminal to form a virtual antenna array, and thereby achieving space diversity and improving the system performance, hence cooperative communications have attracted much attention. The relaying nodes essentially operate in either amplify and- forward (AF) and decode-and-forward relaying modes, which are basic for various evolved relaying schemes.the adaptive selective relaying scheme which determines the best among multiple AF relaying nodes having the maximum received SNR through the SR link was proposed, and its performances of outage  channel capacity , symbol error rate were analyzed



FOR MORE DETAILS

ON THE OUTAGE PERFORMANCE OF SELECTION AMPLIFY-AND-FORWARD RELAYING SCHEME

what is spatial Modulation?

Spatial Modulation:
Having one (or few) active RF chains but still being able to exploit all transmit-antenna elements for multiplexing and transmit-diversity gains. Offering Maximum-Likelihood (ML) optimum decoding performance with single-stream decoding complexity Working without the need of (power inefficient) linear modulation schemes (QAM) or allowing us to use constant envelope modulation (PSK) with negligible performance degradation

LINE OF SIGHT: 
                Line of sight (LoS) is a type of propagation that can transmit and receive data only where transmit and receive stations are in view of each other without any sort of an obstacle between them. FM radio, microwave and satellite transmission are examples of line-of-sight communication.  We use space shift keying (SSK)  to present the idea of spatial modulation in line-of-sight (LOS) conditions and show under which conditions high performance can be achieved. The proposed framework is general and can be extended to generalized spatial modulation schemes .LOS transmission is typically seen in point-to-point communication (e.g., backhaul) and millimeter-wave (mmWave) communications.At mm Wave frequencies, the propagation is quasi-optical, sparsely scattered and with large reflection loss (typically 10 dB on average with 4 dB RMS deviation . To focus on our main target—to establish the operating conditions for LOS-SSK—and also for simplicity, only LOS components are considered

                             
                                                           Fig: Line of sight communication

We have shown that SSK can operate efficiently in LOS conditions. Two operating conditions, namely OSSK and BiSSK, are established. A system setup with dual TX arrays and single RX array is proposed to achieve BiSSK. The BEP for both schemes are derived and given in closed form.we analyses to Bit error performance.

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Space Shift Keying for LOS Communication at mmWave Frequencies

How to increase sum rate in mse duality for relay system?

SUM RATE MAXIMIZATION:

               TWO-WAY relay systems in wireless networks have received significant attention due to their high spectral efficiency.To enhance the data rate of non regenerative two-way relay systems, beam forming design schemes were studied based on the iterative method and channel parallelization. a new algorithm using the MSE duality is proposed that maximizes the sum rate for a non regenerative multiple-input multiple-output (MIMO) two-way relay system

                                                                Fig: Relay system

beam forming problem to maximize the sum rate is non-convex we present the per stream MSE duality for the MIMO two-way relay system and exploit the alternate algorithm using the MSE duality and convex optimization programming.The linear beam forming design was investigated to maximize
the sum rate of an MIMO two-way relay system. We derived the per stream MSE duality in the two-way relay system under cross power constraints. A novel iterative algorithm was developed using the per stream MSE duality and convex optimization programming to jointly optimize the linear transceivers.
In general, a half-duplex relay is preferable to full-duplex relay from an implementation aspect, but leads to a loss of spectral efficiency because the transmission and reception require orthogonal time resources. To overcome the loss of spectral efficiency, a two-way relay channel (TWRC), which completes an exchange of messages between two source nodes over two time phases,


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SUM RATE MAXIMIZATION OF AN MIMO TWO-WAY RELAY SYSTEM USING MSE DUALITY

Linear Precoding in MIMO

LDPC CODING:

                    The constraint of minimizing the dependence between the  system’s receiving branches, thus reducing the relevant transmitter and receiver complexities.The concept of Multiple-Input Multiple-Output (MIMO) still represents a prevailing research direction in wireless communications due to its ever increasing capability to offer higher rate, more efficient communications, as measured by spectral utilization, and under low transmitting or receiving power.

