This letter focuses on the simplified capacity evaluation for the downlink of a distributed antenna system (DAS) with random antenna layout. Based on system scale-up, we derive a good approximation of the downlink capacity by developing the results from random matrix theory. We also propose an iterative method to calculate the unknown parameters in the approximated expression of the downlink capacity. The approximation is illustrated to be quite accurate and the iterative method is shown to be quite efficient by Monte Carlo simulations.

In this letter, we address the problem of downlink power allocation for the generalized distributed antenna system (DAS) with cooperative clusters. Considering practical applications, we assume that only the large-scale channel state information is available at the transmitter. The power allocation scheme is investigated with the target of ergodic achievable sum rate maximization. Based on some approximations and the Rayleigh Quotient Theory, the simple selective power allocation scheme is derived for the low SNR scenario and the high SNR scenario, respectively. The methods are applicable in practice due to their low complexity.

In this paper, an adaptive expansion strategy (AES) is proposed for multiple-input/multiple-output (MIMO) detection in the presence of circular signals. By exploiting channel properties, the AES classifies MIMO channels into three types: excellent, average and deep fading. To avoid unnecessary branch-searching, the AES adopts single expansion (SE), partial expansion (PE) and full expansion (FE) for excellent channels, average channels and deep fading channels, respectively. In the PE, the non-circularity of signal is exploited, and the widely linear processing is extended from non-circular signals to circular signals by I (or Q) component cancellation. An analytical performance analysis is given to quantify the performance improvement. Simulation results show that the proposed algorithm can achieve quasi-optimal performance with much less complexity (hundreds of flops/symbol are saved) compared with the fixed-complexity sphere decoder (FSD) and the sphere decoder (SD).

In this letter, coordinated power allocation (PA) is investigated for the downlink of a generalized multi-cluster distributed antenna system (DAS). Motivated by practical applications, we assume only the global large-scale channel state information is known at the transmitter. First, an upper bound (UB) for the ergodic sum capacity of the system is derived and used as a simplified optimization target. Then, a coordinated PA scheme is proposed based on Geometric Programming (GP), which is demonstrated to be nearly optimal by Monte Carlo simulations.

The rapid variation of wireless channels and feedback delay make the available channel state information (CSI) outdated in dynamic wireless multi-hop networks, which significantly degrades the accuracy of cross-layer resource allocation. To deal with this problem, a cross-layer resource allocation scheme is proposed for wireless multi-hop networks by taking the outdated CSI into account and basing compensation on the results of channel prediction. The cross-layer resource allocation is formulated as a network utility maximization problem, which jointly considers congestion control, channel allocation, power control, scheduling and routing with the compensated CSI. Based on a dual decomposition approach, the problem is solved in a distributed manner. Simulation results show that the proposed algorithm can reasonably allocate the resources, and significantly improve the throughput and energy efficiency in the network.