**Novel Techniques for Multiple Antenna**

Transmission and Detection

Transmission and Detection

**Outline**

**Introduction and Literature Review.**

System Models, Analysis and Simulations.

System Models, Analysis and Simulations.

**My Contributions in this Project & Conclusion**

**By: Khaled Alhazmi**

**Receive Diversity; System Model, Analysis and Simulations.**

Vertical Bell Labs Architecture for Space-Time (VBLAST); System Model, Analysis and Simulations.

Various Equalization Techniques in MIMO; System Model, Analysis and Simulations.

Various Modulation Schemes in MIMO; Analysis and Simulations.

Space-Time Block Code (STBC); System Model, Analysis and Simulations.

STBC with more Tx and One Rx Antenna; Analysis and Simulations.

STBC with more Tx and Two Rx Antennas; Analysis and Simulations.

Precoding Technique in STBC; System Model, Analysis and Simulations.

Antenna Selection Technique in STBC; System Model, Analysis and Simulations.

Vertical Bell Labs Architecture for Space-Time (VBLAST); System Model, Analysis and Simulations.

Various Equalization Techniques in MIMO; System Model, Analysis and Simulations.

Various Modulation Schemes in MIMO; Analysis and Simulations.

Space-Time Block Code (STBC); System Model, Analysis and Simulations.

STBC with more Tx and One Rx Antenna; Analysis and Simulations.

STBC with more Tx and Two Rx Antennas; Analysis and Simulations.

Precoding Technique in STBC; System Model, Analysis and Simulations.

Antenna Selection Technique in STBC; System Model, Analysis and Simulations.

**Discussions and Future Work.**

Conclusions.

Conclusions.

Challenges in Wireless Communication

The main challenge with wireless communication is

channel fading.

Another challenge for current and future wireless communication is to provide

high capacity and data rates.

To overcome these challenges, multiple input and multiple output (MIMO) is proposed,

where multiple antennas at the transmitter and at the receiver are employed to combat fading and to increase capacity and data rates.

Use of multiple antennas in communication system guarantees that

at least one of the path will less effect the transmitted signal,

thus improves the signal detection at the receiver.

Receive Diversity

The use of multiple antennas at the receiver, known as diversity, is the most common technique for mitigating effects of multipath fading in wireless communications.

If multiple antennas are employed at the receiver, the system is known as RECEIVE DIVERSITY.

The received signals through multiple receive antennas are combined in some fashion to maximize the received signal strength.

One of the optimum receive diversity combining technique is Maximal Ratio Combining (MRC).

Fig. 1. Maximal Ratio Combining (MRC)

Receive Diversity; System Model

Fig. 1. Maximal Ratio Combining (MRC)

Receive Diversity; Simulations

Rayleigh fading channel is used in this simulation.

I assumed that fading channel coefficients are known at the receiver.

Maximum likelihood detection is employed at the receiver to estimate the transmitted signals.

Fig. 11. MRC Diversity over Rayleigh Fading Channel.

Simulated using Monte Carlo simulation.

BER of MRC system is obtained with BPSK.

That increasing the number of receive antennas decrease the BER and thus, improving the system’s reliability and performance.

Example: at SNR of 15 dB, the BER

1- 8x10-2

2- 7x10-3

3- 1x10-4

4-2.6x10-5

Receive Diversity

The use of multiple antennas at the receiver, known as diversity, is the most common technique for mitigating effects of multipath fading in wireless communications.

If multiple antennas are employed at the receiver, the system is known as RECEIVE DIVERSITY.

The received signals through multiple receive antennas are combined in some fashion to maximize the received signal strength.

One of the optimum receive diversity combining technique is Maximal Ratio Combining (MRC).

Fig. 1. Maximal Ratio Combining (MRC)

Receive Diversity; System Model

If multiple antennas are employed at the receiver, the system is known as RECEIVE DIVERSITY.

The received signals through multiple receive antennas are combined in some fashion to maximize the received signal strength.

One of the optimum receive diversity combining technique is Maximal Ratio Combining (MRC).

Rayleigh fading channel is used in this simulation.

I assumed that fading channel coefficients are known at the receiver.

Maximum likelihood detection is employed at the receiver to estimate the transmitted signals.

Receive Diversity; Simulation # 1

Simulated using Monte Carlo simulation.

BER of MRC system is obtained with BPSK.

That increasing the number of receive antennas decrease the BER and thus, improving the system’s reliability and performance.

