Research on D2D Joint Mode Selection and Resource Allocation

doi:10.11871/jfdc.issn.2096-742X.2023.06.016

Abstract

Abstract:

[Objective] In the case of relatively scarce communication resources, the D2D direct reuse technology of cellular network resources may cause numerous technical problems such as interference management, communication mode selection, and resource allocation. [Methods] This paper studies the scheme of the combination of mode selection, channel distribution, and power control. Because optimizing the combination scheme is an NP-hard problem, this paper divides the optimization problem into two sub-problems: one is to select an appropriate communication mode and allocate reasonable channel resources for each D2D user, and the other is to optimize the power for D2D users and honeycomb users by the improved gray wolf algorithm. The goal of this approach is to improve the overall system throughput and reduce the interference. [Results] The experimental results in different scenarios show that this approach can effectively reduce the interference and improve the system throughput. The improved gray wolf algorithm has increased the average throughput by about 4% for this solution. [Limitations] The Gray Wolf Optimization Algorithm is continuously evolving and introduces certain limitations. [Conclusions] The subsequent work will continue to explore and consider the network status and the user mobility, improving both performance and throughput of the system.

Key words: cellular network, D2D, mode selection, resource allocation, gray wolf algorithm

ZHENG Yijia, DU Yongwen, HUANG Ju, ZHANG Xiquan. Research on D2D Joint Mode Selection and Resource Allocation[J]. Frontiers of Data and Computing, 2023, 5(6): 173-184, https://cstr.cn/32002.14.jfdc.CN10-1649/TP.2023.06.016.

Figures/Tables 11

Fig.1

Algorithm 1: Mode selection algorithm

计算每个D2D用户在蜂窝模式和专用模式的信道容量
创建一个向量集合T,其中元素为每个D2D用户在蜂窝模式下和专用模式下信道容量对比后的最大值.
初始化上行信道计数器

n 1

=0,下行信道计数器

n 2

=0.
While

n 1

N u

and

n 2

N D

do
select k*= argmaxTk
If

T k *

T k * 1

then

n 2

set

n 1

n 1

+1,

n 2

=n2+1,

x k * 1

=1.
else
if

N u

-n1>

N D

-n2 then
set n1=n1+1 and

x k * 2

=1.
else
set n₂=n₂+1 and

x k * 2

=1.
end if
end if
Set

T k * 1

T k * 2

=0_,并且更新T
end while
For i=1 to max{

N u

-n1,

N D

-n2}
select k*=argmax

T k 2

,set

x k * 2

=1
end for

Algorithm 2: The Channel Allocation Algorithm
初始化M个CU和N个DU的用户参数信息利用HK算法得到矩阵（35）中每个DU的最佳信道安排. for all k=1:k- $N D$ - $N u$ do set $x π k, ω π k 3$ =1 end for for all k=1:k- $N D$ +1:k do set $x π k 2$ =1 end for

Fig.2

Fig.3

Algorithm 3： Power control algorithm

输入：种群数量，搜索维度，迭代次数，D2D用户
输出: 吞吐量
初始化种群数量，计算满足约束条件（15）和（16）的个体位置；
根据（20），（21），（22）计算适应度值；
找出三个最大适应度值；
While（t<t_max）;
通过改进的非线性收敛因子以及种群更新策略更新

X α

、

X β

、

X δ

：
t=t+1
end while
最优个体为DUE最优功率分配结果，得到最佳发射功率矩阵；
输出系统中所有DUE的最大吞吐量

Table 4

Simulation parameters"

参数	参数值
蜂窝半径（R）	0.5KM
蜂窝用户数	10-20
带宽	180KHZ
最大CU传输功率	25dBm
最大D2D传输功率	25dBm
上行信道数	20
下行信道数	20
SING阈值, $? m i n$	10dm
D2D用户数	活跃的CU个数的10%，20%...100%
噪声功率	-174dBm/HZ
快速衰落	瑞丽衰落

Table 4

Table 5

Benchmark functions"

Function	Function Expression	Range	Fmin
F7	$f 7 (x) = 0.1 {s i n 2 (3 π x 1) + ∑ i = 1 n (x i - 1) 2 [1 + s i n 2 (3 π x i + 1)] + (x n - 1) 2 [1 + s i n 2 (2 π x n)]} + ∑ i = 1 n u (x i, 5,100,4)$	[-1.28,1.28]	0
F10	$f 10 (x) = - 20 e x p (- 0.2 1 n ∑ i = 1 n c o s (2 π x i)) + 20 + e$	[-32,32]	0
F14	$f 14 (x) = 1500 + ∑ j = 1 25 1 j + ∑ i = 1 2 (x i - x i j) 6 - 1$	[-65,65]	1
F15	$f 15 (x) = ∑ i = 1 11 [a i - x 1 (b i 2 + b i x 2) b i 2 + b i x 3 + x 4] 2$	[-5,5]	0.00030

Table 5

Fig.4

Fig.5

Fig.6

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