                                                                                 

                                                                     Fig:LDPC

Precoding is a generalization of beamforming to support multi-stream (or multi-layer) transmission in multi-antenna wireless communications. In conventional single-stream beamforming, the same signal is emitted from each of the transmit antennas with appropriate weighting (phase and gain) such that the signal power is maximized at the receiver output. When the receiver has multiple antennas, single-stream beam forming cannot simultaneously maximize the signal level at all of the receive antennas.
globally optimal linear precoding techniques were presented for finite alphabet inputs, capable of achieving mutual information rates much higher than the previously presented MWF techniques, by introducing input symbol correlation through a unitary input transformation matrix in conjunction with channel weight adjustment (power allocation). These mutual information maximizing globally optimal pre coders are more appropriate for LDPC codes which are very popular currently, than e.g., Maximal Diversity Precoders (MDP).LDPC codes is addressed under the constraint of minimizing the dependence between the system’s receiving branches, thus reducing the relevant transmitter and receiver complexities.




 FOR MORE DETAILS:

Linear Precoding for MIMO With LDPC Coding and Reduced Complexity

What is Index Modulation in OFDM?

OFDM:
    multi carrier transmission has become an  attractive technique in many wireless standards to meet the increasing demand for high data rate communication systems. One of the most popular multicarrier techniques, orthogonal frequency division multiplexing (OFDM), has developed into a widely-used scheme for wide band digital communication. The major advantage of OFDM over single-carrier schemes is its ability to cope with frequency-selective fading channel with only one-tap equalizer. modulation index of a signal will vary as the modulating signal intensity varies. However some static values enable the various levels to visualised more easily.

                                                    Fig: OFDM with index modulation


an OFDM with generalized index modulation (OFDM-GIM). The generalization is proposed in two aspects. First, a more flexible selection of active sub carriers is proposed to further improve the spectral efficiency.We also demonstrate that the two generalization schemes are compatible with each other and their combined scheme greatly outperforms existing works in spectral efficiency and BER performance, at the cost of a little higher complexity.


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GENERALIZATION OF ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING WITH INDEX

DIGITAL MODULATION TECHNIQUES

DIGITAL MODULATION TECHNIQUES:       
Fundamental to all wireless communications is modulation, the process of impressing the data to be transmitted on the radio carrier. Most wireless transmissions today are digital, and with the limited spectrum available, the type of modulation is more critical than it has ever been.
The main goal of modulation today is to squeeze as much data into the least amount of spectrum possible. That objective, known as spectral efficiency, measures how quickly data can be transmitted in an assigned bandwidth. The unit of measurement is bits per second per Hz (b/s/Hz). Multiple techniques have emerged to achieve and improve spectral efficiency.
Amplitude Shift Keying (ASK) andFrequency Shift Keying (FSK)
 There are three basic ways to modulate a sine wave radio carrier: modifying the amplitude, frequency, or phase. More sophisticated methods combine two or more of these variations to improve spectral efficiency. These basic modulation forms are still used today with digital signals.

