In this thesis, we discuss multi-user detectors for synchronous and asynchronous DS-CDMA system. In synchronous case, we investigates the application of linear reinforcement learning stochastic approximation to the synchronous CDMA radio channels in the presence of multiple access interference (MAI) and additive Gaussian noise. However, the ODFD receiver requires the knowledge of the receiver energies. In order to overcome this problem, we apply well-known LSA algorithm to estimate all the user¡¦s energies. Numerical simulation shows that the performance of the ODFD-LSA is the same of origined ODFD with known user¡¦s energies. In asynchronous case, we propose a blind adaptive approach to asynchronous DS-CDMA over multipath fading channels, termed GSCMCMA Approach. The GSCMCMA Approach use modified CMA algorithm in GSC structure with multipath constrained matrix. The CMA algorithm can not converge to unity When using constrained matrix in GSC structure. So we proposed modified CMA (MCMA) algorithm in GSC structure which can overcome such problem. In computer simulation, we will compare performance with existing MCMV and MMCMV detectors.

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Use of multiple antennas at both ends of a communication link, known as multiple-input multiple-output (MIMO), increases the reliability and/or capacity of that link. Orthogonal frequency division multiplexing (OFDM) is an effective technique for high data rate transmission over frequency selective channels. At this time MIMO-OFDM has been proposed for many emerging standards and seems to be a promising solution for future high data rate wireless communications. In the first part of this thesis, a novel sub-optimum detection method for spatially multiplexed multicarrier code division multiplexing (SM-MC-CDM) transmission is proposed. It is shown that compared to the spatially multiplexed OFDM (SM-OFDM), the frequency domain spreading in SM-MC-CDM systems results in an additional diversity gain. To take advantage of diversity and multiplexing while mitigating the interference, a low complexity efficient detector employing unified successive interference cancellation (U-SIC) is designed. Analytical results for the performance and capacity of zero-forcing (ZF) U-SIC are provided. Further performance improvement is achieved by adopting an iterative subcarrier reconstruction-detection algorithm in conjunction with the U-SIC. The results demonstrate significant performance improvement over other existing methods of comparable complexity. Performance of turbo-coded SM-MC-CDM transmission is also investigated. In the next part of the thesis, multiuser MIMO downlink is considered. Efficient transmission schemes based on zero-forcing (ZF) linear receiver processing, eigenmode transmission and partial channel state information are proposed. The proposed schemes utilize a handshaking procedure between the BS and the users to select (schedule) a subset of users and determine the precoding matrix at the base station (BS). The advantage of the proposed limited feedback schemes lies in their relatively low complexity scheduling algorithms and high sum rate throughput, even for a small pool of users. For large user pools and when the number of antennas at each user terminal is at least equal to the number of antennas at the BS, we show that the proposed scheme is asymptotically optimal in the sense that it achieves the same sum rate as the optimum scheme as the number of users approaches infinity. Next, net throughput is used as a benchmark to compare several MIMO-OFDM downlink transmission schemes with complete CSIT and also with limited feedback. Considering limited feedback per chunk user scheduling for MIMO-OFDM downlink, it is shown that there exists a chunk size which maximizes the average net throughput. It is shown that the net throughput maximizing chunk size depends on the number of users in the system and the communication channel's characteristics. Finally, future directions for possible research are given.

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In this thesis, we evaluate the performance of multi-user detectors over an uplink using AWGN, Rayleigh flat fading single-input single-output (SISO) and multiple-input multiple-output (MIMO) channel models. First, we review the performance of three multiuser receivers; the decorrelator, the MMSE receiver and the multistage parallel interference cancellation receiver in an AWGN and Rayleigh flat fading SISO channel. Next, the V-BLAST algorithm is reviewed and the error propagation of this algorithm is investigated. Then, the V-BLAST algorithm is combined with multiuser receivers to achieve high channel capacity while sharing the spectral resources over a MIMO channel. A bias reduction technique is considered for multistage parallel interference cancellation receiver on both SISO and MIMO channel. Finally, the effect of channel estimation error and timing delay estimation error is evaluated for MIMO systems with multiple users. / Master of Science

The well-known code division multiple access (CDMA) decorrelating detector (DD) and minimum mean-square error (MMSE) detector use a bank of correlators, followed by the inverse of the matrix operation to eliminate the multiple access interference (MAI). However, the operation for the inverse of the matrix involves a great deal of computation, especially when the users¡¦ number is large. Therefore, in this thesis, we propose some recursive methods, the least-mean-square (LMS) algorithm and the recursive least-squares (RLS) algorithm, to detect users¡¦ signals adaptively. We make use of the analogy between a traditional Winner filter and the decorrelating detector to construct adaptive implementation schemes of the decorrelating detector and MMSE detector, called decorrelating transversal filter and MMSE transversal filter, respectively. We applied both LMS algorithm and RLS algorithm to the decorrelating transversal filter and MMSE transversal filter, just as the ways to apply the LMS algorithm and RLS algorithm to the Winner filters. With the proposed schemes, we can greatly reduce the computational complexity of a CDMA multi-user detector while maintaining an acceptable performance.

