MIMO system using DSP kits

Chapter 1

1 Introduction

For high transmission spectral efficiency, data rate and reliability are essential for fast wireless communication. Wireless channels undergo a lot from attenuation due to multipath fading in the channel. These physical restrictions of the wireless medium create a technical test for reliable and fast wireless communication. The need of high data rates, demand for technologies delivering higher link performance (capacity and reliability) achieved by current systems. Techniques improving spectral efficiency and overcoming channel impairments (signal fading and interference) have led to the development of wireless communications.

Multiple input Multiple Output (MIMO) systems are type of spatial diversity. In multipath channel, deploying multiple antenna techniques at both transmitter and receiver achieves high data rate reliability and capacity without increasing the total transmission power or bandwidth. MIMO is a vast technique to attain high bandwidth and system performance. MIMO systems offer considerable diversity and benefits over conventional wireless communication systems by exploiting both transmission and receiver diversity using space time coding technique and many other developed on basis of MIMO technology.

1.1 Objective

The main aim of our group was to implement a MIMO system using DSP kits. The system should work reliably on multipath environment. The system should be able to transmit information from one PC to another through DSP kits.

1.2 Problem Specification

We will be using two computers with two DSP boards that will act as receiver and transmitter in a communication scheme, while a third as DSP emulated the channel as shown in fig. 1.1 all the processing has to be completed with the DSP boards. The transmitter and receiver are separately controlled by Matlab interface programs and trough simulink. The interfaces are useful to choose the setup of the communication system at transmitter side and to show the detected signal and constellation plots at receiver side. We have to perform simulations and then implement them on hardware.

1.2 Background

(MIMO) systems take gain of spatial diversity that is obtained through the spatially alienated antennas in a dense multipath environment where we will experience reflection , refraction scattering and fading. When channel information is available at the receiver it is seen that the capacity has been improved linearly with the quantity of antennas (both transmitter and receiver). Most MIMO detection schemes are based on ideal channel knowledge that should be available at the receiver.

Due to advancement of technologies it is now achievable to execute such sort of improvements given by advanced diversity order.

1.3 Overview

After a brief introduction to the problem the paper is dealing with, resources allocation will be explained in section 1.4; afterwards, Chapter 2 will be about MIMO systems and their main features, while Chapter 3 will explain all the theory that stands behind the communication system and that was used in order to achieve the goal of the project. Chapter 4 will carry out the preliminary results coming from the simulation that were done using a Matlab environment, thus previously to the actual implementation; Chapter 5 will give some ideas of the real DSP programming, Chapter 6 will be dealing with the graphical user interface (GUI) necessary to control all the setup of the system by an external user; finally in Chapter 7, comparisons between real performances and simulations will be presented and some possible future work and conclusions will be discussed.

1.4 Resources

1.4.1 Hardware

Following are the components for our communication system we have used all of them during the development of oyr project.

  • Four standard PC(s) in Lab
  • Three DSP boards DSK320C6713
  • Oscilloscope
  • Function Generator
  • Cables

1.4.2 Software

We have used following softwares in our project

  • Matlab used to simulate algorithms
  • Code Composer Studio set up to work together with the provided boards in order to implement the theoretical algorithm
  • Visual Studio 6.0 for testing and debugging C programs


The foundations of the whole system were not designed by we have taken a lot of ideas from previous works in the selected area. We have mentioned that list in the references. Readers can read all those details if they are interested.

  • Books related to Telecommunications;
  • Papers listed on the References;
  • Projects from the previous years.
  • Websites listed in the references.

Chapter 2


2.1 Introduction

Multiple Input Multiple Output systems which are called as (MIMO systems) are the application where there are multiple antennas at transmitter as well as receiver side due to which we can improve communication performance. MIMO has emerged as the primary technology for increasing the spectral efficiency and capacity of communication systems. Many MIMO techniques are developed. First we will discuss the techniques that lead to development of MIMO systems.


These are classical and easiest systems in which there is one transmitting and one receiving antenna. SISO systems are less complex than mimo systems but they suffer a lot of fading and This is one of the severe issues encountering wireless technologies and we cannot achieve desired system performance.


These systems have one transmitting and several receiving antennas. It is often referred to as receive diversity. This means one transmitting antennas at the base station and more than one receiving antenna at mobile radiotelephone.


