Earticle

Traditional distributed power control algorithms in cognitive radio networks are based on the assumption of perfect channel estimation which can lead to performance degradation in practical system. Cognitive radio sensor network (CRSN) has emerged as a promising solution to address the spectrum-related challenges of wireless sensor networks (WSN). Moreover, cognitive radio (CR) gives us a possibility to maximize the utilization efficiency of limited spectrum resources. However, because the wireless devices coexist in the same radio environment, there are harmful channel conflicts among users. First at all, this paper presents a practical model of cumulative interferences from the entire cognitive radio based industrial wireless sensor networks (CR-IWSN). Then, based on the interference model, we propose an intelligent power control scheme to address the communication requirements. The simulation results show that the proposed distributed power control scheme can efficiently increase the energy efficiencies as well as the throughput of the CR-IWSN compared with the existing protocols.

셀룰러 네트워크를 운용하는데 드는 에너지의 대부분은 기지국에 의해서 소비되므로 에너지 효율적인 셀룰러 네트워크를 위하여 기지국의 송신 전력을 줄이는 것이 필요하다. 본 논문에서는 셀룰러 네트워크의 에너지 효율을 향상시키기 위한 목적으로 플로킹(flocking) 모델에 기반한 분산 송신전력제어 알고리즘을 제안한다. 새 무리에서 각각의 새가 자신의 속도를 인접한 이웃 새들의 평균 속도로 맞춰 날아가는 것과 같이, 제안 방안에서는 각 셀의 단말의전송률이 인접 셀의 같은 채널을 사용하는 단말의 평균 전송률과 같도록 서빙 기지국의 송신 전력을 제어한다. 모의실험 결과 제안한 분산 송신전력제어 알고리즘은 플로킹 모델과 같은 수렴 속성을 가지며, 셀 간 간섭이 증가함에 따라 낮은 아웃티지 확률을 유지하면서도 기지국의 전력 소모를 효과적으로 줄일 수 있음을 보여준다. 이를 통하여 제안 방안은 기지국 수가 20개 이상일 때 셀룰러 네트워크의 에너지 효율을 기존 방식 대비 두 배 이상 향상시킨다.

Most of the energy used to operate a cellular network is consumed by a base station (BS), and reducing the transmission power of a BS is required for energy-efficient cellular networks. In this paper, a distributed transmit power control (TPC) algorithm is proposed based on the flocking model to improve the energy efficiency of a cellular network. Just as each bird in a flock attempts to match its velocity with the average velocity of adjacent birds, in the proposed algorithm each mobile station (MS) in a cell matches its rate with the average rate of the co-channel MSs in adjacent cells by controlling the transmit power of its serving BS. Simulation results show that the proposed TPC algorithm follows the same convergence properties as the flocking model and also effectively reduces the power consumption at the BSs while maintaining a low outage probability as the inter-cell interference increases. Consequently, it significantly improves the energy efficiency of a cellular network.