High transmission spectral efficiency

Chapter 1

1 Introduction

High transmission spectral efficiency, data rate, reliability are necessary for high speed wireless communication. Wireless channels suffer a lot from attenuation due to multipath fading due to channel. These physical limitations of the wireless medium create a technical challenge for reliable and fast wireless communication. Due to need of high speed wireless demand for technologies delivering higher link reliability and capacity than achieved by current systems. We have to use techniques that improve spectral efficiency and overcome channel impairments e.g. interference and signal interference. These techniques have made a great contribution to the reliability and efficiency of wireless communication.

Multiple input Multiple Output (MIMO) systems are form of spatial diversity in which we use multiple antennas at transmitter as well as receiver. In multipath channel, deploying multiple antenna techniques at both transmitter and receiver achieves high data rate without increasing the total transmission power or bandwidth. This technology is used to reduce errors and optimize data rates. MIMO is a great technique to achieve high bandwidth and system performance. MIMO systems offer significant diversity and advantages over traditional wireless communication systems by exploiting both transmission and receiver diversity using space time coding technique and many other.

1.1 Objective

The main goal 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 acting as transmitter and receiver in a communication system, while a third as DSP emulated the channel as shown in fig. 1.1 all the processing has to be done with the DSP boards. The transmitter and receiver boards are separately controlled by Matlab interface programs . 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

1.2 Background

(MIMO) systems take advantage of spatial diversity obtained through the spatially separated antennas in a dense multipath environment. When channel knowledge is available at the receiver, the capacity has been shown to grow linearly with the number of antennas. Most MIMO detection schemes are based on perfect channel knowledge being available at the receiver.

Due to advancement in technologies it is now possible to implement such kind of improvements given by higher 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

These are the components for building and testing our communication system; the group has used all of them during the whole developing process because the trials were the most time- consuming phases.

  • Four standard PC in Lab A315;
  • Three DSP boards, Texas Instrument DSK320C6713;
  • Cables;
  • Oscilloscope;
  • Function Generator;
  • Two DSP Line-Adapters.

1.4.2 Software

Regarding the software, the red group made common choices in order to develop the communication system:

  • Matlab used to simulate algorithms and to design the GUI interface;
  • 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 us; a lot of ideas were taken from previous works in the selected area. Here follows a rough list of the materials. May the reader wants to find more details about the papers actually used, he can read more in the References

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

Chapter 2


2.1 Introduction to MIMO

Multiple Input Multiple Output (MIMO) is the application of multiple antennas at both transmitter and receiver side, aiming to improve communication performance. It is one of several forms of smart antenna. MIMO has emerged as the leading technology for increasing the spectral efficiency of communication systems. Many MIMO techniques are now widely know. First we will discuss the techniques that lead to development of mimo.


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 troublesome and frustrating problem in receiving radio signals is variations in signal strength, most commonly known as fading. There are several conditions that can produce fading however in ionospheric circuits fading occurs mainly due to multipath propagation. Multipath fading occurs in any environment where there is multipath propagation and there is some movement of elements within the radio communications system. This may include the radio transmitter or receiver position, or in the elements that give rise to the reflections. The multipath fading can often be relatively deep, i.e. the signals fade completely away, whereas at other times the fading may not cause the signal to fall below a useable strength.

Multipath fading may also cause distortion to the radio signal. As the various paths that can be taken by the signals vary in length, the signal transmitted at a particular instance will arrive at the receiver over a spread of times. This can cause problems with phase distortion and intersymbol interference when data transmissions are made. As a result, it may be necessary to secure features within the radio communications system that enables the effects of these problems to be minimized.

2.2.1 Types of fading

  1. Fast fading
  2. In multipath fading impulse response of channel changes rapidly within a symbol duration. The amplitude and phase change imposed by the channel varies considerably over the period of use. 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.

  3. slow fading
  4. This type of fading occur 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.

  5. flat fading
  6. This type of fading effects 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

  7. selective fading
  8. This type of fading effects differently for different frequency components so we can 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.

  9. Rayleigh Fading
  10. 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.

  11. Rician Fading
  12. 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 powerful communication receiver technique that provides wireless link improvement at a relatively very low cost. Diversity techniques are used in wireless communications Systems primarily to improve performance over a fading radio channel. In such a system, the receiver is provided with multiple copies of the same information signal which are transmitted over two or more real or virtual communication channels. The system consisting of N different channels, can thus achieve a diversity order equal to N. Without diversity techniques attenuation makes it difficult for the receiver to determine the transmitted signal. Diversity technique provides less attenuated replicas of transmitter at the receiver. Spatial diversity technique increases the gain and consequently increases gain diversity thus increasing reliability of the wireless link

Types of Diversity

There are three major types of diversity space diversity polarization diversity frequency and time diversity that are explained below in detail.

