F. R. V. Guimarães, Gábor Fodor, W. Freitas, Y. Silva
{"title":"动态TDD网络中基于多流定价的预编码和功率控制算法","authors":"F. R. V. Guimarães, Gábor Fodor, W. Freitas, Y. Silva","doi":"10.1109/CSCN.2019.8931407","DOIUrl":null,"url":null,"abstract":"Dynamic time division duplexing (DTDD) cellular networks enable to adapt the number of uplink and downlink time slots to the prevailing traffic demands in each cell at the expense of base station (BS)-to-BS and user equipment (UE)-to-UE interference. Recognizing the importance of mitigating the effect of these additional interference types, previous works proposed multicell coordinated beamforming to realize the full potential of DTDD systems that employ multiple antennas at the BSs. Unfortunately, the previously proposed mechanisms suffer from slow convergence, which renders such schemes impractical in fast fading and highly mobile environments. In this paper, we formulate the multicell multi-stream DTDD beamforming problem as an optimization task, and propose a near-optimal pricing-based algorithm to determine the beam directions and transmit power levels for each stream at the BSs. The proposed distributed precoding and power control algorithm not only improves the downlink performance, but it also substantially mitigates the BS-to-BS interference levels, and thereby improves the uplink performance as well. Simulation results indicate that the proposed algorithm exhibits faster convergence than previously proposed near-optimal schemes at the expense of some small performance degradation in terms of the achieved signal-to-interference-plus-noise-ratio (SINR).","PeriodicalId":102095,"journal":{"name":"2019 IEEE Conference on Standards for Communications and Networking (CSCN)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Multi-Stream Pricing-Based Precoding and Power Control Algorithm for Dynamic TDD Networks\",\"authors\":\"F. R. V. Guimarães, Gábor Fodor, W. Freitas, Y. Silva\",\"doi\":\"10.1109/CSCN.2019.8931407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dynamic time division duplexing (DTDD) cellular networks enable to adapt the number of uplink and downlink time slots to the prevailing traffic demands in each cell at the expense of base station (BS)-to-BS and user equipment (UE)-to-UE interference. Recognizing the importance of mitigating the effect of these additional interference types, previous works proposed multicell coordinated beamforming to realize the full potential of DTDD systems that employ multiple antennas at the BSs. Unfortunately, the previously proposed mechanisms suffer from slow convergence, which renders such schemes impractical in fast fading and highly mobile environments. In this paper, we formulate the multicell multi-stream DTDD beamforming problem as an optimization task, and propose a near-optimal pricing-based algorithm to determine the beam directions and transmit power levels for each stream at the BSs. The proposed distributed precoding and power control algorithm not only improves the downlink performance, but it also substantially mitigates the BS-to-BS interference levels, and thereby improves the uplink performance as well. Simulation results indicate that the proposed algorithm exhibits faster convergence than previously proposed near-optimal schemes at the expense of some small performance degradation in terms of the achieved signal-to-interference-plus-noise-ratio (SINR).\",\"PeriodicalId\":102095,\"journal\":{\"name\":\"2019 IEEE Conference on Standards for Communications and Networking (CSCN)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Conference on Standards for Communications and Networking (CSCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSCN.2019.8931407\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Conference on Standards for Communications and Networking (CSCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCN.2019.8931407","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Multi-Stream Pricing-Based Precoding and Power Control Algorithm for Dynamic TDD Networks
Dynamic time division duplexing (DTDD) cellular networks enable to adapt the number of uplink and downlink time slots to the prevailing traffic demands in each cell at the expense of base station (BS)-to-BS and user equipment (UE)-to-UE interference. Recognizing the importance of mitigating the effect of these additional interference types, previous works proposed multicell coordinated beamforming to realize the full potential of DTDD systems that employ multiple antennas at the BSs. Unfortunately, the previously proposed mechanisms suffer from slow convergence, which renders such schemes impractical in fast fading and highly mobile environments. In this paper, we formulate the multicell multi-stream DTDD beamforming problem as an optimization task, and propose a near-optimal pricing-based algorithm to determine the beam directions and transmit power levels for each stream at the BSs. The proposed distributed precoding and power control algorithm not only improves the downlink performance, but it also substantially mitigates the BS-to-BS interference levels, and thereby improves the uplink performance as well. Simulation results indicate that the proposed algorithm exhibits faster convergence than previously proposed near-optimal schemes at the expense of some small performance degradation in terms of the achieved signal-to-interference-plus-noise-ratio (SINR).