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Optimal Power Control and Load Balancing for Uplink Cell-Free Multi-User Massive MIMO
In this paper, we consider the problem of power control and load balancing in the uplink of the cell-free (CF) multi-user (MU) massive multiple-input multiple-output system. The power control problem is solved using three different criteria: 1) power minimization; 2) maximize min quality of service...
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Published in: | IEEE access 2018-01, Vol.6, p.14462-14473 |
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description | In this paper, we consider the problem of power control and load balancing in the uplink of the cell-free (CF) multi-user (MU) massive multiple-input multiple-output system. The power control problem is solved using three different criteria: 1) power minimization; 2) maximize min quality of service (QoS); and 3) maximize sum spectral efficiency (SE) under imperfect channel state information. While power minimization and min-QoS maximization problems can be solved in polynomial time, sum SE maximization is NP-hard. Hence, we apply a successive approach to convert it into a geometric program and achieve near optimum solution. As the number of connections in CF-MU system is large, we minimize the number of base stations (BSs) serving each user while maintaining the optimized power consumption and QoS from the previous stage. We propose an iterative elimination (IE) algorithm to remove ineffective BSs for each user. The system analysis is performed under two common BS receivers: maximum ratio combining and zero forcing. The simulation shows that our method is better than both maximum signal-to-noise ratio association and full-set joint transmission, especially in the high QoS regime. Another notable result is that the selection of the linear receiver becomes more influential than the association method. |
doi_str_mv | 10.1109/ACCESS.2018.2797874 |
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The power control problem is solved using three different criteria: 1) power minimization; 2) maximize min quality of service (QoS); and 3) maximize sum spectral efficiency (SE) under imperfect channel state information. While power minimization and min-QoS maximization problems can be solved in polynomial time, sum SE maximization is NP-hard. Hence, we apply a successive approach to convert it into a geometric program and achieve near optimum solution. As the number of connections in CF-MU system is large, we minimize the number of base stations (BSs) serving each user while maintaining the optimized power consumption and QoS from the previous stage. We propose an iterative elimination (IE) algorithm to remove ineffective BSs for each user. The system analysis is performed under two common BS receivers: maximum ratio combining and zero forcing. The simulation shows that our method is better than both maximum signal-to-noise ratio association and full-set joint transmission, especially in the high QoS regime. Another notable result is that the selection of the linear receiver becomes more influential than the association method.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2018.2797874</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Algorithms ; Antennas ; Energy conversion efficiency ; Interference ; Linear receivers ; Load balancing ; Load management ; Massive MIMO ; Maximization ; MIMO (control systems) ; MIMO communication ; Optimization ; Polynomials ; power allocation ; Power consumption ; Power control ; Quality of service ; Receivers ; Signal to noise ratio ; Systems analysis ; Uplink ; user association</subject><ispartof>IEEE access, 2018-01, Vol.6, p.14462-14473</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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Another notable result is that the selection of the linear receiver becomes more influential than the association method.</description><subject>Algorithms</subject><subject>Antennas</subject><subject>Energy conversion efficiency</subject><subject>Interference</subject><subject>Linear receivers</subject><subject>Load balancing</subject><subject>Load management</subject><subject>Massive MIMO</subject><subject>Maximization</subject><subject>MIMO (control systems)</subject><subject>MIMO communication</subject><subject>Optimization</subject><subject>Polynomials</subject><subject>power allocation</subject><subject>Power consumption</subject><subject>Power control</subject><subject>Quality of service</subject><subject>Receivers</subject><subject>Signal to noise ratio</subject><subject>Systems analysis</subject><subject>Uplink</subject><subject>user association</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>DOA</sourceid><recordid>eNpNUU1LAzEQXURBUX-Bl4DnrZl8bfaoS6uFlgrac0iTrGyNm5psFf-9qSviXGZ4zHvzhlcUV4AnALi-uW2a6dPThGCQE1LVlazYUXFGQNQl5VQc_5tPi8uUtjiXzBCvzor1ajd0b9qjx_DpImpCP8Tgke4tWgRt0Z32ujdd_4LaENF657v-FTXO-3IWnUPLvR-6cp0ydalT6j4yNF-uLoqTVvvkLn_7ebGeTZ-bh3Kxup83t4vSsIoNpcBUcEaJZOCAkeypNRXHBlpWA3cAlZQGasuFw5QxLDUYY4nOoICaW3pezEddG_RW7WL-JH6poDv1A4T4onQcOuOdsu2GWMsYMXbDJBgtKKOGgt2AkxtBs9b1qLWL4X3v0qC2YR_7bF8RxrmsZQWQt-i4ZWJIKbr27ypgdYhDjXGoQxzqN47MuhpZnXPujyHzx0ww-g1fO4NH</recordid><startdate>20180101</startdate><enddate>20180101</enddate><creator>Nguyen, Tien Hoa</creator><creator>Nguyen, The Khai</creator><creator>Han, Huy Dung</creator><creator>Nguyen, Van Duc</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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The power control problem is solved using three different criteria: 1) power minimization; 2) maximize min quality of service (QoS); and 3) maximize sum spectral efficiency (SE) under imperfect channel state information. While power minimization and min-QoS maximization problems can be solved in polynomial time, sum SE maximization is NP-hard. Hence, we apply a successive approach to convert it into a geometric program and achieve near optimum solution. As the number of connections in CF-MU system is large, we minimize the number of base stations (BSs) serving each user while maintaining the optimized power consumption and QoS from the previous stage. We propose an iterative elimination (IE) algorithm to remove ineffective BSs for each user. The system analysis is performed under two common BS receivers: maximum ratio combining and zero forcing. 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subjects | Algorithms Antennas Energy conversion efficiency Interference Linear receivers Load balancing Load management Massive MIMO Maximization MIMO (control systems) MIMO communication Optimization Polynomials power allocation Power consumption Power control Quality of service Receivers Signal to noise ratio Systems analysis Uplink user association |
title | Optimal Power Control and Load Balancing for Uplink Cell-Free Multi-User Massive MIMO |
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