This paper addresses the robust linear filter design issues for non-regenerative multiple input multiple output （MIMO） relay systems with imperfect channel state information （CSI） in both or partial hops. By considering statistical Kronecker channel model involving channel mean and antenna correlation, the robust linear processing schemes in imperfect CSI scenario for both hops are first derived based on mean squared error （MSE） criterion. In addition to this, the result is also extended to two practical scenarios, i.e. imperfect CSI for relay link with perfect CSI for access link and imperfect CSI for access link with perfect CSI for relay link. Simulation results show that the proposed scheme is capable of mitigating the performance degradation caused by the imperfect CSI.
Distributed multipoint systems （DMS） are important and timely for the move to future broadband wireless communication systems. Traditional studies on DMS have mainly focused on the issues with the spatial division multiple access such as precoding techniques, which only consider a narrowband case. This paper addresses the downlink radio resource management of the orthogonal frequency division multiple access DMS （OFDMA-DMS）, including power allocation between users or subcarriers, and distributed antenna selection. Signal models with incoherent and coherent transmitters are built. To maximize the system throughput, for the incoherent transmitter case, a strategy based on the iterative water-filling power allocation is proposed to approach the optimality. As for the coherent case, where coherent additions of the signal could occur at the users, the problem is transformed into an integer programming which is solvable. Numerical results show that the gain from the coherent transmitter is promising. And to achieve a near-optimal solution, only part of the DA ports will be used, which have better channel conditions.
Multiple input multiple output （MIMO） relaying techniques can greatly improve the spectral efficiency and extend network coverage for future wireless systems. This article investigates a multiuser MIMO relay channel, where a base station （BS） with multiple antennas communicates with multiple mobile stations （MS） via a relay station （RS） with multiple antennas. The RS applies linear processing to the received signal and then forwards the processed signal. The dual channel conditions between MIMO relay multiple access channel （MAC） and broadcast channel （BC） are first developed for single-relay scenario with white Gaussian noise. Then the MAC-BC duality for MIMO relay systems is established by proving that the capacity region of MIMO relay MAC is equal to that of dual MIMO relay BC under the same total network transmit power constraint. In addition, the duality is also extended to multi-relay scenario with arbitrary noise. Finally, several simple general numerical examples are provided to better illustrate the effectiveness of the MIMO relay MAC-BC duality.
The increasing demand for interactive mobile multimedia service is causing the integration of 3rd generation （3G） cellular systems and wireless broadcast systems. The key challenge is to support data dissemination with low response time, request drop rate, and the unfairness of request drop. This article proposes a novel scheduling algorithm called DAG （on-demand scheduling utilizing analytic hierarchy process （AHP） and grey relational analysis （GRA））, which takes multiple factors--waiting time, number of active requests, deadline--into consideration, and models the data scheduling process as a multiple factors＇ decision-making and best option-selecting process. The proposed approach comprises two parts. The first part applies AHP to decide the relative weights of multiple decision factors according to user requests, while the second adopts GRA to rank the data item alternatives through the similarity between each option and the ideal option. Simulation results are presented to demonstrate that DAG performs well in the multiple criterions mentioned above.