1. Three basic digital modulation formats are still very popular with low-data-rate short-range wireless applications: amplitude shift keying (a), on-off keying (b), and frequency shift keying (c). These waveforms are coherent as the binary state change occurs at carrier zero crossing points.
Figure 1 shows a basic serial digital signal of binary zeros and ones to be transmitted and the corresponding AM and FM signals resulting from modulation. There are two types of AM signals: on-off keying (OOK) and amplitude shift keying (ASK). In Figure 1a, the carrier amplitude is shifted between two amplitude levels to produce ASK. In Figure 1b, the binary signal turns the carrier off and on to create OOK.
AM produces sidebands above and below the carrier equal to the highest frequency content of the modulating signal. The bandwidth required is two times the highest frequency content including any harmonics for binary pulse modulating signals.
Frequency shift keying (FSK) shifts the carrier between two different frequencies called the mark and space frequencies, or f_m and f_s(Fig. 1c). FM produces multiple sideband frequencies above and below the carrier frequency. The bandwidth produced is a function of the highest modulating frequency including harmonics and the modulation index, which is:
m = Δf(T)
Δf is the frequency deviation or shift between the mark and space frequencies, or:
Δf = f_s – f_m
T is the bit time interval of the data or the reciprocal of the data rate (1/bit/s).
Smaller values of m produce fewer sidebands. A popular version of FSK called minimum shift keying (MSK) specifies m = 0.5. Smaller values are also used such as m = 0.3.
Here are two ways to further improve the spectral efficiency for both ASK and FSK. First, select data rates, carrier frequencies, and shift frequencies so there are no discontinuities in the sine carrier when changing from one binary state to another. These discontinuities produce glitches that increase the harmonic content and the bandwidth.
The idea is to synchronize the stop and start times of the binary data with when the sine carrier is transitioning in amplitude or frequency at the zero crossing points. This is called continuous phase or coherent operation. Both coherent ASK/OOK and coherent FSK have fewer harmonics and a narrower bandwidth than non-coherent signals.
A second technique is to filter the binary data prior to modulation. This rounds the signal off, lengthening the rise and fall times and reducing the harmonic content. Special Gaussian and raised cosine low pass filters are used for this purpose. GSM cell phones widely use a popular combination, Gaussian filtered MSK (GMSK), which allows a data rate of 270 kbits/s in a 200-kHz channel.
Binary Phase Shift Keying (BPSK) AndQuadrature Phase Shift Keying (QPSK)
 A very popular digital modulation scheme, binary phase shift keying (BPSK), shifts the carrier sine wave 180° for each change in binary state (Fig. 2). BPSK is coherent as the phase transitions occur at the zero crossing points. The proper demodulation of BPSK requires the signal to be compared to a sine carrier of the same phase. This involves carrier recovery and other complex circuitry.

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2. In binary phase shift keying, note how a binary 0 is 0° while a binary 1 is 180°. The phase changes when the binary state switches so the signal is coherent.
A simpler version is differential BPSK or DPSK, where the received bit phase is compared to the phase of the previous bit signal. BPSK is very spectrally efficient in that you can transmit at a data rate equal to the bandwidth or 1 bit/Hz.
In a popular variation of BPSK, quadrature PSK (QPSK), the modulator produces two sine carriers 90° apart. The binary data modulates each phase, producing four unique sine signals shifted by 45° from one another. The two phases are added together to produce the final signal. Each unique pair of bits generates a carrier with a different phase (Table 1).

Figure 3a illustrates QPSK with a phasor diagram where the phasor represents the carrier sine amplitude peak and its position indicates the phase. A constellation diagram in Figure 3b shows the same information. QPSK is very spectrally efficient since each carrier phase represents two bits of data. The spectral efficiency is 2 bits/Hz, meaning twice the data rate can be achieved in the same bandwidth as BPSK

3. Modulation can be represented without time domain waveforms. For example, QPSK can be represented with a phasor diagram (a) or a constellation diagram (b), both of which indicate phase and amplitude magnitudes.
Data Rate And Baud Rate:
 The maximum theoretical data rate or channel capacity (C) in bits/s is a function of the channel bandwidth (B) channel in Hz and the signal-to-noise ratio (SNR):
C = B log₂ (1 + SNR)
This is called the Shannon-Hartley law. The maximum data rate is directly proportional to the bandwidth and logarithmically proportional the SNR. Noise greatly diminishes the data rate for a given bit error rate (BER).
Another key factor is the baud rate, or the number of modulation symbols transmitted per second. The term symbol in modulation refers to one specific state of a sine carrier signal. It can be an amplitude, a frequency, a phase, or some combination of them. Basic binary transmission uses one bit per symbol.
In ASK, a binary 0 is one amplitude and a binary 1 is another amplitude. In FSK, a binary 0 is one carrier frequency and a binary 1 is another frequency. BPSK uses a 0° shift for a binary 0 and a 180° shift for a binary 1. In each of these cases there is one bit per symbol.
Data rate in bits/s is calculated as the reciprocal of the bit time (t_b):
bits/s = 1/t_b
With one symbol per bit, the baud rate is the same as the bit rate. However, if you transmit more bits per symbol, the baud rate is slower than the bit rate by a factor equal to the number of bits per symbol. For example, if 2 bits per symbol are transmitted, the baud rate is the bit rate divided by 2. For instance, with QPSK a 70 Mb/s data stream is transmitted at a baud rate of 35 symbols/second.
Multiple Phase Shift Keying (M-PSK):
 QPSK produces two bits per symbol, making it very spectrally efficient. QPSK can be referred to as 4-PSK because there are four amplitude-phase combinations. By using smaller phase shifts, more bits can be transmitted per symbol. Some popular variations are 8-PSK and 16-PSK.
8-PSK uses eight symbols with constant carrier amplitude 45° shifts between them, enabling three bits to be transmitted for each symbol. 16-PSK uses 22.5° shifts of constant amplitude carrier signals. This arrangement results in a transmission of 4 bits per symbol.
While Multiple Phase Shift Keying (M-PSK) is much more spectrally efficient, the greater the number of smaller phase shifts, the more difficult the signal is to demodulate in the presence of noise. The benefit of M-PSK is that the constant carrier amplitude means that more efficient nonlinear power amplification can be used.
Quadrature Amplitude Modulation(QAM):
 The creation of symbols that are some combination of amplitude and phase can carry the concept of transmitting more bits per symbol further. This method is called quadrature amplitude modulation (QAM). For example, 8QAM uses four carrier phases plus two amplitude levels to transmit 3 bits per symbol. Other popular variations are 16QAM, 64QAM, and 256QAM, which transmit 4, 6, and 8 bits per symbol respectively (Fig. 4).

