Optimization and Design of Beamforming for Cellular Internet-of-Things with Energy Efficiency Maximization in Short Packet Domain
-
摘要: 为了满足未来蜂窝物联网(IoT)中超高可靠和超低时延的要求，该文提出一种适用于多小区多用户超高可靠极低时延网络短包域公平性能量效率最大化算法。首先，以最小用户传输速率、每个发射机最大功率等约束为限制，构建了一个关于波束成形矢量的非线性分式规划资源配置模型。随后，采用变量代换、连续凸近似等技术，将原始非凸优化问题转化为标准的凸问题，进而提出一种短包域迭代能量效率最优化方法进行求解。最后，数值仿真结果验证了所提算法在短包域具有良好的能量效率性能。Abstract: In order to meet the requirements of ultra-high reliability and ultra-low latency in future cellular Internet-of-Things (IoT), an algorithm for such networks, which ensures the fairness-aware energy efficiency maximization in short packet domain, is developed. Firstly, a nonlinear fractional programming resource allocation model, which optimize the beamforming vector, is constructed with several constraints such as minimum user transmission rate and maximum power of per transmitter. Subsequently, the original non-convex optimization problem is transformed into a standard convex problem by exploiting the variable substitution and continuous convex approximation. Furthermore, an iterative energy efficiency optimization algorithm is developed in short packet regime. Finally, the numerical simulation results verify that the proposed algorithm has good energy efficiency performance in the short packet domain.
-
1 短包域能量效率最大化算法(算法1)
(1) 令$n = 0 $，设置满足功率约束的初始波束矢量${{\boldsymbol{w}}^{\left( n \right)}} $，算法的
最大迭代次数为${N_{\max }} $。(2) 通过约束${\text{C}}{{\text{3}}'} $，C4，C5，式(8)和式(13)，计算得到和
$\left\{ {x_j^{\left( n \right)},y_j^{\left( n \right)},{\boldsymbol{\upsilon}} _j^{\left( n \right)},\zeta _{j,k}^{\left( n \right)} } \right\}$。(3) 开始循环： (4) 依据${{\boldsymbol{w}}^{\left( n \right)}} $, $x_j^{\left( n \right)} $, $y_j^{\left( n \right)} $, ${\boldsymbol{\upsilon}} _j^{\left( n \right)}$和$ \zeta _{j,k}^{\left( n \right)} $，通过求解P1，输出相应
的解${t^ * } $, ${{\boldsymbol{w}}^{\text{*} } }$, $x_j^ * $, $y_j^ * $, ${\boldsymbol{\upsilon}} _j^ *$和$\zeta _{j,k}^ * $。(5) 更新${{\boldsymbol{w}}^{\left( {n + 1} \right)}} = {{\boldsymbol{w}}^ * } $, $ x_j^{\left( {n + 1} \right)} = x_j^ * $, $y_j^{\left( {n + 1} \right)} = y_j^ * $,
${\boldsymbol{\upsilon}} _j^{\left( {n + 1} \right)} = {\boldsymbol{\upsilon}} _j^ *$, $\zeta _{j,k}^{\left( {n + 1} \right)} = \zeta _{j,k}^ * $。(6) 更新P1的代价函数值：${t^{\left( {n + 1} \right)}} = {t^ * } $。 (7) 若$ \left| {{t^{\left( {n + 1} \right)}} - {t^{\left( n \right)}}} \right| < \xi $或$n > {N_{\max }} $，其中$\xi $表示预置的任意小
的数，则跳出循环并输出最终的解；否则，$n = n + 1 $,
${{\boldsymbol{w}}^{\left( n \right)}} = {{\boldsymbol{w}}^ * } $, $x_j^{\left( n \right)} = x_j^ * $, $y_j^{\left( n \right)} = y_j^ * $, ${\boldsymbol{\upsilon}} _j^{\left( n \right)} = {\boldsymbol{\upsilon}} _j^ *$,
$\zeta _{j,k}^{\left( n \right)} = \zeta _{j,k}^ * $, ${t^{\left( n \right)}} = {t^ * } $，回到第(3)步。
下载: 导出CSV
-
[1] 丰雷, 谢坤宜, 朱亮, 等. 面向电网业务质量保障的5G高可靠低时延通信资源调度方法[J]. 电子与信息学报, 2021, 43(12): 3418–3426. doi: 10.11999/JEIT210509FENG Lei, XIE Kunyi, ZHU Liang, et al. 5G ultra-reliable and low latency communication resource scheduling for power business quality assurance[J]. Journal of Electronics &Information Technology, 2021, 43(12): 3418–3426. doi: 10.11999/JEIT210509 [2] FENG Chen and WANG Huiming. Secure short-packet communications at the physical layer for 5G and beyond[J]. IEEE Communications Standards Magazine, 2021, 5(3): 96–102. doi: 10.1109/MCOMSTD.121.2100028 [3] 许方敏, 伍丽娇, 王翔, 等. 5G上行链路中基于预测的紧急资源分配方法研究[J]. 