宏基站和微基站群之间的预测性信道调度算法

doi:10.11959/j.issn.1000-436x.2019217

Abstract

Abstract:

A novel predictive channel scheduling algorithm was proposed for non-real-time traffic transmission between macro-base stations and micro-base stations in 5G ultra-cellular networks.First,based on the stochastic stationary process characteristics of wireless channels between stationary communication agents,a discrete channel state probability space was established for the scheduling process from the perspective of classical probability theory,and the event domain was segmented.Then,the efficient scheduling of multi-user,multi-non-real-time services was realized by probability numerical calculation of each event domain.The theoretical analysis and simulation results show that the algorithm has low computational complexity.Compared with other classical scheduling algorithms,the new algorithm can optimize traffic transmission in a longer time dimension,approximate the maximum signal-to-noise ratio algorithm in throughput performance,and increase system throughput by about 14% under heavy load.At the same time,the new algorithm is accurate.Quantitative computation achieves a self-adaption match between the expected traffic rate and the actual scheduling rate.

Key words: super cellular network, stationary stochastic process, discrete channel state probability space, predictive channel scheduling, quantitative scheduling

CLC Number:

TP393

Yinghai XIE,Ruohe YAO,Bin WU. Predictive channel scheduling algorithm between macro base station and micro base station group[J]. Journal on Communications, 2019, 40(11): 19-29.

Figures/Tables 7

调制方案	编码码率	频率利用率/(bit.Hz^-1)	要求信噪比/dB
BPSK	$\frac{1}{4}$	$\frac{1}{4}$	–2.9
BPSK	$\frac{1}{2}$	$\frac{1}{2}$	–0.2
QPSK	$\frac{1}{2}$	1	2.2
8PSK	$\frac{1}{2}$	$\frac{3}{2}$	5.2
8PSK	$\frac{2}{3}$	2	8.4
64QAM	$\frac{1}{2}$	3	11.8
64QAM	$\frac{3}{2}$	4	15.1

References 15

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