Resource Allocation In Multi-cell MIMO Wireless Networks

MIMO technology will become an important wireless communicationtechnology in future because it could significantly increase channel capacity byseveral orders of magnitude without based on additional frequency bands. However,in actual communication systems downlink, multi-cell MIMO technology is facedwith interference from users and inter-cellular. With the fact that traditional diversitytechnology and launch strategy can only improve link level’s performance andreliability, and user’s QoS in cellular is still not improved effectively. It has importantpractical significance to research interference avoidance technology on resourceallocation based on multi-cell MIMO wireless networks.With full knowledge of multi-cell MIMO networks resource allocation problems’Research status both domestic and foreign, and based on Practical application.According to MIMO multi-cellular interference is limited, Information processing andinteraction based on cooperation the precoding and decoding technology is toocomplex, it is difficult to implement in the reality system. This paper made thefollowing research and innovation work:(1) The thesis proposed the problem that how to achive the network utilitymaximization through multi-cell cooperation using beamforming and power controlwhen there is power constraint about the tramsmitting antenna in downlink.Compared with the traditional problem model, the innovation reflect in two hands, onthe one hand, the model considered the power constraint of antenna combination. Onthe other hand, the model consider multi-users communication simultaneously on thesame frenquency bands under the same cell.(2) Under the average allocation of user’s power, using optimization theory,from the perspective of game theory, introducing price mechanism，the problem canbe converted to some sub-problems of beamforming and power allocation. Accordingto the different variables search method, this paper puts forward two algorithms basedon multi-cellular collaboration:(a) without antenna power combination constraint,Optimization problems only have one constraint item (neglect non-zero constraint),this paper proposes a cooperative algorithm based on the dichotomy variable searchmethod, and proves the convergence.(b) with antenna power combination restraint,Optimization problems have more than one constraint item, this paper proposes a cooperative algorithm based on the ellipsoid variable search method, and proves theconvergence. Both cooperative algorithms have lower complexity, can be realizedeasily and have real feasibility. In simulation section, we compare the performance ofcooperative and non-cooprative algorithms, the result shows that with a good transmitSNR, the performance of average algorithm based on cooperation is much better thanthat of non-cooperation.(3) In circumstances that the sum of antenna transmit power in base station islimited, according to primal decomposition, we decompose the optimization probleminto master and sub-problems. We update the power constraint variable in masterproblem with fast projection method and solve the sub-problems with an algorithmsimilar to cooperative algorithm. We propose an adaptive resource allocationalgorithm based on fast projection method, analysis the realization of adaptivealgorithm and adaptive allocation mechanism in detail. This algorithm can adaptivelyimplements beamforming and power control. Finally, we do the simulation ofcooperative algorithms, non-cooperative algorithm and adaptive algorithm for manytimes. The results show that although adaptive algorithm increases complexity on thealgorithm and system, it improves the network utility.