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 pro...
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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） *** 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.
在时变多用户MIMO-OFDM系统中,所有子载波整体预编码方案的性能优于单个子载波单独预编码方案。然而前者的复杂度是基站发射天线数J与子载波总数N乘积的函数,显著高于后者,特别NJ>1000时,复杂度极高。为了解决这个问题,我们提出了一种基于最大化信泄噪比的复杂度可调的分组子载波GS-Max-SLNR(Grouped-Subcarrier Maximum Signal-toLeakage-and-Noise Ratio)预编码方案。此外,我们推导了组间干扰公式,该公式在给定多普勒频移和信噪比的条件下,可以根据需要选取合适的分组数。理论建模和仿真表明,通过选取合适的分组数目,提出的GS-Max-SLNR能够实现复杂度和性能的良好折中。
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