These are the systems having several transmitting antennas and one receive antennas. This is also termed as receive diversity. This means there are several transmitting antennas at the base station and one transmitting antenna at mobile radiotelephone


The systems that use multiple antennas at transmitter and receiver are known as mimo systems. In MIMO systems there is mapping of a data stream to multiple parallel data streams and de-mapping into a single data stream. of MIMO systems is to provide spatial and time diversity by multiple antennas and space-time coding. . Latest 3G and 4G services are designed in order to take advantage of this new concept of using spatial diversity to improve the performance of mobile devices. In such a way, it becomes more and more important to move steps forward towards new techniques, which will allow data rates never seen before. In order to assess the benefits of the MIMO technology, realistic models of the wireless propagation channel are required. In general, the radio propagation is subject to multi-path, i.e. the signal from the transmitter propagates along different paths to the (mobile) receiver. . MIMO technology has widespread applications in digital television (DTV), wireless local area networks (WLANs), metropolitan area networks (MANs), and mobile communications.

2.2 Fading

The most difficult and annoying dilemma in receiving radio signals is variation in signal strength that known as fading. It is a particularity of wireless signals that they suffer from channel impairments across time space and frequency. Fading occurs when ever there is multipath. This may include the radio transmitter or receiver location. Some level of fading is acceptable but when fade is very deep we cannot distinguish our signal at receiver end.

So multipath fading causes distortion to the radio signals and when signals vary in length so the signal transmitted at some instance will arrive at the receiver over a spread of times which will lead to presence of ISI and phase distortion. So for reliable and fast communication these impairments should be reduced. So MIMO technology was mainly developed to not only overcome but exploit this channel impairment. Following are types of fading.

2.2.1 Types of fading

1 Fast fading

In multipath fading impulse response of channel varies quickly in a symbol duration. Amplitude and phase change that are forced by the channel changes significantly over the phase. In a fast fading channel coherence time is less than symbol period and it has high Doppler spread. Its channel variations are faster than baseband signal variations.

2 slow fading

This type of fading occurs due to reflection, refraction and scattering due to buildings, gaps in buildings and it occurs at longer distances than fast fading. In a slow-fading channel coherence time is greater than symbol period and it has low Doppler spread.Its channel variations are slower than baseband signal variations.

3 flat fading

This type of fading affects all frequencies in some proportion so we cannot reduce it by changing the frequency. It occurs when bandwidth of signal is less than bandwidth of channel and delay spread is less than symbol period

4 selective fading

This type of fading effects in a different way for every frequency components so we can easily reduce it by changing frequency. It occurs when bandwidth of signal is greater than bandwidth of channel and delay spread is greater than symbol period.

5 Rayleigh Fading

Rayleigh fading occurs when magnitude of a signal that has passed through a communication channel varies randomly according to Rayleigh distribution. Rayleigh fading is applicable when there is no propagation along LOS between the transmitter and receiver.

6 Rician Fading

Rician fading occurs when the signal arrives at the receiver by two different paths and at least one of the paths typically LOS is much stronger than the others. It occurs when magnitude of signal varies according to Rician distribution.

2.3 Diversity

Diversity is a communication technique that gives wireless link improvement at a relatively very low expenditure. Diversity techniques are used in wireless communications Systems mainly for improvement of performance over a fading channel. In this system the receiver is provided with several copies of the same information signal which we are transmitting over two or more communication channels. The system consisting of N different channels that can thus achieve a diversity order of N. Without diversity techniques attenuation makes it hard for the receiver to determine the transmitted signal. Diversity practice provides us less attenuated replicas of transmitter at the receiver and thus increases the gain and as a result increases gain diversity and increases reliability of the wireless link .

Types of Diversity

There are three main types of diversity that are space diversity polarization diversity frequency and time diversity explained following.

2.3.1 Space Diversity

Space diversity is also called antenna diversity and it is most frequently used in MIMO systems. In this technique all the antennas are spatially separated. Signals received from spatially separated antennas are chosen according to following types.

1. Selection diversity

Selection diversity is also called antenna diversity it is especially effective at minimizing multipath fading. This is because multiple antennas offer a receiver several observations of the same signal. Each antenna will experience different environment so if one antenna is experiencing a deep fade, it is likely that another receives good signal so we have a good robust link.

