Space Time Processing And Resource Allocation In MIMO System

With the development of economy, advancement of science and technologyand increasing demand for information transmission, higher transmission rate andbetter service quality are required in communication network. In order to realizethe full potential of 'any where, any time personal communication', space-timesignal processing is now regarded as a core element of future system deployment.In multiuser system, smart antenna system yields a capacity enhancement or rangeextension over conventional fixed beam antenna installations by focusing theirbeam patterns towards the desired user. Despite these benefits offered by singlearray, 3rd and 4rd generation wireless networks could still fall short of marketexpectations in terms of available capacity for 'e-commerce'and 'multi-media'based services. As a result, the smart antenna concept is extended by employingmulti-element arrays at both ends of the communication, which is called MIMOsystem. Important improvement in throughput without additional bandwidth andpower can be achieved when multiple antennas are applied at both the transmitterand receiver side, especially in a rich scattering environment. So, MIMOarchitecture has been applied in wireless cell network, wireless LAN and ADSL.MIMO techniques can basically be split into two groups: space time coding(STC) and space division multiplexing (SDM). STC increases the performance ofthe communication system by coding over the different transmitter branches,whereas SDM achieves a higher throughput by transmitting independent datastreams on the different transmitter branches simultaneously and at the samecarrier frequency. Currently, adaptive MIMO resource allocation techniques havebeen in an active research. In wireless channel, adaptive MIMO space timeprocessing technique which combines space-time processing and adaptive bits,power allocation can suppress multipath fading and improve system throughput.Now, wide researches about space-time techniques in single user MIMOsystem have been conducted. However, adaptive MIMO space-time processingtechnique and adaptive resource allocation technique in multiuser MIMO systemare in a primary stage. This paper consists of seven chapters. The first three chapters mainlyintroduce the existent research fruits, the fourth, fifth and sixth chapters areauthor's main contribution and the last chapter is conclusion. The first chapter is introduction, which presents the research background,principle, realization and application of MIMO system. In the second chapter, we show an overview on the capacity of MIMO systemin fixed channel and fading channel. In fading channel, channel capacity has aclose relation with channel statistical characteristic and channel informationacquired by transmitter and receiver. In flat fading channel, channel capacitieswith channel state information at the receiver (CSIR) and at the transmitter (CSIT)and with CSIR and channel distribution at the transmitter (CDIT) are discussedrespectively. In frequency-selective fading channel, first, we converts thefrequency-selective channel into frequency flat spatial subchannels with differentcarrier, then introduce the capacity with CSIT, CDIT and CSIR. In the third chapter, receiver algorithms in MIMO flat andfrequency-selective fading channel are introduced, which include the zero forcing(ZF), MMSE, ML and successive interference cancellation algorithm. We present the group space-time processing and power allocation techniquesin MIMO-CDMA system in multipath fading channel in chapter four. This schemeimproves performance of system without increasing the complexity. In chapter five, we research adaptive resource allocation technique in MIMOspatial multiplexing system, which include BLAST, antenna selectin algorithmand adaptive bit interleaved coded modulation technique in fast fading channel. In chapter six, we research adaptive multiuser diversity technique in flatfading channel and frequency-selective fading channel. In flat fading channel,channel is decoupled into parallel sub-channels with random beamforming in thetransmitter and linear processing in the receiver. With each user's effectivesub-channel SNRs, the transmitter then schedules the transmission to oneparticular selected with proportional fair scheduling algorithm. Finally, adaptivemodulation is applied to each sub-channel of the selected user based on the BERconstraint. In frequency-selective fading channel, sub-carrier random beamformerand QR linear receiver decouple the space-frequency channels into sub-channels.QR receiver can suppress the interference between sub-channels, which make thesystem performance approach that of eigen-beamforming system even the usernumber is small. Simulation results show that multiuser diversity with antennaallocation can achieve better performance than that of eigen-beamforming system.Finally, adaptive subchannel coded modulation is adopted to improve systemperformance further. The sixth chapter is conclusion, which generalizes the main work of thispaper and challenge faced in commercialization. The originality of this paper is as fellows: 1. Apply group space-time coding to CDMA system, which improve system performance without increasing complexity. 2. Propose adaptive bit interleaving coded modulation and correspongding decoding algorithm in fast fading channel, which improve the reliability of communication over multipath fading channel. 3. Propose variable rate multiuser diversity algorithm in flat fading and frequency-selective fading channel and realize resourse allocation in multiuser MIMO system. In flat fading channel, adaptive multiuser diversity can maximum system throughput; in frequency selective fading channel, adaptive multiuser diversity with OFDM can optimize system throughput and BER performance. This paper has some illumination means to the two questions as follows: 1. Best offset algorithm between maximizing diversity gain and maximizing system capacity.