Research On Energy-efficient Adaptive Resource Allocation In MISO-OFDM Downlink Scenario

With the greenhouse gas emission has been proved to be responsible for the globalwarming and frequently extremely climate, the demand of energy saving comes to becrucial. The latest estimation showed that the ICT consumed2%-10%of total energyconsumption all over the world，and this weight was still growing, so was the unit cost ofthe energy. Under this critical background, both academe and industry show great concernto the system performance on energy efficiency, being the important part of ICT, themobile communication have the same demand. One category of the effective energyoptimization strategies is to improve the energy efficiency of the network elements to letperformance of whole network be improved. In the cellular network system, such effortwas mainly concentrated on the wireless access networks(base stations).For the number ofbase stations is relative high with relative high energy consumption, the energy efficiencyimprovement of base stations will improve the performance of whole network enormously.Corresponding to the situation that while MIMO-OFDM comes to be downlink multiaccess technology by the3GPP-LTE standards but the implementation of MIMO is stilllimited in practical, we mainly focus on the energy-efficient adaptive power allocation inMISO-OFDM downlink scenario.Begin with the analysis of base station energy efficiency, we formulated the energyefficiency model of the single cell multi users MISO-OFDM system. Then combined withthe characteristic of OFDM, we investigate the currently energy-efficient adaptiveresource allocation strategies. In the following parts of our work, we design a resourceallocation strategy that power allocated non-equally among subcarriers, but subcarriersallocated equally among the selected users to deal with the scenario that the number ofusers is great than subcarriers. To deal with the much more practical scenario that thenumber of subcarriers is great than users, we design a resource allocation strategy thatpower allocated equally among subcarriers, but subcarriers allocated non-equally amongthe users. These two allocation strategies could satisfy both the total transmission powerconstraint and user demand for Quality of Service(QoS). Numerical results showed thatboth allocation strategies could effectively meet the demand of QoS and energy efficiency improvement.The allocation strategies we proposed could provide low complexity implementationfor user QoS satisfaction and energy efficiency optimization.