Wireless Communication System Using Bpsk Modulation

Published Date: 02 Nov 2017

Abstract: With increasing technology many new techniques are coming with which we can improve today’s available techniques for better future. In this project we are trying to show new communication technique using multiple inputs and multiple outputs (MIMO). With MIMO we are using orthogonal frequency division multiplexing (OFDM) which is useful in sending large amount of data in single frequency band. MIMO can be used with high data rate and reduced distortion with V-BLAST technique. In MIMO communication system V-BLAST, D-BLAST and Alamouti methods are used to improving bit error rate and signal to noise ratio. So In this I am using V-BLAST and D-BLAST algorithms and develop code using BPSK modulation system. For V-BLAST processing algorithms and CCI cancellation has two types of equalizers zero forcing (ZF) and Minimum Mean Square Error (MMSE). For project we use MMSE equalizer using Rayleigh channel. We consider spatial multiplexing systems in correlated multiple-input multiple-output (MIMO) Rayleigh channels with equal power allocated to each transmit antenna

Key Words: MIMO ,OFDM ,Wireless.

INTRODUCTION

Orthogonal frequency division multiplexing (OFDM) has become a popular technique for transmission of signals over wireless channels. OFDM has been adopted in several wireless standards such as digital audio broadcasting (DAB), digital video broadcasting (DVB-T), the IEEE 802.11a [1] local area network (LAN) standard and the IEEE 802.16a [2] metropolitan area network (MAN) standard. OFDM is also being pursued for dedicated short-range communications (DSRC) for road side to vehicle communications and as a potential candidate for fourth-generation (4G) mobile wireless systems. Orthogonal frequency division multiplexing (OFDM) has become a popular technique for transmission of signals over wireless channels. OFDM has been adopted in several wireless standards such as digital audio broadcasting (DAB), digital video broadcasting (DVB-T), the IEEE 802.11a [1] local area network (LAN) standard and the IEEE 802.16a [2] metropolitan area network (MAN) standard. OFDM is also being pursued for dedicated short-range communications (DSRC) for road side to vehicle communications and as a potential candidate for fourth-generation (4G) mobile wireless systems. OFDM converts a frequency-selective channel into a parallel collection of frequency flat sub channels. The subcarriers have the minimum frequency separation required to maintain orthogonality of their corresponding time domain waveforms, yet the signal spectra corresponding to the different subcarriers overlap in frequency. Hence, the available bandwidth is used very efficiently. If knowledge of the channel is available at the transmitter, then the OFDM transmitter can adapt its signaling strategy to match the channel. Due to the fact that OFDM uses a large collection of narrowly spaced sub channels, these adaptive strategies can approach the ideal water pouring capacity of a frequency- selective channel. In practice this is achieved by using adaptive bit loading techniques, where different sized signal constellations are transmitted on the subcarriers.

OFDM is a block modulation scheme where a block of information symbols is transmitted in parallel on subcarriers. The time duration of an OFDM symbol is times larger than that of a single-carrier system. An OFDM modulator can be implemented as an inverse discrete Fourier transform (IDFT) on a block of information symbols followed by an analog-to-digital converter (ADC). To mitigate the effects of intersymbol interference (ISI) caused by channel time spread, each block of IDFT coefficients is typically preceded by a cyclic prefix (CP) or a guard interval consisting of samples, such that the length of the CP is at least equal to the channel length. Under this condition, a linear convolution of the transmitted sequence and the channel is converted to a circular convolution. As a result, the effects of the ISI are easily and completely eliminated. Moreover, the approach enables the receiver to use fast signal processing transforms such as a fast Fourier transform (FFT) for OFDM implementation [3]. Similar techniques can be employed in single-carrier systems as well, by preceding each transmitted data block of length by a CP of length , while using frequency- domain equalization at the receiver.

OFDM

Orthogonal Frequency Division Multiplexing (OFDM) is a popular modulation scheme that is used in wireless LAN standards like 802.11a, g, HIPERLAN/2 and in the Digital Video Broadcasting standard (DVBT). It is also used in the ADSL standard, where it is referred to as Discrete Multitone modulation. OFDM modulation divides a broadband channel into many parallel sub channels. This makes it a very efficient scheme for transmission in multipath wireless channels. The use of an FFT/IFFT pair for modulation and demodulation make it computationally efficient as well. The transmitted signals arrive at the receiver after being reflected from many objects. Sometimes the reflected signals add up in phase and sometimes they add up out of phase causing a "fade". This causes the received signal strength to fluctuate constantly. Also, different sub channels are distorted differently as shown in Figure . An OFDM receiver has to sense the channel and correct these distortions on each of the sub channels before the transmitted data can be extracted. OFDM is effective in correcting such frequency selective distortions

Figure 1. OFDM SIGNAL

OFDM has many advantages over other transmission techniques. One such advantage is high spectral efficiency (measured in bits/sec/Hz). The "Orthogonal" part of the name refers to a precise mathematical relationship between the frequencies of the sub channels that make up the OFDM system. Each of the frequencies is an integer multiple of a fundamental frequency. This ensures that even though the sub channels overlap they do not interfere with each other. This results in high spectral efficiency. The use of IFFT and FFT for modulation and demodulation results in computationally efficient OFDM modems. The block diagram of an OFDM modulator and demodulator are shown in Figure .

