Research On Key Technologies Of Cooperative MIMO System With Multiple-antenna Terminals

In a wireless communication system, the presence of signal fading arising frommultipath propagation degrades the system performance and severely limits the systemcapacity. Multiple-antenna diversity technology is an effective method that combatsfading. However, it is difficult for many systems to equip a mobile terminal withmultiple-antenna due to size, power or hardware complexity. In this circumstance,cooperative diversity technology was proposed and attracted increasing attention.Cooperative diversity is also called cooperative MIMO in some literatures, it is a newform of spatial diversity, which is a method to allow a single-antenna mobile to shareother mobiles’ antennas and thus achieve transmit diversity. Due to the long distanceamong the terminals, much larger than several times of wavelength, the channels haveless correlation with each other and hence maximize the channel capacity. The use ofmultiple-antenna terminals, however, has been identified as a certain developmenttendency. In wireless networks with multiple-antenna terminals, the problem ofcooperation still exits, cooperative MIMO with multiple-antenna terminals can improvethe system performance further. This dissertation focuses on decode-and-forwardcooperative MIMO with multiple-antenna terminals. Cooperation strategies, powerallocation algorithms and partner selection algorithms have been studied.The cooperation strategies of cooperative MIMO with multiple-antenna terminals arestudied and two adaptive algorithms are proposed. Based on the detailed bit error rateanalysis of decode-and-forward cooperative MIMO, the conditions of cooperation’s biterror rate performance being better than non-cooperation that the instantaneous signal tonoise ratios of different links should satisfied are given. For networks with light trafficand much unoccupied channel resource, adaptive algorithm with minimized bit error ratecan select direct transmission mode or decode-and-forward cooperation mode accordingto the instantaneous signal to noise ratios of different links, minimizes the system biterror rate, the energy consumption and channel resource occupancy are also less thantraditional cooperative diversity. For networks with heavy traffic and little unoccupiedchannel resource, adaptive algorithm with minimized channel resource occupancy givesdirect transmission mode priority on the premise of bit error rate request can be satisfied.In this way, the energy consumption and channel resource occupancy can be decreasedgreatly and the outage probability is lower as well.Power allocation algorithms of cooperative MIMO with multiple-antenna terminals arestudied, an optimal power allocation algorithm based on golden section iterative methodand two simplified algorithms are proposed. Minimizing energy consumption is taken asthe optimization objective in these algorithms, transmission power are allocated dynamically among the source and the relay according to instantaneous signal to noiseratios of different links, minimizing the total transmission power and maximizing theenergy gain on the premise of bit error rate request can be satisfied. The optimal powerallocation algorithm based on golden section iterative method can reduce the interval thatcontains the optimal solution gradually through iterations and thus get the optimalsolution that satisfies some accuracy demand. By setting cooperation thresholds,reducing initial interval or directly using the formula of the optimal power allocationcoefficient approximation, the two simplified algorithms can decrease the computationalcomplexity greatly and get similar energy gain as the optimal power allocation algorithmbased on golden section iterative method.Partner selection methods for cooperative MIMO with multiple-antennaterminals are studied. Three improved worst link first partner selection algorithms areproposed for different scenarios: partner selection algorithm with minimized bit errorrate, partner selection algorithm with equal power allocation and maximized energygain and combined power allocation and partner selection algorithm. According tothe analysis of system bit error rate and energy gain, these three algorithms decreasedcomputational complexity greatly through setting cooperative thresholds and usingestimated energy gains or power allocation factors. Simulation results show thatthese three algorithms can get high performance, and the computational complexitiesare much lower than ordinary worst link first algorithm.