Joint User Scheduling and Resource Allocation in Distributed MIMO Systems with Multi-Carriers
Compared with the traditional collocated multi-input multi-output system (C-MIMO), distributed MIMO (D-MIMO) systems have the advantage of higher throughput and coverage, making them strong candidates for next-generation communication architecture. As a practical implementation of a D-MIMO cooperati...
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Veröffentlicht in: | Electronics (Basel) 2022-06, Vol.11 (12), p.1836 |
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description | Compared with the traditional collocated multi-input multi-output system (C-MIMO), distributed MIMO (D-MIMO) systems have the advantage of higher throughput and coverage, making them strong candidates for next-generation communication architecture. As a practical implementation of a D-MIMO cooperative network, the multi-TRP (multiple transmission/reception point) system becomes a hotspot in the research of advanced 5G. Different from previous research on a cooperative D-MIMO network with single narrowband transmission, this paper proposes a joint optimization scheme to address the user scheduling problem along with carrier allocation to maximize the total spectral efficiency (SE) in the downlink of coherent multi-TRP systems with multi-carriers. We establish a joint optimization model of user scheduling and resource allocation to maximize the system spectral efficiency under the constraints of power consumption and the backhaul capacity limits at each RAU (remote antenna unit), as well as the QoS (quality of service) requirement at each user. Since the optimization model is both non-covex and non-smooth, a joint optimization algorithm is proposed to solve this non-convex combinatorial optimization problem. We first smooth the mixed-integer problem by employing penalty functions, and after decoupling the coupled variables by introducing auxiliary variables, the original problem is transformed into a series of tractable convex optimization problems by using successive convex approximation (SCA). Numerical results demonstrate that the proposed joint optimization algorithm for user scheduling and resource allocation can reliably converge and achieve a higher system SE than the general multi-TRP system without carrier allocation, and this advantage is more pronounced under a higher backhaul capacity or higher power consumption constraints. |
doi_str_mv | 10.3390/electronics11121836 |
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As a practical implementation of a D-MIMO cooperative network, the multi-TRP (multiple transmission/reception point) system becomes a hotspot in the research of advanced 5G. Different from previous research on a cooperative D-MIMO network with single narrowband transmission, this paper proposes a joint optimization scheme to address the user scheduling problem along with carrier allocation to maximize the total spectral efficiency (SE) in the downlink of coherent multi-TRP systems with multi-carriers. We establish a joint optimization model of user scheduling and resource allocation to maximize the system spectral efficiency under the constraints of power consumption and the backhaul capacity limits at each RAU (remote antenna unit), as well as the QoS (quality of service) requirement at each user. Since the optimization model is both non-covex and non-smooth, a joint optimization algorithm is proposed to solve this non-convex combinatorial optimization problem. We first smooth the mixed-integer problem by employing penalty functions, and after decoupling the coupled variables by introducing auxiliary variables, the original problem is transformed into a series of tractable convex optimization problems by using successive convex approximation (SCA). Numerical results demonstrate that the proposed joint optimization algorithm for user scheduling and resource allocation can reliably converge and achieve a higher system SE than the general multi-TRP system without carrier allocation, and this advantage is more pronounced under a higher backhaul capacity or higher power consumption constraints.