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Adaptive Energy-Efficient Power Allocation in Green Interference Alignment Based Wireless Networks
Interference alignment (IA) is a promising technique for interference management in wireless networks. However, the sum rate may fall short of the theoretical maximum especially at low signal-to-noise ratio (SNR) levels since IA mainly concentrates on mitigating the interference, instead of improving the quality of desired signal. Moreover, most of the previous works focused on improving spectrum efficiency, but the energy efficiency aspect is largely ignored. In this paper, an adaptive energy-efficient IA algorithm is proposed through power allocation and transmission-mode adaptation for green IAbased wireless networks. The power allocation problem for IA is first analyzed, then we propose a power allocation scheme that optimizes the energy efficiency of IA-based wireless networks. When SNR is low, the transmitted power of some users may become zero. Thus the users with low transmitted power are turned into the sleep mode in our scheme to save energy. The transmitted power and transmission mode of the remaining active users are adapted again to further improve the energy efficiency of the network. To guarantee the interests of all the users, fairness among users is also considered in the proposed scheme. Simulation results are presented to show the effectiveness of the proposed algorithm in improving the energy efficiency of IAbased wireless networks
5G green cellular networks considering power allocation schemes
It is important to assess the effect of transmit power allocation schemes on
the energy consumption on random cellular networks. The energy efficiency of 5G
green cellular networks with average and water-filling power allocation schemes
is studied in this paper. Based on the proposed interference and achievable
rate model, an energy efficiency model is proposed for MIMO random cellular
networks. Furthermore, the energy efficiency with average and water-filling
power allocation schemes are presented, respectively. Numerical results
indicate that the maximum limits of energy efficiency are always there for MIMO
random cellular networks with different intensity ratios of mobile stations
(MSs) to base stations (BSs) and channel conditions. Compared with the average
power allocation scheme, the water-filling scheme is shown to improve the
energy efficiency of MIMO random cellular networks when channel state
information (CSI) is attainable for both transmitters and receivers.Comment: 14 pages, 7 figure
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