Figure 2. OFDM

MIMO

Various schemes that employ multiple antennas at the transmitter and receiver are being considered to improve the range and performance of communication systems. By far the most promising multiple antenna technology today happens to be the so called multiple-input multiple-output (MIMO) system. MIMO systems employ multiple antennas at both the transmitter and receiver as shown in Figure

Figure 3. MIMO

They transmit independent data (say x1, x2, …, xN) on different transmit antennas simultaneously and in the same frequency band. At the receiver, a MIMO decoder users M≥N antennas. Assuming N receive antennas, and representing the signal received by each antenna as rj we have:

As can be seen from the above set of equations, in making their way from the transmitter to the receiver, the independent signals {x1, x2, …, xN} are all combined. Traditionally this "combination" has been treated as interference. However, by treating the channel as a matrix, we can in fact recover the independent transmitted streams {xi}. To recover the transmitted data stream {xi} from the {rj} we must estimate the individual channel weights hij, construct the channel matrix H. Having estimated H, multiplication of the vector r with the inverse of H produces the estimate of the transmitted vector x. This is equivalent to solving a set of N linear equations in N unknowns. Because multiple data streams are transmitted in parallel from different antennas there is a linear increase in throughput with every pair of antennas added to the system. An important fact to note is that unlike traditional means of increasing throughput, MIMO systems do not increase bandwidth in order to increase throughput. They simply exploit the spatial dimension by increasing the number of unique spatial paths between the transmitter and reciver

MIMO Fundamental

MIMO systems are found to be promising technique for high data rate in wireless communication systems. There are two types of MIMO systems. Space time coding (STC) and spatial multiplexing. We are using spatial multiplexing technique. Which requires MIMO antenna configuration In spatial multiplexing, a high rate signal is split into multiple lower rate streams and each stream is transmitted from a different transmit antenna in the same frequency channel. If these signals arrive at the receiver antenna array with sufficiently different spatial signatures, the receiver can separate these streams into (almost) parallel channels. Spatial multiplexing is a very powerful technique for increasing channel capacity at higher signal-to-noise ratios (SNR).

MIMO-OFDM SYSTEM MODEL

A multicarrier system can be efficiently implemented in discrete time using an inverse FFT (IFFT) to act as a modulator and an FFT to act as a demodulator. The transmitted data are the "frequency" domain coefficients and the samples at the output of the IFFT stage are "time" domain samples of the transmitted waveform. Fig. shows a typical MIMO-OFDM implementation .

Figure 4 MIMO-OFDM SYSTEM MODEL

Let X={X0, X1,… XN-1} denote the length of N data symbol block. the IDFT of the data block X yields the time domain sequence X={x0,x1,…..,xN-1} that is

Xn=IFFTN{XN} (n). (1)

To mitigate the effects of channel delay spread, a guard interval comprised of either a CP or suffix is appended to the sequence . In case of a CP, the transmitted sequence with guard interval is

xng =x(n)N , n= -G,….,-1,0,1…..,N-1 (2)

where is the guard interval length in samples, and is the residue of modulo . The OFDM complex envelope is obtained by passing the sequence through a pair of ADCs (to generate the real and imaginary components) with sample rate s, and the analog and signals are unconverted to an RF carrier frequency. To avoid ISI, the CP length must equal or exceed the length of the discrete-time channel impulse response . The time required to transmit one OFDM symbol is called the OFDM symbol time. The OFDM signal is transmitted over the pass band RF channel, received, and down converted to base band. Due to the CP, the discrete linear convolution of the transmitted sequence with the channel impulse response becomes a circular convolution. Hence, at the receiver the initial samples from each received block are removed, followed by an -point discrete Fourier transform (DFT) on the resulting sequence.

MIMO V-BLAST

Wireless communication system having different method are used and to get improve the result in the form of higher data rate. So many techniques used in MIMO. V-BLAST, D-BLAST and Alamuti are the methods used in MIMO technology. V-BLAST means vertical-bell laboratories layered space time. This method depends on layered space time coding .blast is connected to receiver side of MIMO system. This is also known as receiver signal processing algorithm. V-BLAST is used to reduced the distortion due to interference from the channel as compared to other techniques V-BLAST is better than D-BLAST and Alamuti techniques in communication.