4. 16QAM uses a mix of amplitudes and phases to achieve 4 bits/Hz. In this example, there are three amplitudes and 12 phase shifts.
While QAM is enormously efficient of spectrum, it is more difficult to demodulate in the presence of noise, which is mostly random amplitude variations. Linear power amplification is also required. QAM is very widely used in cable TV, Wi-Fi wireless local-area networks (LANs), satellites, and cellular telephone systems to produce maximum data rate in limited bandwidths.
Amplitude Phase Shift Keying (APSK):
 Amplitude phase shift keying (APSK), a variation of both M-PSK and QAM, was created in response to the need for an improved QAM. Higher levels of QAM such as 16QAM and above have many different amplitude levels as well as phase shifts. These amplitude levels are more susceptible to noise.
Furthermore, these multiple levels require linear power amplifiers (PAs) that are less efficient than nonlinear (e.g., class C). The fewer the number of amplitude levels or the smaller the difference between the amplitude levels, the greater the chance to operate in the nonlinear region of the PA to boost power level.
APSK uses fewer amplitude levels. It essentially arranges the symbols into two or more concentric rings with a constant phase offset θ. For example, 16APSK uses a double-ring PSK format (Fig. 5). This is called 4-12 16APSK with four symbols in the center ring and 12 in the outer ring.

5. 16APSK uses two amplitude levels, A1 and A2, plus 16 different phase positions with an offset of θ. This technique is widely used in satellites.
Two close amplitude levels allow the amplifier to operate closer to the nonlinear region, improving efficiency as well as power output. APSK is used primarily in satellites since it is a good fit with the popular traveling wave tube (TWT) PAs.
Orthogonal Frequency DivisionMultiplexing (OFDM):
 Orthogonal frequency division multiplexing (OFDM) combines modulation and multiplexing techniques to improve spectral efficiency. A transmission channel is divided into many smaller subchannels or subcarriers. The subcarrier frequencies and spacings are chosen so they’re orthogonal to one another. Their spectra won’t interfere with one another, then, so no guard bands are required (Fig. 6).

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6. In the OFDM signal for the IEEE 802.11n Wi-Fi standard, 56 subcarriers are spaced 312.5 kHz in a 20-MHz channel. Data rates to 300 Mbits/s can be achieved with 64QAM.
The serial digital data to be transmitted is subdivided into parallel slower data rate channels. These lower data rate signals are then used to modulate each subcarrier. The most common forms of modulation are BPSK, QPSK, and several levels of QAM. BPSK, QPSK, 16QAM, and 64QAM are defined with 802.11n. Data rates up to about 300 Mbits/s are possible with 64QAM.
The complex modulation process is only produced by digital signal processing (DSP) techniques. An inverse fast Fourier transform (IFFT) generates the signal to be transmitted. An FFT process recovers the signal at the receiver.
OFDM is very spectrally efficient. That efficiency level depends on the number of subcarriers and the type of modulation, but it can be as high as 30 bits/s/Hz. Because of the wide bandwidth it usually occupies and the large number of subcarriers, it also is less prone to signal loss due to fading, multipath reflections, and similar effects common in UHF and microwave radio signal propagation.
Currently, OFDM is the most popular form of digital modulation. It is used in Wi-Fi LANs, WiMAX broadband wireless, Long Term Evolution (LTE) 4G cellular systems, digital subscriber line (DSL) systems, and in most power-line communications (PLC) applications. For more, see “Orthogonal Frequency-Division Multiplexing (OFDM): FAQ Tutorial.”
Determining Spectral Efficiency:
 Again, spectral efficiency is a measure of how quickly data can be transmitted in an assigned bandwidth, and the unit of measurement is bits/s/Hz (b/s/Hz). Each type of modulation has a maximum theoretical spectral efficiency measure (Table 2).