2. Scanning or feedback diversity

In this type we have to select signals that are higher than the minimum threshold value we have set. With this type of diversity theNsignals are scanned in a series until the signal is set up that exceeds a given threshold. This signal is the chosen signal until it falls below the threshold and we have to start the scanning process gain. This technique is easy because feedback is rather simple to implement.

3. Maximal ratio combining

In maximal ratio combining we select all signals according to their SNR and then add them to get an acceptable SNR. The individual signals must be co phased before they are summed. Maximal-ratio combining can produce acceptable average SNR even when none of the individual SNR of the signal is acceptable. It uses each of the signals which is than co phased and weighted in a manner such that the largest possible SNR is available.

4. Equal gain combining

In equal gain combining equalization is performed at the receiver by dividing the received symbolby known phase that are unity weights. This is the method of transmission and reception used to minimize the effect of selective fading of the components of a radio signal it is usually accomplished through the use of vertically and horizontally polarized receiving antennas.

2.3.2 Polarization Diversity

Those type of diversity is usually accomplished through the use of separate vertically and horizontally polarized receiving antennas.The antennas use the multipath propagation characteristics to receive separate uncorrelated signals.We can use circular linear elliptical polarization according to situation to get benefits.This is very effective in reducing multipath delays.

2.3.3 Frequency Diversity

In this type of diversity we have to transmit different carrier frequencies. Using this technique we can overcome the effects of multipath fading since the wavelength for different frequencies result in different and uncorrelated fading characteristics.So there is a chance we can have a good signal out of all.

2.3.4Time Diversity

Time Diversityis used in digital communication systems to combat error burstsdue to time-varying channel conditions. These error bursts can be caused byfadingin combination with a moving receiver, transmitter or obstacle, orco-channel interferencefrom radio transmitters. Time diversity implies that the same data is transmitted multiple times, or a redundanterror codeis added.

2.4 Rayleigh Channel

The central limit theorem states that under certain conditions, sum of all independent random variables approaches very closely to normal distribution. When there are large numbers of paths, By applyingCentral Limit Theorem, we can model each path circularly symmetric complex Gaussian random variablewith time as the variable. This type of model is calledRayleigh fading channel model

As you can see real and imaginary parts are zero mean independent and identically distributed random variables. For acircularly symmetric complex random variable.

The magnitudewhich has a probability density is called aRayleigh random variable.This model, calledRayleigh fading channel model, is reasonable for an environment where there is large number of reflectors. It is an excellent approximation to measure fading amplitude statistics for mobile fading channels in NLOS situations.

Chapter 3


The demand of mobile communication systems with high data rates has increased a lot in recent years. New methods are required in order to satisfy this demand of communications, as we have to exploit the Limited resources such as power and bandwidth as efficient as possible. MIMO systems with multiple antenna elements at both link ends are an efficient solution for wireless communications systems as they provide very high data rates by exploiting the spatial domain under the limited bandwidth and transmission power MIMO systems require very less transmission power and energy than SISO systems.

Direct application of multi-antenna techniques is impractical due to limited physical size of which typically can only support a single antenna but fortunately if we allow individual single-antenna nodes to cooperate on information transmission or reception and a co operative MIMO system can be constructed such that energy efficient MIMO schemes can be applied. Energy-efficient communication techniques typically focus on minimizing the transmission energy only, which is reasonable in long range applications where the transmission energy is dominant in the total energy consumption. However in short range applications where the circuit energy consumption is comparable to the transmission energy, different approaches need to be taken to minimize the total energy consumption.

In this chapter we will discuss different MIMO techniques in detail.

3.1 Space Time Coding

Aspace time codeis a technique used to improve reliability of datatransmissioninwireless communication systemsin which we use multiple transmission antennas. Space Time Coding depends on transmitting several copies of the data to thereceiverin the expectation that at least there will be a signal that will survive the. When the signal extends over both space due to the several antennas and time due to many symbols times it is usually called as space time coding. Mainly space time codes explained in this section are considered where the channel is constant over a block of symbol times and our channel is implicit at the transmitter . In this model the channel input and output are written in form of matrices with dimensions equivalent to space antennas and time.

