Iterative turbo beamforming for OFDM based hybrid terrestrial-satellite mobile system

In the context of orthogonal frequency division multiplexing (OFDM)-based systems, pilot-based beamforming (BF) exhibits a high degree of sensitivity to the pilot sub-carriers. Increasing the number of reference pilots significantly improves BF performance as well as system performance. However, this increase comes at the cost of data throughput, which inevitably shrinks due to transmission of additional pilots. Hence an approach where reference signals available to the BF process can be increased without transmitting additional pilots can exhibit superior system performance without compromising throughput. Thus, the authors present a novel three-stage iterative turbo beamforming (ITBF) algorithm for an OFDM-based hybrid terrestrial-satellite mobile system, which utilises both pilots and data to perform interference mitigation. Data sub-carriers are utilised as virtual reference signals in the BF process. Results show that when compared to non-iterative conventional BF, the proposed ITBF exhibits bit error rate gain of up to 2.5 dB with only one iteration

Wireless Cellular Networks

When aiming for achieving high spectral efficiency in wireless cellular networks, cochannel interference (CCI) becomes the dominant performancelimiting factor. This article provides a survey of CCI mitigation techniques, where both active and passive approaches are discussed in the context of both open- and closed-loop designs.More explicitly, we considered both the family of flexible frequency-reuse (FFR)-aided and dynamic channel allocation (DCA)-aided interference avoidance techniques as well as smart antenna-aided interference mitigation techniques, which may be classified as active approach

An Iterative Receiver for OFDM With Sparsity-Based Parametric Channel Estimation

In this work we design a receiver that iteratively passes soft information between the channel estimation and data decoding stages. The receiver incorporates sparsity-based parametric channel estimation. State-of-the-art sparsity-based iterative receivers simplify the channel estimation problem by restricting the multipath delays to a grid. Our receiver does not impose such a restriction. As a result it does not suffer from the leakage effect, which destroys sparsity. Communication at near capacity rates in high SNR requires a large modulation order. Due to the close proximity of modulation symbols in such systems, the grid-based approximation is of insufficient accuracy. We show numerically that a state-of-the-art iterative receiver with grid-based sparse channel estimation exhibits a bit-error-rate floor in the high SNR regime. On the contrary, our receiver performs very close to the perfect channel state information bound for all SNR values. We also demonstrate both theoretically and numerically that parametric channel estimation works well in dense channels, i.e., when the number of multipath components is large and each individual component cannot be resolved.Comment: Major revision, accepted for IEEE Transactions on Signal Processin