电子与信息学报, 2022, 44(2): 611–619. doi: 10.11999/JEIT201050XU Fangmin, WU Lijiao, WANG Xiang, et al. Research on prediction based emergency resource allocation in 5G uplink[J]. Journal of Electronics &Information Technology, 2022, 44(2): 611–619. doi: 10.11999/JEIT201050 [4] ZHANG Qianqian, LIANG P P, HUANG Yudi, et al. Label-assisted transmission for short packet communications: A machine learning approach[J]. IEEE Transactions on Vehicular Technology, 2018, 67(9): 8846–8859. doi: 10.1109/TVT.2018.2851619 [5] SINGH K, BISWAS S, KU Menglin, et al. Transceiver design and power control for full-duplex ultra-reliable low-latency communication systems[J]. IEEE Transactions on Wireless Communications, 2022, 21(2): 1392–1406. doi: 10.1109/TWC.2021.3103861 [6] 胡锦松, 吴林梅, 束锋, 等. 无人机中继协助的有限码长隐蔽通信[J]. 电子与信息学报, 2022, 44(3): 1006–1013. doi: 10.11999/JEIT211372HU Jinsong, WU Linmei, SHU Feng, et al. UAV-relay assisted covert communication with finite block-length[J]. Journal of Electronics &Information Technology, 2022, 44(3): 1006–1013. doi: 10.11999/JEIT211372 [7] SHIRVANIMOGHADDAM M, MOHAMMADI M S, ABBAS R, et al. Short block-length codes for ultra-reliable low latency communications[J]. IEEE Communications Magazine, 2019, 57(2): 130–137. doi: 10.1109/MCOM.2018.1800181 [8] POLYANSKIY Y, POOR H V, and VERDU S. Channel coding rate in the finite blocklength regime[J]. IEEE Transactions on Information Theory, 2010, 56(5): 2307–2359. doi: 10.1109/TIT.2010.2043769 [9] HU Yulin, OZMEN M, and GURSOY M C. Optimal power allocation for QoS-constrained downlink multi-user networks in the finite blocklength regime[J]. IEEE Transactions on Wireless Communications, 2018, 17(9): 5827–5840. doi: 10.1109/TWC.2018.2850302 [10] NASIR A A, TUAN H D, NGUYEN H H, et al. Resource allocation and beamforming design in the short blocklength regime for URLLC[J]. IEEE Transactions on Wireless Communications, 2021, 20(2): 1321–1335. doi: 10.1109/TWC.2020.3032729 [11] KHALIFA N B, ANGILELLA V, ASSAAD M, et al. Low-complexity channel allocation scheme for URLLC traffic[J]. IEEE Transactions on Communications, 2021, 69(1): 194–206. doi: 10.1109/TCOMM.2020.3022008 [12] MAKKI B, SVENSSON T, and ZORZI M. Finite block-length analysis of spectrum sharing networks using rate adaptation[J]. IEEE Transactions on Communications, 2015, 63(8): 2823–2835. doi: 10.1109/TCOMM.2015.2449842 [13] CAI Yeming, JIANG Xu, LIU Mingqian, et al. Resource allocation for URLLC-oriented two-way UAV relaying[J]. IEEE Transactions on Vehicular Technology, 2022, 71(3): 3344–3349. doi: 10.1109/TVT.2022.3143174 [14] SUN Chengjian, SHE Changyang, YANG Chenyang, et al. Optimizing resource allocation in the short blocklength regime for ultra-reliable and low-latency communications[J]. IEEE Transactions on Wireless Communications, 2019, 18(1): 402–415. doi: 10.1109/TWC.2018.2880907 [15] SABUJ S R, AHMED A, CHO Y, et al. Cognitive UAV-aided URLLC and mMTC services: Analyzing energy efficiency and latency[J]. IEEE ACCESS, 2021, 9: 5011–5027. doi: 10.1109/ACCESS.2020.3048436 [16] SINGH K, KU Menglin, and FLANAGAN M F. Energy-efficient precoder design for downlink multi-user MISO networks with finite blocklength codes[J]. IEEE Transactions on Green Communications and Networking, 2021, 5(1): 160–173. doi: 10.1109/TGCN.2020.3045687 -
下载:
图(4) / 表(1)
计量
- 文章访问数: 319
- HTML全文浏览量: 107
- PDF下载量: 111
- 被引次数: 0