Example: at SNR of 15 dB, the BER

1- 8x10-2

2- 7x10-3

3- 1x10-4

4-2.6x10-5

Vertical Bell Laboratories Layered Space-Time VBLAST

VBLAST provides spatial diversity.

The incoming data stream is divided into parallel streams and each steam is modulated and sent to the respective transmitter.

Each stream is taken as desired signal and other streams are taken as interfering signals. Signal processing technique are employed at the receiver to remove interference.

Provides high data rates.

MIMO System Model, and simulation

Multiple-Input Multiple Output - MIMO

If multiple antennas are employed both at the transmitter and receiver side, then it is said to be multiple-input and multiple-output (MIMO) system.

Two most popular techniques of MIMO are explored in this project;

one is based on VBLAST structure

and other on STBC structure.

VBLAST is proposed by Foschini et. al. and STBC is proposed by Alamouti, and then extended to more than two transmit antennas by Tarokh et. al.

MIMO simulation #2

Increasing number of antennas at the transmitter side surely improves the system’s reliability and error rate.

For example, at SNR of 15 dB,

2x2 MIMO is 2x10-4,

One receive antennas 8x10-2

Two receive antennas 7x10-3

It proves the significance of employing more antennas at the transmitter side.

Equalization Techniques in MIMO

The equalization is a technique to mitigate the transmission impairment at receiver end.

The equalization generally uses filtering technique so that the error between the actual and desired output is minimized.

In digital communication equalization is used to solve interference problem at the receiver end.

Thus, equalizer is to reverse distortions by the channel.

1- Zero- Forcing (ZF)Equalizer

The ZF equalizer takes one symbol and tries to remove the interference from that and provides zero response for other symbols.

Equalizer estimates the value of transmitted signal and compares it with the signal at equalizer output and uses average mean square error (MSE) to minimize the difference between two

2- Minimum Mean Square Error (MMSE) Equalizer

In case of successive detection of signals the output of first detector can be used to detect the signals arriving afterwards.

3- Successive Interference Cancellation (SIC)

In Maximum Likelihood (ML) Detection, the equalizer tests all possible data sequences and selects the sequence that has maximum probability at the output.

4- Maximum Likelihood (ML) Detection

Equalization Techniques in MIMO Simulation # 3

in this simulation, I tested 2x2 MIMO using different equalizers.

It is clear that ML detection technique provides improvement in BER

as compared to other detection techniques

Analysis of Modulation Schemes in MIMO System# 4

STBC system model

STBC simulations

Space Time Block Code - STBC

MIMO simulation

Increasing number of antennas at the transmitter side surely improves the system’s reliability and error rate.

For example, at SNR of 15 dB,

2x2 MIMO is 2x10-4,

One receive antennas 8x10-2

Two receive antennas 7x10-3

It proves the significance of employing more antennas at the transmitter side.

Fig. 12. MIMO over Rayleigh Fading Channel

STBC is proposed by Alamouti, the transmission is organized as orthogonal matrix to reduce the complexity at the receiver side. But two symbols are transmitted in two time slots.

Transmitted signals are orthogonal to each other.

Provides transmit diversity low data rates and good bit error rate by STBC.

Has two transmit antennas which are fed after encoding of signals at the transmitter end.

Input data is first modulated and then encoded through STBC encoder, which uses specified encoding matrix, such as G2 for two

transmit and two receive antenna STBC.

In this system, we used BPSK and QPSK over Rayleigh fading and AWGN noise added at the receiver.

At the receiver, received symbols are decoded using Maximum likelihood detection.

Space-Time Block Codes (STBC) - Simulation # 5

**Background, System Models, Simulations**

Receive Diversity

Multiple Input Multiple Output MIMO

Space Time Block Code- STBC

MIMO system model block diagram considered in this project is shown in above where two transmit and two receive are used .

Different modulation schemes over Rayleigh fading with AWGN then fed to equalizer.

The received signal is a combination of faded signal, AWGN noise and interference

In this simulation, I tested higher order modulation schemes over MIMO system. I used BPSK, QPSK, 16-PSK and 16-QAM. We can say that data rates can be increased by using higher order modulation schemes in MIMO.

STBC simulations - 2

MIMO simulation

Increasing number of antennas at the transmitter side surely improves the system’s reliability and error rate.

For example, at SNR of 15 dB,

2x2 MIMO is 2x10-4,

One receive antennas 8x10-2

Two receive antennas 7x10-3

It proves the significance of employing more antennas at the transmitter side.