</description><identifier>ISSN: 2079-9292</identifier><identifier>EISSN: 2079-9292</identifier><identifier>DOI: 10.3390/electronics11121836</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Algorithms ; Antennas ; Combinatorial analysis ; Communication ; Computational geometry ; Convex analysis ; Convexity ; Cooperation ; Decoupling ; Energy efficiency ; Integer programming ; MIMO communication ; Mixed integer ; Narrowband ; Optimization ; Optimization models ; Penalty function ; Power consumption ; Resource allocation ; Resource scheduling ; Scheduling ; Variables</subject><ispartof>Electronics (Basel), 2022-06, Vol.11 (12), p.1836</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c322t-2f95aebd5650ed05abb808ce497f8882b90025f8f29350353974d04653793b813</citedby><cites>FETCH-LOGICAL-c322t-2f95aebd5650ed05abb808ce497f8882b90025f8f29350353974d04653793b813</cites><orcidid>0000-0002-7020-8996</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Bu, Yinglan</creatorcontrib><creatorcontrib>Zong, Jiaying</creatorcontrib><creatorcontrib>Xia, Xinjiang</creatorcontrib><creatorcontrib>Liu, Yang</creatorcontrib><creatorcontrib>Yang, Fengyi</creatorcontrib><creatorcontrib>Wang, Dongming</creatorcontrib><title>Joint User Scheduling and Resource Allocation in Distributed MIMO Systems with Multi-Carriers</title><title>Electronics (Basel)</title><description>Compared with the traditional collocated multi-input multi-output system (C-MIMO), distributed MIMO (D-MIMO) systems have the advantage of higher throughput and coverage, making them strong candidates for next-generation communication architecture. 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We first smooth the mixed-integer problem by employing penalty functions, and after decoupling the coupled variables by introducing auxiliary variables, the original problem is transformed into a series of tractable convex optimization problems by using successive convex approximation (SCA). Numerical results demonstrate that the proposed joint optimization algorithm for user scheduling and resource allocation can reliably converge and achieve a higher system SE than the general multi-TRP system without carrier allocation, and this advantage is more pronounced under a higher backhaul capacity or higher power consumption constraints.</description><subject>Algorithms</subject><subject>Antennas</subject><subject>Combinatorial analysis</subject><subject>Communication</subject><subject>Computational geometry</subject><subject>Convex analysis</subject><subject>Convexity</subject><subject>Cooperation</subject><subject>Decoupling</subject><subject>Energy efficiency</subject><subject>Integer programming</subject><subject>MIMO communication</subject><subject>Mixed integer</subject><subject>Narrowband</subject><subject>Optimization</subject><subject>Optimization models</subject><subject>Penalty function</subject><subject>Power consumption</subject><subject>Resource allocation</subject><subject>Resource scheduling</subject><subject>Scheduling</subject><subject>Variables</subject><issn>2079-9292</issn><issn>2079-9292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNptUM1OwzAYixBITGNPwCUS50KSb2mS4zT-hlZNYuyIqjb9yjJ17UhSob09RePAAV_sg2VbJuSas1sAw-6wQRt91zobOOeCa0jPyEgwZRIjjDj_oy_JJIQdG2A4aGAj8v7SuTbSTUBP13aLVd-49oMWbUVfMXS9t0hnTdPZIrqupa6l9y5E78o-YkWzRbai62OIuA_0y8UtzfomumReeO_QhytyURdNwMkvj8nm8eFt_pwsV0-L-WyZWBAiJqI2ssCykqlkWDFZlKVm2uLUqFprLUrDmJC1roUByUCCUdOKTVMJykCpOYzJzSn34LvPHkPMd8P0dqjMRaqMYopDOrjg5LK-C8FjnR-82xf-mHOW_1yZ_3MlfAOP3WlI</recordid><startdate>20220601</startdate><enddate>20220601</enddate><creator>Bu, Yinglan</creator><creator>Zong, Jiaying</creator><creator>Xia, Xinjiang</creator><creator>Liu, Yang</creator><creator>Yang, Fengyi</creator><creator>Wang, Dongming</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L7M</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0002-7020-8996</orcidid></search><sort><creationdate>20220601</creationdate><title>Joint User Scheduling and Resource Allocation in Distributed MIMO Systems with Multi-Carriers</title><author>Bu, Yinglan ; 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subjects | Algorithms Antennas Combinatorial analysis Communication Computational geometry Convex analysis Convexity Cooperation Decoupling Energy efficiency Integer programming MIMO communication Mixed integer Narrowband Optimization Optimization models Penalty function Power consumption Resource allocation Resource scheduling Scheduling Variables |
title | Joint User Scheduling and Resource Allocation in Distributed MIMO Systems with Multi-Carriers |
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