具有能量采集的中继辅助多层异构网络中的节能带宽和功率分配

doi:10.1007/s12204-021-2336-y

J Shanghai Jiaotong Univ Sci ›› 2023, Vol. 28 ›› Issue (6): 822-830.doi: 10.1007/s12204-021-2336-y

具有能量采集的中继辅助多层异构网络中的节能带宽和功率分配

高锦程，赵宜升，陈加法，陈忠辉

（福州大学物理与信息工程学院，福州350108）

接受日期:2020-08-07 出版日期:2023-11-28 发布日期:2023-12-04

Energy-Efficient Bandwidth and Power Allocation in Relay-Assisted Multi-Layer Heterogeneous Networks with Energy Harvesting

GAO Jincheng (高锦程)，ZHAO Yisheng* (赵宜升)，CHEN Jiafa (陈加法)，CHEN Zhonghui (陈忠辉)

(Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China)

Accepted:2020-08-07 Online:2023-11-28 Published:2023-12-04

摘要/Abstract

摘要： 针对多层异构网络中微微基站存用户过多的情况，本文研究了异构网络中能量效率最大化的资源分配问题。微微基站中部分用户的数据通过具有能量收集功能的中继节点传输到相邻的空闲微微基站。考虑用户和中继节点的带宽和发射功率，建立资源分配优化问题。在用户最小数据速率和能量消耗的约束条件下，使整个异构网络的能量效率最大化。采用粒子群优化算法和量子行为粒子群优化算法获得次优解。仿真结果表明，采用的方法比传统的固定功率和带宽方法具有更高的能量效率。此外，采用的方法的时间复杂度相对较低。

关键词: 能量收集，异构网络，能量效率

Abstract: Aiming at excessive users existing in a pico base station (PBS) in the multi-layer heterogeneous networks, the resource allocation problem of maximizing the energy efficiency of the networks is investigated in this paper. By deploying a relay node with energy harvesting function, the data of some users in the PBS can be transferred to an adjacent idle PBS. The bandwidth and transmitting power of users and the relay node are both considered to formulate the resource allocation optimization problem. The objective is to maximize the energy efficiency of the whole heterogeneous networks under the constraints of the user’s minimum data rate and energy consumption. The suboptimal solution is obtained by using the particle swarm optimization (PSO) algorithm and quantum-behaved particle swarm optimization (QPSO) algorithm. Simulation results show that the adopted methods have higher energy efficiency than the conventional fixed power and bandwidth method. In addition, the time complexity of the adopted methods is relatively low.

Key words: energy harvesting, heterogeneous networks, energy efficiency

中图分类号:

TN915.65

高锦程，赵宜升，陈加法，陈忠辉. 具有能量采集的中继辅助多层异构网络中的节能带宽和功率分配[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(6): 822-830.

GAO Jincheng (高锦程)，ZHAO Yisheng* (赵宜升)，CHEN Jiafa (陈加法)，CHEN Zhonghui (陈忠辉). Energy-Efficient Bandwidth and Power Allocation in Relay-Assisted Multi-Layer Heterogeneous Networks with Energy Harvesting[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(6): 822-830.

