EXIT Chart Based Joint Code-Rate and Spreading-Factor Optimisation of Single-Carrier Interleave Division Multiple Access

Abstract—In this paper, we consider the joint code-rate and spreading-factor optimisation of turbo-style iterative joint detection and decoding assisted single-carrier interleave division multiple access (SC-IDMA) systems using different-rate convolutional codes and Extrinsic Information Transfer (EXIT) charts, when communicating over Additive White Gaussian Noise (AWGN) channels. More explicitly, we study the extrinsic information exchange between two serial concatenated components and maximise the number of users supported by the SC-IDMA system under the constraint of a fixed bandwidth expansion factor, while maintaining a predefined Bit Error Ratio (BER) versus Eb/N0 performance. We found that an optimum coderate and spreading-factor combination can be found for the SC-IDMA system at low Eb/N0 values, where maintaining a low BER inevitably requires the employment of channel coding. By contrast, at high Eb/N0 the system performs best, when no channel coding is used, i.e. DS-spreading is the only means of bandwidth expansion

Joint Source-Channel Coding over a Fading Multiple Access Channel with Partial Channel State Information

In this paper we address the problem of transmission of correlated sources over a fast fading multiple access channel (MAC) with partial channel state information available at both the encoders and the decoder. We provide sufficient conditions for transmission with given distortions. Next these conditions are specialized to a Gaussian MAC (GMAC). We provide the optimal power allocation strategy and compare the strategy with various levels of channel state information. Keywords: Fading MAC, Power allocation, Partial channel state information, Correlated sources.Comment: 7 Pages, 3 figures. To Appear in IEEE GLOBECOM, 200

Dispensing with channel estimation: differentially modulated cooperative wireless communications

As a benefit of bypassing the potentially excessive complexity and yet inaccurate channel estimation, differentially encoded modulation in conjunction with low-complexity noncoherent detection constitutes a viable candidate for user-cooperative systems, where estimating all the links by the relays is unrealistic. In order to stimulate further research on differentially modulated cooperative systems, a number of fundamental challenges encountered in their practical implementations are addressed, including the time-variant-channel-induced performance erosion, flexible cooperative protocol designs, resource allocation as well as its high-spectral-efficiency transceiver design. Our investigations demonstrate the quantitative benefits of cooperative wireless networks both from a pure capacity perspective as well as from a practical system design perspective

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems