114 research outputs found

    Simulated annealing based multiuser detection for synchronous SDMA system

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    In this treatise, a novel Simulated Annealing (SA) based Multi-User Detection (MUD) is proposed in synchronous Space Division Multiple Access (SDMA) system. SA MUD modifies experiential Cooling Schedule (CS) of traditional SA algorithm according to its use in MUD. Moreover, in order to ensure sufficient diversity acquired in the whole Markov chain and to prevent from being trapped at local optima, Uniform Mutation (UM) based trial vector generation scheme is brought forward. In addition, the optimal solution recording scheme is also invoked in case of being lost during cooling process. Simulation results illustrate that in comparison with Genetic Algorithm (GA) MUD in the same simulation conditions, without turbo processing and soft-information, SA MUD proposed in this paper performs better, approaching the performance of Maximum Likelihood (ML) MUD and imposes lower complexity

    Improved decoder metrics for DS-CDMA in practical 3G systems

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    While 4G mobile networks have been deployed since 2008. In several of the more developed markets, 3G mobile networks are still growing with 3G having the largest market -in terms of number of users- by 2019. 3G networks are based on Direct- Sequence Code-Division Multiple-Access (DS-CDMA). DS-CDMA suffers mainly from the Multiple Access Interference (MAI) and fading. Multi-User Detectors (MUDs) and Error Correcting Codes (ECCs) are the primary means to combat MAI and fading. MUDs, however, suffer from high complexity, including most of sub-optimal algorithms. Hence, most commercial implementations still use conventional single-user matched filter detectors. This thesis proposes improved channel decoder metrics for enhancing uplink performance in 3G systems. The basic idea is to model the MAI as conditionally Gaussian, instead of Gaussian, conditioned on the users’ cross-correlations and/or the channel fading coefficients. The conditioning implies a time-dependent variance that provides enhanced reliability estimates at the decoder inputs. We derive improved log-likelihood ratios (ILLRs) for bit- and chip- asynchronous multipath fading channels. We show that while utilizing knowledge of all users’ code sequences for the ILLR metric is very complicated in chip-asynchronous reception, a simplified expression relying on truncated group delay results in negligible performance loss. We also derive an expression for the error probability using the standard Gaussian approximation for asynchronous channels for the widely used raised cosine pule shaping. Our study framework considers practical 3G systems, with finite interleaving, correlated multipath fading channel models, practical pulse shaping, and system parameters obtained from CDMA2000 standard. Our results show that for the fully practical cellular uplink channel, the performance advantage due to ILLRs is significant and approaches 3 dB

    Near-capacity MIMOs using iterative detection

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    In this thesis, Multiple-Input Multiple-Output (MIMO) techniques designed for transmission over narrowband Rayleigh fading channels are investigated. Specifically, in order to providea diversity gain while eliminating the complexity of MIMO channel estimation, a Differential Space-Time Spreading (DSTS) scheme is designed that employs non-coherent detection. Additionally, in order to maximise the coding advantage of DSTS, it is combined with Sphere Packing (SP) modulation. The related capacity analysis shows that the DSTS-SP scheme exhibits a higher capacity than its counterpart dispensing with SP. Furthermore, in order to attain additional performance gains, the DSTS system invokes iterative detection, where the outer code is constituted by a Recursive Systematic Convolutional (RSC) code, while the inner code is a SP demapper in one of the prototype systems investigated, while the other scheme employs a Unity Rate Code (URC) as its inner code in order to eliminate the error floor exhibited by the system dispensing with URC. EXIT charts are used to analyse the convergence behaviour of the iteratively detected schemes and a novel technique is proposed for computing the maximum achievable rate of the system based on EXIT charts. Explicitly, the four-antenna-aided DSTSSP system employing no URC precoding attains a coding gain of 12 dB at a BER of 10-5 and performs within 1.82 dB from the maximum achievable rate limit. By contrast, the URC aidedprecoded system operates within 0.92 dB from the same limit.On the other hand, in order to maximise the DSTS system’s throughput, an adaptive DSTSSP scheme is proposed that exploits the advantages of differential encoding, iterative decoding as well as SP modulation. The achievable integrity and bit rate enhancements of the system are determined by the following factors: the specific MIMO configuration used for transmitting data from the four antennas, the spreading factor used and the RSC encoder’s code rate.Additionally, multi-functional MIMO techniques are designed to provide diversity gains, multiplexing gains and beamforming gains by combining the benefits of space-time codes, VBLASTand beamforming. First, a system employing Nt=4 transmit Antenna Arrays (AA) with LAA number of elements per AA and Nr=4 receive antennas is proposed, which is referred to as a Layered Steered Space-Time Code (LSSTC). Three iteratively detected near-capacity LSSTC-SP receiver structures are proposed, which differ in the number of inner iterations employed between the inner decoder and the SP demapper as well as in the choice of the outer code, which is either an RSC code or an Irregular Convolutional Code (IrCC). The three systems are capable of operating within 0.9, 0.4 and 0.6 dB from the maximum achievable rate limit of the system. A comparison between the three iteratively-detected schemes reveals that a carefully designed two-stage iterative detection scheme is capable of operating sufficiently close to capacity at a lower complexity, when compared to a three-stage system employing a RSC or a two-stage system using an IrCC as an outer code. On the other hand, in order to allow the LSSTC scheme to employ less receive antennas than transmit antennas, while still accommodating multiple users, a Layered Steered Space-Time Spreading (LSSTS) scheme is proposed that combines the benefits of space-time spreading, V-BLAST, beamforming and generalised MC DS-CDMA. Furthermore, iteratively detected LSSTS schemes are presented and an LLR post-processing technique is proposed in order to improve the attainable performance of the iteratively detected LSSTS system.Finally, a distributed turbo coding scheme is proposed that combines the benefits of turbo coding and cooperative communication, where iterative detection is employed by exchanging extrinsic information between the decoders of different single-antenna-aided users. Specifically, the effect of the errors induced in the first phase of cooperation, where the two users exchange their data, on the performance of the uplink in studied, while considering different fading channel characteristics