参考文献 15

[10]	HADZI-VELKOV Z, ZLATANOV N, DUONG T Q, et al. Rate maximization of decode-and-forward relaying systems with RF energy harvesting [J]. IEEE Communications Letters, 2015, 19(12): 2290-2293.
[1]	LU X, WANG P, NIYATO D, et al. Wireless networks with RF energy harvesting: A contemporary survey [J]. IEEE Communications Surveys & Tutorials, 2015, 17(2): 757-789.
[11]	BHARADIA D, BANSAL G, KALIGINEEDI P, et al. Relay and power allocation schemes for OFDMbased cognitive radio systems [J]. IEEE Transactions on Wireless Communications, 2011, 10(9): 2812-2817.
[2]	ZHAO M, ZHAO J, ZHOU W, et al. Energy efficiency optimization in relay-assisted networks with energy harvesting relay constraints [J]. China Communications, 2015, 12(2): 84-94.
[12]	POLI R, KENNEDY J, BLACKWELL T. Particle swarm optimization: An overview [J]. Swarm Intelligence, 2007, 1(1): 33-57.
[3]	MAHDAVI-DOOST H, PRASAD N, RANGARAJAN S. Optimizing energy efficiency over energy-harvesting LTE cellular networks [J]. IEEE Transactions on Green Communications and Networking, 2017, 1(3): 320-332.
[13]	SUN J, FANG W, WU X, et al. Quantum-behaved particle swarm optimization: Analysis of individual particle behavior and parameter selection [J]. Evolutionary Computation, 2012, 20(3): 349-393.
[4]	ZHANG J, TAO X, ZHANG X, et al. Energy-aware user association in heterogeneous networks with renewable energy supplies [C]//IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications. Montreal, Canada: IEEE, 2017: 1-7.
[14]	3GPP. User equipment (UE) radio transmission and reception (FDD) [S]. France: 3GPP, 2018.
[5]	ZHANG H, HUANG S, JIANG C, et al. Energy efficient user association and power allocation in millimeter-wave-based ultra dense networks with energy harvesting base stations [J]. IEEE Journal onSelected Areas in Communications, 2017, 35(9): 1936- 1947.
[15]	SONG C, HUANG Y, CARTER P, et al. A novel six-band dual CP rectenna using improved impedance matching technique for ambient RF energy harvesting [J]. IEEE Transactions on Antennas and Propagation, 2016, 64(7): 3160-3171.
[6]	YE G, ZHANG H, LIU H, et al. Energy efficient joint user association and power allocation in a two-tier heterogeneous network [C]//2016 IEEE Global Communications Conference. Washington, DC, USA: IEEE, 2016: 1-5.
[7]	YU G, JIANG Y, XU L, et al. Multi-objective energyefficient resource allocation for multi-RAT heterogeneous networks [J]. IEEE Journal on Selected Areas in Communications, 2015, 33(10): 2118-2127.
[8]	KUANG Z, LIU G, LI G, et al. Energy efficient resource allocation algorithm in energy harvesting-based D2D heterogeneous networks [J]. IEEE Internet of Things Journal, 2019, 6(1): 557-567.
[9]	ZHAO Y, LEUNG V C M, ZHU C, et al. Energyefficient sub-carrier and power allocation in cloudbased cellular network with ambient RF energy harvesting [J]. IEEE Access, 2017, 5: 1340-1352.
[10]	HADZI-VELKOV Z, ZLATANOV N, DUONG T Q, et al. Rate maximization of decode-and-forward relaying systems with RF energy harvesting [J]. IEEE Communications Letters, 2015, 19(12): 2290-2293.
[11]	BHARADIA D, BANSAL G, KALIGINEEDI P, et al. Relay and power allocation schemes for OFDMbased cognitive radio systems [J]. IEEE Transactions on Wireless Communications, 2011, 10(9): 2812-2817.
[12]	POLI R, KENNEDY J, BLACKWELL T. Particle swarm optimization: An overview [J]. Swarm Intelligence, 2007, 1(1): 33-57.
[13]	SUN J, FANG W, WU X, et al. Quantum-behaved particle swarm optimization: Analysis of individual particle behavior and parameter selection [J]. Evolutionary Computation, 2012, 20(3): 349-393.
[14]	3GPP. User equipment (UE) radio transmission and reception (FDD) [S]. France: 3GPP, 2018.
[15]	SONG C, HUANG Y, CARTER P, et al. A novel six-band dual CP rectenna using improved impedance matching technique for ambient RF energy harvesting [J]. IEEE Transactions on Antennas and Propagation, 2016, 64(7): 3160-3171.

具有能量采集的中继辅助多层异构网络中的节能带宽和功率分配

Energy-Efficient Bandwidth and Power Allocation in Relay-Assisted Multi-Layer Heterogeneous Networks with Energy Harvesting

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