2.3.1 Space Diversity

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

  1. Selection diversity
  2. 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.

  3. Scanning or feedback diversity
  4. In this type we have to select signals that are above the minimum threshold value we have set. With this type of diversity theMsignals are scanned in a sequence until the signal is found that exceeds a given threshold. This signal is the chosen signal until it falls below the threshold and we have to star the scanning process gain. This method is easy beacause feedback is quite simple to implement.

  5. Maximal ratio combining
  6. Selecting 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.

  7. Equal gain combining
  8. 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

Thos 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

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

Aspacetime codeis a method employed to improve reliability of datatransmissioninwireless communication systemsusing multiple transmit antennas. STC rely on transmitting multiple,redundantcopies of the data stream to thereceiverin the hope that at least some of them may survive the physicalbetween transmission and reception in a good enough state to allow reliable decoding at the receiver. When the signal design extends over both space via the multiple antennas and time via multiple symbol times it is typically referred to as a space-time code. Most space-time codes discussed in this section, are designed where the channel is constant over a block of T symbol times, and the channel is assumed unknown at the transmitter Under this model the channel input and output become matrices, with dimensions corresponding to space antennas and time.

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 antennae. Space time block codes were designed to achieve this maximum diversity order for the given number of transmit and receive antennas which are subject to the constraint of having a simple linear decoding algorithm. This has made space-time block codes a very poplar scheme and most widely used. Space time block codes STBCs are an alternative space-time code that can also extract excellent diversity and coding gain with linear receiver complexity. Interests in STBCs were initiated by the Alamouti code described in which obtains full diversity order with linear receiver processing for a two antenna transmit system. This scheme was generalized to STBCs that achieve full diversity order with an arbitrary number of transmit antennas. However, while these codes achieve full diversity order, they do not provide coding gain, and thus have inferior performance to STTCs, which achieve both full diversity gain as well as coding gain. STBCs can be seen as a mapping of Q symbols (complex or real) onto a codeword C of size nt T. Those code words are encoded in the sense that no error correcting code is contained in the STBC. Theoretically, STBCs may take several forms, but practically, linear STBCs are by far the most widely used. The idea behind linear STBCs is to spread information symbols in space and time in order to improve either the diversity gain, or the spatial multiplexing rate, or both the diversity gain and the spatial multiplexing rate. By packing more symbols into a given codeword, i.e. by increasing Q, the data rate is increased. In the following, we first present a general framework of linear STBCs together with some general properties, before particularizing this framework to some important subclasses of STBCs.

3.1 Space Time Trellis Coding

Spacetime trellis codesare a type ofspacetime codeused inmultiple antennawireless communications. This scheme transmits multiple,redundantcopies of acode distributed over time and a number ofantennas. These multiple copies of the data are used by the receiver to attempt to reconstruct the actual transmitted data. For an STC to be used, there must necessarily be multipletransmitantennas, but only a singlereceiveantennas is required nevertheless multiple receive antennas are often used since the performance of the system is improved by so doing. In contrast tospacetime block codes(STBCs), they are able to provide both coding gain and diversity gain and have a betterbit-error rateperformance. However, being based ontrellis codes, they are more complex than STBCs to encode and decode. In STTC when we keep the number of transmit antennas fixed, the decoding complexity increases exponentially with transmission rate.

3.2 The Alamouti Space Time Coding

Alamouti scheme with two transmit antennas and two receiver antennas can achieve transmission diversity for the downlink, as shown in fig 2.1. It can achieve the same diversity order as receiver diversity, which can be achieved by Maximum Ratio Combining using a transmit antenna and four receive antennas, but with 3dB performance loss due to the power allocation for two transmission 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.

2.3 STBC with CSIT

Assuming the downlink using MPSK modulations, aiming to simplify the user terminal with two antennas, encoding is done with CSIT at the base station and decoding at user end is desired to be completed with CSI, as shown in the figure 2.2

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

3.3 Tarokh Space Time Coding Scheme

Tarokh applied orthogonal designs to achieve diversity using space time block codes.First we wil discuss orthogonal designs that were developed by Hawritz Radon.

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.

For 44 designs

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.

For i=1N, and decide in favour of among all constellation symbols s

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