Multiuser Detection and Channel Estimation for Multibeam Satellite Communications

In this paper, iterative multi-user detection techniques for multi-beam communications are presented. The solutions are based on a successive interference cancellation architecture and a channel decoding to treat the co-channel interference. Beams forming and channels coefficients are estimated and updated iteratively. A developed technique of signals combining allows power improvement of the useful received signal; and then reduction of the bit error rates with low signal to noise ratios. The approach is applied to a synchronous multi-beam satellite link under an additive white Gaussian channel. Evaluation of the techniques is done with computer simulations, where a noised and multi-access environment is considered. The simulations results show the good performance of the proposed solutions.Comment: 12 page

Adaptive antennas at the mobile and base stations in an OFDM/TDMA system

In recent years, several smart antenna systems have been proposed and demonstrated at the base station (BS) of wire-less communications systems, and these have shown that significant system performance improvement is possible. In this paper, we consider the use of adaptive antennas at the BS and mobile stations (MS), operating jointly, in combination with orthogonal frequency-division multiplexing. The advantages of the proposed system includes reductions in average error probability and increases in capacity compared to conventional systems. Multiuser access, in space, time, and through subcarriers, is also possible and expressions for the exact joint optimal antenna weights at the BS and MS under cochannel interference conditions for fading channels are derived. To demonstrate the potential of our proposed system, analytical along with Monte Carlo simulation results are provided

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