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SNR is another important factor that influences spectral efficiency. It also can be expressed as the carrier to noise power ratio (CNR). The measure is the BER for a given CNR value. BER is the percentage of errors that occur in a given number of bits transmitted. As the noise becomes larger compared to the signal level, more errors occur.
Some modulation methods are more immune to noise than others. Amplitude modulation methods like ASK/OOK and QAM are far more susceptible to noise so they have a higher BER for a given modulation. Phase and frequency modulation (BPSK, FSK, etc.) fare better in a noisy environment so they require less signal power for a given noise level (Fig. 7).
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7. This is a comparison of several popular modulation methods and their spectral efficiency expressed in terms of BER versus CNR. Note that for a given BER, a greater CNR is needed for the higher QAM levels.
Other Factors Affecting SpectralEfficiency
 While modulation plays a key role in the spectral efficiency you can expect, other aspects in wireless design influence it as well. For example, the use of forward error correction (FEC) techniques can greatly improve the BER. Such coding methods add extra bits so errors can be detected and corrected.
These extra coding bits add overhead to the signal, reducing the net bit rate of the data, but that’s usually an acceptable tradeoff for the single-digit dB improvement in CNR. Such coding gain is common to almost all wireless systems today.
Digital compression is another useful technique. The digital data to be sent is subjected to a compression algorithm that greatly reduces the amount of information. This allows digital signals to be reduced in content so they can be transmitted as shorter, slower data streams.
For example, voice signals are compressed for digital cell phones and voice over Internet protocol (VoIP) phones. Music is compressed in MP3 or AAC files for faster transmission and less storage. Video is compressed so high-resolution images can be transmitted faster or in bandwidth-limited systems.
Another factor affecting spectral efficiency is the use of multiple-input multiple-output (MIMO), which is the use of multiple antennas and transceivers to transmit two or more bit streams. A single high-rate stream is divided into two parallel streams and transmitted in the same bandwidth simultaneously.
By coding the streams and their unique path characteristics, the receiver can identify and demodulate each stream and reassemble it into the original stream. MIMO, therefore, improves data rate, noise performance, and spectral efficiency. Newer wireless LAN (WLAN) standards like 802.11n and 802.11ac/ad and cellular standards like LTE and WiMAX use MIMO. For more, see “How MIMO Works.”
Implementing Modulation AndDemodulation:
 In the past, unique circuits implemented modulation and demodulation. Today, most modern radios are software-defined radios (SDR) where functions like modulation and demodulation are handled in software. DSP algorithms do the job previously assigned to modulator and demodulator circuits.
The modulation process begins with the data to be transmitted being fed to a DSP device that generates two digital outputs, which are needed to define the amplitude and phase information required at the receiver to recover the data. The DSP produces two baseband streams that are sent to digital-to-analog converters (DACs) that produce the analog equivalents.
These modulation signals feed the mixers along with the carrier. There is a 90° shift between the carrier signals to the mixers. The resulting quadrature output signals from the mixers are summed to produce the signal to be transmitted. If the carrier signal is at the final transmission frequency, the composite signal is ready to be amplified and sent to the antenna. This is called direct conversion. Alternately, the carrier signal may be at a lower intermediate frequency (IF). The IF signal is upconverted to the final carrier frequency by another mixer before being applied to the transmitter PA.
At the receiver, the signal from the antenna is amplified and downconverted to IF or directly to the original baseband signals. The amplified signal from the antenna is applied to mixers along with the carrier signal. Again, there is a 90° shift between the carrier signals applied to the mixers.
The mixers produce the original baseband analog signals, which are then digitized in a pair of analog-to-digital converters (ADCs) and sent to the DSP circuitry where demodulation algorithms recover the original digital data.
There are three important points to consider. First, the modulation and demodulation processes use two signals in quadrature with one another. The DSP calculations call for two quadrature signals if the phase and amplitude are to be preserved and captured during modulation or demodulation.
Second, the DSP circuitry may be a conventional programmable DSP chip or may be implemented by fixed digital logic implementing the algorithm. Fixed logic circuits are smaller and faster and are preferred for their low latency in the modulation or demodulation process.
Third, the PA in the transmitter needs to be a linear amplifier if the modulation is QPSK or QAM to faithfully reproduce the amplitude and phase information. For ASK, FSK, and BPSK, a more efficient non-linear amplifier may be used.
The Pursuit Of Greater SpectralEfficiency:
 With spectrum being a finite entity, it is always in short supply. The Federal Communications Commission (FCC) and other government bodies have assigned most of the electromagnetic frequency spectrum over the years, and most of that is actively used.
Shortages now exist in the cellular and land mobile radio sectors, inhibiting the expansion of services such as high data speeds as well as the addition of new subscribers. One approach to the problem is to improve the efficiency of usage by squeezing more users into the same or less spectrum and achieving higher data rates. Improved modulation and access methods can help.
One of the most crowded areas of spectrum is the land mobile radio (LMR) and private mobile radio (PMR) spectrum used by the federal government, state governments, and local public safety agencies like fire and police departments. Currently they’re assigned spectrum by FCC license in the 150- to 174-MHz VHF spectrum and the 421- to 512-MHz UHF spectrum.
Most radio systems and handsets use FM analog modulation that occupies a 25-kHz channel. Recently the FCC has required all such radios to switch over to 12.5-kHz channels. This conversion, known as narrowbanding, doubles the number available channels.