The Development of cost-effective and economically viable telecommunications solutions for rural underdeveloped areas has been a key problem to Africa and South Africa. Selecting an appropriate telecommunications technology and an appropriate network topology that could provide both voice and data communication solutions for these areas would be a major advantage for both the community and industries in these areas. Success lies in our ability to adapt selected technologies and implement it with a viable and affordable telecommunication solution. This paper proposes an appropriate telecommunications technology utilization of a cost effective network that can provide wide bandwidth for voice and data telecommunications solutions that are essential for the education, business and private multi-user needs for the Soshanguve and Ga- Rankuwa areas, North-West of Pretoria..

User/relay selection is a simple technique that achieves spatial diversity in multiuser networks. However, for user/relay selection algorithms to make a selection decision, channel state information (CSI) from all cooperating users/relays is usually required at a central node. This requirement poses two important challenges. Firstly, CSI acquisition generates a great deal of feedback overhead (air-time) that could result in significant transmission delays. Secondly, the fed-back channel information is usually corrupted by additive noise. This could lead to transmission outages if the central node selects the set of cooperating relays based on inaccurate feedback information. Motivated by the aforementioned challenges, we propose a limited feedback user/relay selection scheme that is based on the theory of compressed sensing. Firstly, we introduce a limited feedback relay selection algorithm for a multicast relay network. The proposed algorithm exploits the theory of compressive sensing to first obtain the identity of the “strong” relays with limited feedback air-time. Following that, the CSI of the selected relays is estimated using minimum mean square error estimation without any additional feedback. To minimize the effect of noise on the fed-back CSI, we introduce a back-off strategy that optimally backs-off on the noisy received CSI. In the second part of the thesis, we propose a feedback reduction scheme for full-duplex relay-aided multiuser networks. The proposed scheme permits the base station (BS) to obtain channel state information (CSI) from a subset of strong users under substantially reduced feedback overhead. More specifically, we cast the problem of user identification and CSI estimation as a block sparse signal recovery problem in compressive sensing (CS). Using existing CS block recovery algorithms, we first obtain the identity of the strong users and then estimate their CSI using the best linear unbiased estimator (BLUE). Moreover, we derive the error covariance matrix of the post-detection noise to be used in the back-off strategy. In addition to this, we provide exact closed form expressions for the average maximum equivalent SNR at the destination user. The last part of the thesis treats the problem of user selection in a network MIMO setting. We propose a distributed user selection strategy that is based on a well known technique called semi-orthogonal user selection when the zero-forcing beamforming (ZFBF) is adopted. Usually this technique requires perfect channel state information at the transmitter (CSIT) which might not be available or need large feedback overhead. Instead, we propose a distributed user selection technique where no communication between base stations is needed. In order to reduce the feedback overhead, each user set a timer that is inversely proportional to his channel quality indicator (CQI). This technique will allow only the user with the highest CQI to feedback provided that the transmission time is shorter than the difference between his timer and the second strongest user timer, otherwise a collision will occur. In the case of collision, we propose another feedback strategy that is based on the theory of compressive sensing, where collision is allowed and each user encode its feedback using Gaussian codewords and feedback the combination at the same time with other users. We prove that the problem can be formulated as a block sparse recovery problem and that this approach is agnostic on the transmission time, thus it could be a good alternative to the timer approach when collision is dominant. Simulation results show that the proposed CS-based selection algorithms yield a rate performance that is close to the ones achieved when perfect CSI is available while consuming a small amount of feedback.

An analytically tractable model for Gaussian multiuser channels with fading is studied, and the capacity region of this model is found to be a good approximation of the capacity region of the original Gaussian network. This work extends the existing body of work on deterministic models for Gaussian multiuser channels to include the physical phenomenon of fading. In particular, it generalizes these results to a unicast, multiple node network setting with fading. / text