Fig. 12. MIMO over Rayleigh Fading Channel

STBC with more Transmit and one Receive Antenna - Simulation # 6

STBC simulations - 3

MIMO simulation

Increasing number of antennas at the transmitter side surely improves the system’s reliability and error rate.

For example, at SNR of 15 dB,

2x2 MIMO is 2x10-4,

One receive antennas 8x10-2

Two receive antennas 7x10-3

It proves the significance of employing more antennas at the transmitter side.

Fig. 12. MIMO over Rayleigh Fading Channel

STBC with more Transmit and two Receive Antennas - Simulation # 7

In this figure we see the output results of STBC system with two transmit and two receive antenna is simulated.

We have also simulated STBC with two transmit and one receive antenna. We also simulated single tx and single rx, receiver diversity with two receive and receive diversity with four receive, we simulated MIMO 2x2.

We compared STBC with other simulation results and we clearly see that STBC 2x2 provides very good results as compared to others.

In this simulation, we extended the work of two transmit antennas to three and four transmit antennas with one receive antenna.

We clearly see that increasing number of transmit antennas improves BER.

But when we increase tx antennas to four, the improvement is not significant, because it increases the complexity and so we could not exploit diversity with four or more tx antennas.

We have similar observations in this simulation, where we simulated two, three, four tx antennas system with two receive antennas.

I investigated

receive diversity

and performed the simulations of receive diversity system with 2, 3, and 4 receive antennas. I also compared my simulation results with analytical results and found that my simulations are correct.

I investigated

MIMO

systems [4] and simulated MIMO using Monte Carlo simulations.

I implemented

equalization techniques in MIMO

system and simulated zero-forcing (ZF), minimum-mean sequare error (MMSE), successive interference cancellation (SIC) and maximum likelihood (ML) using Monte Carlo simulations for 2x2 MIMO system, from Gupta et. al. published in 2012 [5]. In this part, I used BPSK modulation in 2x2 MIMO over Rayleigh fading channel.

I then extended the above contribution and employed

different modulation techniques

such as QPSK, 16-PSK, and 16-QAM.

I further expand my horizon and investigate

transmit diversity techniques

such as space-time block code

(STBC).

I simulated STBC with two transmit one receive and two transmit two receive antennas, proposed by Alamouti [6]. My simulation results exactly match with the published results.

I investigated more than two transmit antenna STBC systems, proposed by Tarokh et al. [7]. I simulated STBC system with three and four transmit antennas and my simulation results are in close agreement with the published ones.

My thirst of exploration does not end and I investigated

precoding technique in STBC

system.

Finally, I implemented

antenna selection technique in STBC

system.

Precoding Technique in STBC - System Model

Antenna Selection Technique in STBC System

In this system model, we analyzed precoding technique in STBC.

Precoding matrix is estimated based on the channel state information at the receiver.

In this simulation, we used precoding matrix proposed by Hochwald et. al.

This precoding matrix is obtained through DFT weight matrix and diagonal angle matrix and updated in each iteration based on CSI at receiver and then precoding matrix is feedback to the transmitter to be used in next iteration.

Precoding Technique in STBC - Simulation # 8

Here, we analyzed precoding technique in STBC (2x1) system, this figure show the simulation results with and without precoding technique.

We can clearly see that precoding technique exploits STBC system and provides good BER compared to without precoding technique.

We analyzed antenna selection technique in STBC system.

Transmitter selects best two antennas out of four based on the channel coefficients for transmission.

We assumed Fading coefficients are available at the receiver, we also assumed that transmitter knows the fading channel coefficients through the feedback channel from the receiver.

The feedback channel is assumed ideal and has no delay.

Antenna Selection Technique in STBC System simulation # 9

We considered STBC 2x1 system and used four antennas at the transmitter side, but transmitter selects only two antennas out of four based on the channel coefficients feedback.

As we clearly see the improved BER using antenna selection and compared to standard STBC 2x1, we found very good results.

A comprehensive investigation with the help of simulations about multiple antenna techniques is documented in this project.

Receiver diversity technique is presented with simulations and simulation results are validated by analytical results.

Multiple antenna systems such as VBLAST and STBC are explained and their simulations are presented.

Equalization techniques are implemented in VBLAST system.

Moreover, STBC with more than two transmit antennas is also investigated and its simulation results are presented.

Furthermore, precoding technique as well as antenna selection technique is employed in STBC system. I

In this project, all simulations have been successfully implemented using Monte Carlo simulations.

All simulation results are found in close agreement with the analytical and published results.

**Conclusion**