    Genetically Enhanced TTCM Assisted MMSE Multi-user Detection for SDMA-OFDM

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    Space Division Multiple Access (SDMA) aided Orthogonal Frequency Division Multiplexing (OFDM) systems assisted by efficient Multi-User Detection (MUD) techniques have recently attracted intensive research interests. The Maximum Likelihood Detection (MLD) arrangement was found to attain the best performance, although this was achieved at the cost of a computational complexity, which increases exponentially both with the number of users and with the number of bits per symbol transmitted by higher-order modulation schemes. By contrast, the Minimum Mean-Square Error (MMSE) SDMA-MUD exhibits a lower complexity at the cost of a performance loss. Forward Error Correction (FEC) schemes such as Turbo Trellis Coded Modulation (TTCM) may be efficiently amalgamated with SDMA-OFDM systems for the sake of improving the achievable performance. Genetic Algorithm (GA) based multiuser detection techniques have been shown to provide a good performance in MUD-aided Code Division Multiple Access (CDMA) systems. In this contribution a GA-aided MMSE MUD is proposed for employment in a TTCM-assisted SDMA-OFDM system, which is capable of achieving a similar performance to that attained by its MLD-aided counterpart at a significantly lower complexity, especially at high user loads

    Iterative Joint Channel Estimation and Multi-User Detection for Multiple-Antenna Aided OFDM Systems

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    Multiple-Input-Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to Single-Input-Single-Output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell LAyered Space-Time architecture (BLAST) or Space Division Multiple Access (SDMA) multi-user MIMO OFDM systems, none of the known channel estimation techniques allows the number of users to be higher than the number of receiver antennas, which is often referred to as a “rank-deficient” scenario, owing to the constraint imposed by the rank of the MIMO channel matrix. Against this background, in this paper we propose a new Genetic Algorithm (GA) assisted iterative Joint Channel Estimation and Multi-User Detection (GA-JCEMUD) approach for multi-user MIMO SDMA-OFDM systems, which provides an effective solution to the multi-user MIMO channel estimation problem in the above-mentioned rank-deficient scenario. Furthermore, the GAs invoked in the data detection literature can only provide a hard-decision output for the Forward Error Correction (FEC) or channel decoder, which inevitably limits the system’s achievable performance. By contrast, our proposed GA is capable of providing “soft” outputs and hence it becomes capable of achieving an improved performance with the aid of FEC decoders. A range of simulation results are provided to demonstrate the superiority of the proposed scheme. Index Terms—Channel estimation, genetic algorithm, multiple-input-multiple-output, multi-user detection, orthogonal frequency division multiplexing, space division multiple access
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