On the Gaussian Many-to-One X Channel

In this paper, the Gaussian many-to-one X channel, which is a special case of general multiuser X channel, is studied. In the Gaussian many-to-one X channel, communication links exist between all transmitters and one of the receivers, along with a communication link between each transmitter and its corresponding receiver. As per the X channel assumption, transmission of messages is allowed on all the links of the channel. This communication model is different from the corresponding many-to-one interference channel (IC). Transmission strategies which involve using Gaussian codebooks and treating interference from a subset of transmitters as noise are formulated for the above channel. Sum-rate is used as the criterion of optimality for evaluating the strategies. Initially, a $3 \times 3$ many-to-one X channel is considered and three transmission strategies are analyzed. The first two strategies are shown to achieve sum-rate capacity under certain channel conditions. For the third strategy, a sum-rate outer bound is derived and the gap between the outer bound and the achieved rate is characterized. These results are later extended to the $K \times K$ case. Next, a region in which the many-to-one X channel can be operated as a many-to-one IC without loss of sum-rate is identified. Further, in the above region, it is shown that using Gaussian codebooks and treating interference as noise achieves a rate point that is within $K/2 -1$ bits from the sum-rate capacity. Subsequently, some implications of the above results to the Gaussian many-to-one IC are discussed. Transmission strategies for the many-to-one IC are formulated and channel conditions under which the strategies achieve sum-rate capacity are obtained. A region where the sum-rate capacity can be characterized to within $K/2-1$ bits is also identified.Comment: Submitted to IEEE Transactions on Information Theory; Revised and updated version of the original draf

An information theoretic approach to non-centralized multi- user communication systems

Ph.DDOCTOR OF PHILOSOPH

A cross-layer cooperation strategy for cellular networks.

PhDCooperation is seen as a means to improve the signal in OFDMA wireless networks by overcoming the inter-cell interference. Such co-operation can be deployed in both the physical layer and the MAC layer. In this thesis, a cross-layer cooperation strategy is considered. Firstly, in the physical layer, a cooperative coding scheme with private information sharing is proposed based on dirty paper coding; this is analyzed in a scenario with two transmitters and two receivers. To implement the cooperation, a rate limited link is deployed at the transmitters’ side in order to share the information. A new achievable rate region is established in both strong interference regime and weak interference regime. Secondly, in the MAC layer, a graph-based dynamic coordinated clustering scheme is proposed. An interference weighted graph is constructed to assist dynamic coordinated clustering for inter-cell interference mitigation and to improve the cell-edge user performance. Only 2 bits are allowed for the signalling exchange between transmitters and this reduces the overhead of the approach. The system throughput and cell-edge throughput with different user distributions are used to evaluate the performance. Thirdly, a transmit antenna selection algorithm is presented to optimize system performance with the constraint of fairness. A graph is generated by using the channel condition between the transmit antennas and Mobile Stations. Based on the graph, a heuristic algorithm is proposed to choose the transmit antenna for each user in order to improve the system performance and guarantee the user fairness. Finally, combining the cooperative coding scheme and cooperative clustering scheme, a cross-layer cooperation scheme is presented. In the physical layer, the cooperation coding scheme mitigates the interference and increases the transmission rate; in the MAC layer, the cooperative clustering scheme provides efficient cooperative transmission. Simulation results show that the proposed scheme can effectively increase both the system throughput and cell-edge throughput