V-BLAST it first detects the most powerful signal or highest SNR and then it regenerated the received signal from the available channel. V-BLAST having higher spectral efficiency with high power and implementation complexity is low that’s why gets better result in this method. in this project we used V-BLAST method for getting better BER and SNR values as compared to other techniques. V-BLAST method depends on ZF (zero forcing) and minimum mean square error MMSE equalizer. V BLAST techniques having low complexity then we use ZF VBLAST for recursive four steps ordering, nulling,slicing and cancelling .in this project used V-BLAST method for processing algorithm and CCI cancellation. The MIMO OFDM V-BLAST system operates in the 17 GHz unlicensed frequency band with an available bandwidth of 200 MHz (17.1–17.3 GHz) that is divided into four 50 MHz-width channels not simultaneously selectable. OFDM with L = 128 subcarriers (frequency sub channels) is designed for each of these 50 MHz wide channels. The indoor coverage ranges from 5 m for non line-of-sight to 20 m for line-of sight (LOS). The indoor environment is the ideal rich-10 scattering environment necessary by the V-BLAST processing to get CCI cancellation at the receiver. V-BLAST algorithm with OSIC processing implements a non-linear detection technique based on Zero Forcing (ZF) filtering combined with symbol cancellation to improve the performance.

V-BLAST Processing Algorithm and CCI cancellation

Theoretically ML detection would be optimal for V-BLAST detection. However, it's too complex to implement. For example, in the case of 6 transmit antennas and 4-QAM modulation, a total of 46 = 4096 comparisons would have to be made for each transmitted symbol. Therefore, V-BLAST performs a non-linear detection that extracts data streams by a ZF or MMSE algorithm w(k) with ordered successive interference cancellation (OSIC). Co Channel Interference traditional approaches require nulling vector being orthogonal to N-1 rows of H where as OSIC requires nulling vector being orthogonal to N-i undetected components per iteration i. there are two algorithms are use as follows .Zero-Forcing (ZF) is the decorrelating receiver where H† is Moore-Penrose pseudo inverse of H

w(k) = H† = (H*H)-1H* (3)

Detection order depends on which subset of (M-i) rows w ki should be constrained by since each component of the signal uses the same constellation the component with the smallest ki will dominate the error performance. At each symbol time, it first detects the "strongest" layer (in the sense of SNR and ? = Es/No at the receiver branch) then cancels the effect of this strongest layer from each of the received signals and then proceeds to detect the "strongest" of the remaining layers. It is assumed that the receiver perfectly knows the channel matrix H, which can be accomplished by classical means of channel estimation, e.g. insertion of training bits in the transmitted TDMA frames.

The system works in single-hop ad hoc networks and provides a wireless access for slowly moving users (about 1 m/s) in an indoor environment. The proposed system is a single-TDMA stream scheme (for multiuser operation) capable to handle rates ranging adaptively from 64 kbps to 100 Mbps after variable-rate adaptive modulation is implemented, according to the subcarrier SNR and target BER. In that sense, the system can implement different modulation schemes (BPSK, QPSK, 16-QAM, 64- QAM) and parallel convolution turbo code with rates 1/2, 2/3 and 3/4. The MIMO OFDM V-BLAST system operates in the 17 GHz unlicensed frequency band with an available bandwidth of 200 MHz (17.1–17.3 GHz) that is divided into four 50 MHz-width channels not simultaneously selectable. OFDM with is designed for each of these 50 MHz wide channels. The indoor coverage ranges from 5 m for non line-of-sight to 20 m for line-of sight (LOS).

Result

Display parameters of the V-BLAST

No. of Transmission bits

No. of Channels Used.

Display Graph of Bit stream and no. of bits.

Display Graph of BER Vs. SNR

SCREEN SHOTS:

MAIN SCREEN:

BLAST SCREEN:

AFTER PUSHING BLAST BUTTON:

AFTER PUSHING BER BUTTON:

Conclusion

This project has thoroughly analyzed the performance of the proposed MIMO OFDM V-BLAST system for different antenna configurations and propagation conditions. It has found that V-BLAST can get potentially higher spectral efficiency because no orthogonal transmitted signals and received co-channel signals are separated by decorrelation (processing algorithm) due to multipath. The report has shown that MIMO OFDM V-BLAST systems are capable of improving bit rate without increasing total transmit power or required bandwidth with V-BLAST processing at the receiver as an efficient CCI cancellation technique. Further research would describe the effect –under different array configurations and propagation conditions- of MMSE filtering in V-BLAST processing, Trellis encoding and Viterbi decoding, and variable-rate variable-power adaptive modulation schemes in the MIMO OFDM V-BLAST analyzed in this study.