Equalization and Decoding for Multiple-Input Multiple-Output Wireless Channels

<p/> <p>We consider multiple-input, multiple-output (MIMO) wireless communication systems that employ multiple transmit and receive antennas to increase the data rate and achieve diversity in fading multipath channels. We begin by focusing on an uncoded system and define optimal and suboptimal receiver structures for this system in Rayleigh fading with and without intersymbol interference. Next, we consider coded MIMO systems. We view the coded system as a serially concatenated convolutional code (SCCC) in which the code and the multipath channel take on the roles of constituent codes. This enables us to analyze the performance using the same performance analysis tools as developed previously for SCCCs. Finally, we present an iterative ("turbo") MAP-based equalization and decoding scheme and evaluate its performance when applied to a system with <inline-formula><graphic file="1687-6180-2002-986492-i1.gif"/></inline-formula> transmit antennas and <inline-formula><graphic file="1687-6180-2002-986492-i2.gif"/></inline-formula> receive antennas. We show that by performing recursive precoding prior to transmission, significant interleaving gains can be realized compared to systems without precoding.</p

Antenna arrays for the downlink of FDD wideband CDMA communication systems

The main subject of this thesis is the investigation of antenna array techniques for improving the performance of the downlink of wideband code division multiple access (WCDMA) mobile communication systems. These communication systems operate in frequency division duplex (FDD) mode and the antenna arrays are employed in the base station. A number of diversity, beamforming and hybrid techniques are analysed and their bit error ratio (BER) versus signalto- noise ratio (SNR) performance is calculated as a function of the eigenvalues of the mean channel correlation matrix, where this is applicable. Also, their BER versus SNR performance is evaluated by means of computer simulations in various channel environments and using different numbers of transmit antenna elements in the base station. The simulation results of the techniques, along with other characteristics, are compared to examine the relationship among their performance in various channel environments and investigate which technique is most suitable for each channel environment. Next, a combination of the channel correlation matrix eigenvalue decomposition and space-time processing is proposed as a possible open loop approach to the downlink data signal transmission. It decomposes the channel into M components in the form of eigenvectors (M is the number of transmit antennas in the base station), and attempts to minimise the transmit power that is needed to achieve a target BER at the mobile receiver by employing the optimum number of these eigenvectors. The lower transmit power and the directional transmission by means of eigenvectors are expected to lower interference levels to non-desired users (especially to those users who are not physically close to the direction(s) of transmission). Theoretical and simulation results suggest that this approach performs better than other presented open loop techniques, while the performance gain depends on M and the channel environment. In simulations it is usually assumed that the base and mobile station have access to perfect estimates of all needed parameters (e.g. channel coecients). However, in practical systems they make use of pilot and/or feedback signals to obtain estimates of these parameters, which result in noisy estimates. The impact of the noisy estimates on the performance of various techniques is investigated by computer simulations, and the results suggest that there is typically some performance loss. The loss depends on the parameter that is estimated from pilot signals, and may be a function of M, SNR and/or the channel environment. In certain beamforming techniques the base station operates the transmit antenna array in an open loop fashion by estimating the downlink weight vector from the directional information of the uplink channel. Nevertheless, in FDD systems this results in performance loss due to the separation between the uplink and downlink carrier frequencies (`FDD gap'). This loss is quantified and the results show that it is a function of M and the FDD gap. Also, a very simple technique for compensating this loss is proposed, and results obtained after its application suggest that it eliminates most of the loss. Comparison of the proposed technique with an existing compensation technique suggests that, even though the latter is more complex than the former, it yields very little additional improvement