Abstract-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 transmitterreceiver 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.

In this contribution we explore a family of novel Optimized Hierarchy Reduced Search Algorithm (OHRSA)-aided space-time processing methods, which may be regarded as an advanced extension of the Complex Sphere Decoder (CSD) method. The algorithm proposed extends the potential application range of the CSD method, as well as reduces the associated computational complexity.

We carry out a comprehensive analysis of a range of wireless network efficiency considerations. Firstly, we explore the properties and the implications of the power-versus bandwidthefficiency criteria. Secondly, we perform a detailed top-down analysis of a typical commercial wireless network, which emphasizes the inherent differences between the aforementioned two efficiency metrics, while demonstrating that the appropriate choice of the network optimization criterion can have a profound effect on the overall network performance. Finally, we address the issue of resource management and its impact on the definition of the overall system efficiency.

Abstract-In this paper we propose a novel Space Division Multiplexing (SDM) detection method. The proposed technique constitutes a list search method and may be regarded as an advanced extension of the Sphere Decoder (SD). Our method may be employed in the so-called over-loaded scenario, where the number of transmit antenna elements exceeds that of the receive antenna elements. Furthermore, it is suitable for highthroughput, non-constant modulus modulation schemes, such as 16 and 64-QAM. We introduce a series of optimization rules which facilitate a substantial reduction in computational complexity. More specifically, we demonstrate that the method proposed, which we refer to as the Soft-output OPtimized HIErarchy (SOPHIE)-aided SDM detector exhibits the near-optimum performance of Log-MAP SDM detector in all considered scenarios. The associated computational complexity, which we control using two complexity-control parameters, is substantially lower than that imposed by all previously proposed methods.

Abstract-In this letter we characterize the substantial difference between two channel estimation approaches, namely the sample-spaced (SS) and the fractionally-spaced (FS) channel impulse response (CIR) estimators. The achievable performance of decision-directed channel estimation (DDCE) methods employing both the SS-and the FS-CIR estimators is analyzed in the context of an OFDM system. The performance of the two estimation methods is compared and it is shown that the DDCE scheme employing the Projection Approximation Subspace Tracking (PAST)-aided FS-CIR estimator outperforms its SS-CIR estimator-based counterpart.Index Terms-Multiuser OFDM, decision directed channel estimation, impulse response estimation SDMA.