研究了长期演进(long term evolution,LTE)网络中考虑机会调度并可提供不同服务质量(QoS)保障的准入控制(CAC)算法的设计.使用基于累积分布函数的调度(cumulative distributed function based scheduling,CS)作为基本调度策略.首先采用机会轮询(opportunistic roundrobin,ORR)计算CS性能下界,并通过仿真验证此计算方法的正确性.然后提出一个CS与ORR相结合的CAC算法COCDQ(CS/ORR based CAC algorithm for different QoS requirements),其可同时保障新接入用户和已存在用户的不同QoS需求.最后通过系统级仿真验证所提算法性能,结果表明联合考虑机会调度与QoS需求,COCDQ算法可有效降低新接入用户阻塞率,提供更好的QoS保障,其代价是仅总吞吐量略有降低.
In order to solve the challenging coverage problem that the long term evolution（ LTE） networks are facing, a coverage optimization scheme by adjusting the antenna tilt angle（ ATA） of evolved Node B（ e NB） is proposed based on the modified particle swarm optimization（ MPSO） algorithm.The number of mobile stations（ MSs） served by e NBs, which is obtained based on the reference signal received power（RSRP） measured from the MS, is used as the metric for coverage optimization, and the coverage problem is optimized by maximizing the number of served MSs. In the MPSO algorithm, a swarm of particles known as the set of ATAs is available; the fitness function is defined as the total number of the served MSs; and the evolution velocity corresponds to the ATAs adjustment scale for each iteration cycle. Simulation results showthat compared with the fixed ATA, the number of served MSs by e NBs is significantly increased by 7. 2%, the quality of the received signal is considerably improved by 20 d Bm, and, particularly, the system throughput is also effectively increased by 55 Mbit / s.