Narrowbanding is expected to improve a radio’s ability to get access to a channel. It also means that more radios can be added to the system. This conversion must take place before January 1, 2013. Otherwise, an agency or business could lose its license or be fined. This switchover will be expensive as new radio systems and handsets are required.
In the future, the FCC is expected to mandate a further change from the 12.5-kHz channels to 6.25-kHz channels, again doubling capacity without increasing the amount of spectrum assigned. No date for that change has been assigned.
The new equipment can use either analog or digital modulation. It is possible to put standard analog FM in a 12.5-kHz channel by adjusting the modulation index and using other bandwidth-narrowing techniques. However, analog FM in a 6.25-kHz channel is unworkable, so a digital technique must be used.
Digital methods digitize the voice signal and use compression techniques to produce a very low-rate serial digital signal that can be modulated into a narrow band. Such digital modulation techniques are expected to meet the narrowbanding goal and provide some additional performance advantages.
New modulation techniques and protocols—including P25, TETRA, DMR, dPMR, and NXDN—have been developed to meet this need. All of these new methods must meet the requirements of the FCC’s Part 90 regulations and/or the regulations of the European Telecommunications Standards Institute (ETSI) standards such as TS-102 490 and TS-102-658 for LMR.
The most popular digital LMR technology, P25, is already in wide use in the U.S. with 12.5-kHz channels. Its frequency division multiple access (FDMA) method divides the assigned spectrum into 6.25-kHz or 12.5-kHz channels.
Phase I of the P25 project uses a four-symbol FSK (4FSK) modulation. Standard FSK, covered earlier, uses two frequencies or “tones” to achieve 1-bit/Hz. However, 4FSK is a variant that uses four frequencies to provide 2-bits/Hz efficiency. With this scheme the standard achieves a 9600-bit/s data rate in a 12.5-KHz channel. With 4FSK, the carrier frequency is shifted by ±1.8 kHz or ±600 Hz to achieve the four symbols.
In Phase 2, a compatible QPSK modulation scheme is used to achieve a similar data rate in a 6.25-kHz channel. The phase is shifted either ±45° or ±135° to get the four symbols. A unique demodulator has been developed to detect either the 4FSK or QPSK signal to recover the digital voice. Only different modulators on the transmit end are needed to make the transition from Phase 1 to Phase 2.
The most widespread digital LMR technology outside of the U.S. is TETRA, or Terrestrial Trunked Radio. This ETSI standard is universally used in Europe as well as in Africa, Asia, and Latin America. Its time division multiple access (TDMA) approach multiplexes four digital voice or data signals into a 25-kHz channel.
A single channel is used to support a digital stream of four time slots for the digital data for each subscriber. This is equivalent to four independent signals in adjacent 6.25-kHz channels. The modulation is π/4-DQPSK, and the data rate is 7.2 kbits/s per time slot.
Another ETSI standard, digital mobile radio (DMR), uses a 4FSK modulation scheme in a 12.5-kHz channel. It can achieve a 6.25-kHz channel equivalent in a 12.5-kHz channel by using two-slot TDMA. The voice is digitally coded with error correction, and the basic rate is 3.6 kbits/s. The data rate in the 12.5-kHz band is 9600 kbits/s.
A similar technology is dPMR, or digital private mobile radio standard. This ETSI standard also uses a 4FSK modulation scheme, but the access is FDMA in 6.25-kHz channels. The voice coding rate is also 3.6 kbits/s with error correction.
LMR manufacturers Icom and Kenwood have developed NXDN, another standard for LMR. It is designed to operate in either 12.5- or 6.25-kHz channels using digital voice compression and a four-symbol FSK system. A channel may be selected to carry voice or data.
The basic data rate is 4800 bits/s. The access method is FDMA. NXDN and dPMR are similar, as they both use 4FSK and FDMA in 6.25-kHz channels. The two methods are not compatible, though, as the data protocols and other features are not the same.
Because all of these digital techniques are similar and operate in standard frequency ranges, Freescale Semiconductor was able to make a single-chip digital radio that includes the RF transceiver plus an ARM9 processor that can be programmed to handle any of the digital standards. The MC13260 system-on-a-chip (SoC) can form the basis of a handset radio for any one if not multiple protocols. For more, see “Chip Makes Two-Way Radio Easy.”
Another example of modulation techniques improving spectral efficiency and increasing data throughput in a given channel is a new technique from NovelSat called NS3 modulation. Satellites are positioned in an orbit around the equator about 22,300 miles from earth. This is called the geostationary orbit, and satellites in it rotate in synchronization with the earth so they appear fixed in place, making them a good signal relay platform from one place to another on earth.
Satellites carry several transponders that pick up the weak uplink signal from earth and retransmit it on a different frequency. These transponders are linear and have a fixed bandwidth, typically 36 MHz. Some of the newer satellites have 72-MHz channel transponders. With a fixed bandwidth, the data rate is somewhat fixed as determined by the modulation scheme and access methods.
The question is how one deals with the need to increase the data rate in a remote satellite as required by the ever increasing demand for more traffic capacity. The answer lies in simply creating and implementing a more spectrally efficient modulation method. That’s what NovelSat did. Its NS3 modulation method increases bandwidth capacity up to 78%.
That level of improvement comes from a revised version of APSK modulation covered earlier. One commonly used satellite transmission standard, DVB-S2, is a single carrier (typically L-band, 950 to 1750 MHz) that can use QPSK, 8PSK, 16APSK, and 32APSK modulation with different forward error correction (FEC) schemes. The most common application is video transmission.
NS3 improves on DVB-S2 by offering 64APSK with multiple amplitude and phase symbols to improve efficiency. Also included is low density parity check (LDPC) coding. This combination provides a maximum data rate of 358 Mbits/s in a 72-MHz transponder. Because the modulation is APSK, the TWT PAs don’t have to be backed off to preserve perfect linearity. As a result, they can operate at a higher power level and achieve the higher data rate with a lower CNR than DVB-S2. NovelSat offers its NS1000 modulator and NS2000 demodulator units to upgrade satellite systems to NS3. In most applications, NS3 provides a data rate boost over DVB-S2 for a given CNR.

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