Cooperative Transmission for Downlink Distributed Antenna in Time Division Duplex System

Multi-user distributed antenna system (MU-DAS) systems play the essential role in improving throughput performance in wireless communications. This improvement can be achieved by exploiting the spatial domain and without the need of additional power and bandwidth. In this thesis, three main issues which are of importance to the data rate transmission have been investigated.

Firstly, user clustering in MU-DAS downlink systems has been considered, where this technique can be effciently used to reduce the complexity and cost caused by radio frequency chains, associated with antennas while keeping most of the diversity advantages of the system. The proposed user clustering algorithm which can select an optimal set of antennas for transmission. The capacity achieved by the proposed algorithm is almost same as the capacity of the optimum search method, with much lower complexity.

Secondly, interference alignment in MU-DAS downlink systems has been studied. The inter-cluster interference is uncoordinated and limits the system performance. The inter-cluster interference should be eliminated or minimized carefully. The interference alignment is proposed to consolidate the strong inter-cluster interference into smaller dimensions of signal space at each user and use the remaining dimensions to transmit the desired signals without any interference. The performance of single cluster is better than the proposed algorithm due to the absence of intercluster interference in the single cluster. The numerical shows that the proposed algorithm is more suitable in multi-cell DAS environment due to the presence of inter-cell interference.

Finally, the impact of different user mobility on TDD downlink MUDAS has been studied. The downlink data transmission in time division duplex (TDD) systems is optimized according to the channel state information (CSI) which is obtained at the uplink time slot. However, the actual channel at downlink time slot may be different from the estimated channel due to channel variation in mobility environment. Based on mobility state information (MSI), an autocorrelation based feedback interval adjustment technique is proposed. The proposed technique adjusts the CSI update interval and mitigates the performance degradation imposed by the user mobility and the transmission delay. Cooperative clusters are formed to maximize sum rate. In order to reduce the computational complexity, a channel gain based antenna selection and signal-to-interference plus noise ratio (SINR) based user clustering are developed. A downlink ergodic capacity is derived in single user clustering. The derived analytical expressions of the downlink ergodic capacity are verified by system simulations. Numerical results show that the proposed scheme can improved sum rate over the non cooperative system and no MSI knowledge. The proposed technique has good performance for a wide range of user speed and suitable for future wireless communications systems.