Let X=[x1,x2,x3xT] represent the Mtt channel input matrix with ith column xi that is equal to the vector channel input over the ith transmission time.

Let Y=[y1,y2,y3yT] represent the Mr T channel output matrix with ith column yi equal to the channel output over the ith transmission time

Let N=[n1,n2,n3nT] denote theMr T noise matrix with ith column ni equal to the receiver noise vector on the ith transmission time. With this matrix representation the input-output relationship over all T blocks becomes

Types of space time coding

3.1 Space Time Block Coding

Space time coding refers to channel coding techniques for transmission with multiple transmissions and receive antenna. Space time block codes were intended to attain maximum diversity order for the specified number of transmit and receive antennas that are issue to the limitation of having a simple linear decoding this has made space-time block codes a much admired scheme and most commonly used. Space time block codes STBCs are a substitute space-time code that can also take out exceptional diversity and coding gain with receiver difficulty. Benefits in STBCs were initiated by help of Alamouti code described in which obtains full diversity order with receiver processing for a two antenna transmit system. As these codes get maximum diversity order they do not give coding gain and thus have inferior performance to STTC that achieve full diversity and coding gain. STBC can be seen as a mapping of I symbols onto a codeword C of size ntT. Those code words are un coded in the way that there have no error correcting mechanism in the STBC. Theoretically STBC may take a number of forms, but practically linear STBC are definitely the most extensively used. The design behind linear STBC is to achieve information symbols within space and time in a way to get better diversity or the spatial multiplexing gain. By adding more symbols into a specified codeword (by increasing I) the data rate is increased. Following are the types of space time block codes.

Linear space-time block codes

A linear code is defined as a set of code words that are linear in the scalar input symbols. for example we can write linear space time codes as shown below. This is an example of linear space time block codes.

Orthogonal space time block codes

Orthogonal space time block codes are a special example of linear codes where codeword _ is intended to be a unitary matrix for example =+.

3.1 Space Time Trellis Coding

Space time trellis coding was proposed before space time block coding. They are based on classical convolution codes. STTCare a category ofspace time codethat are used inMIMOwireless communications where we will transmit several copies of a Code that is separated over time and an amount ofantennas. STTC can provide diversity and coding gain and gives betterBER but they are more complicated than STBC and are difficult to implement. STTC is function of input bits and state of encoder means it depend upon present as well as previous state.

3.2 The Alamouti Space Time Coding

Alamouti scheme is shown in fig 2.1 to attain transmission diversity by means of two transmitter and two receiver antennas. It can attain the similar diversity order as we can achieve with receiver diversity using Maximum Ratio Combining using a transmitter and four receive antennas As alamouti schemes easy encoding and implementation it is preferred.

As a result, it takes part in both Wide-band Code Division Multiple Access (WCDMA) together with Code Division Multiple Access-2000 (CDMA- 2000) standards

Given a code symbol vector consisting of two symbols s0 and s1, where Pt is the total transmit power andis introduced because of power division for two transmit antennas. In Table 2.1 the encoding scheme is shown, symbol s0 is transmitted from antenna 1, while symbol s1 is transmitted from antenna 2 during the first time slot; during second time slot symbols -s1* and s0* are transmitted from antenna 1 and 2, respectively.

As it was shown, Alamouti scheme leads to a very simple encoding and no CSIT required at transmitter, thus it has a large potential to be applied to the uplink of the communication system.

2.3 STBC with CSIT

Considering the downlink using MPSK modulations to simplify the user terminal with two antennas we can encode with CSIT at the base station and decoding at user end is preferred to be completed using CSI in the figure 3.2 below

Given the same code symbol vector and CSIT matrix from formula 2.1with acting as a normalization factor, the encoding method is given below. At the first time slot are transmitted through two transmitter antennas.

At second time slot are transmitted via two transmitter antennas.

3.3 Tarokh Scheme

3.3.1 Orthogonal Designs

Orthogonal design exists only if size of the design n=2,4 or 8. If size is n than design is an orthogonal matrix with in determinates .Consider examples of orthogonal designs for 22 systems.

3.3.2 Coding Scheme

We will focus on providing diversity where denotes complex conjugate of .Value of depends on code sequence ,received signal ,path coefficient and structure of the orthogonal design.

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