Load Balancing User Association in Millimeter Wave MIMO Networks

User association is necessary in dense millimeter wave (mmWave) networks to determine which base station a user connects to in order to balance base station loads and maximize a network utility. Given that mmWave connections are highly directional and vulnerable to small channel variations, user ass...

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Bibliographic Details
Published in:IEEE transactions on wireless communications Vol. 18; no. 6; pp. 2932 - 2945
Main Authors: Alizadeh, Alireza, Vu, Mai
Format: Journal Article
Language:English
Published: New York IEEE 01.06.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Cellular communication
Cellular networks
Combinatorial analysis
Computer simulation
Genetic algorithms
Interference
Load balancing
load balancing; MINLP
Load management
Millimeter waves
MIMO communication
Mixed integer
mmWave MIMO systems
Nonlinear programming
Optical wavelength conversion
Optimization
polynomial-time algorithm
Polynomials
Radio equipment
Simulation
User association
ISSN:1536-1276, 1558-2248
Online Access:Get full text
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Summary:User association is necessary in dense millimeter wave (mmWave) networks to determine which base station a user connects to in order to balance base station loads and maximize a network utility. Given that mmWave connections are highly directional and vulnerable to small channel variations, user association changes these connections and hence significantly affects the network interference and consequently the users' instantaneous rates. In this paper, we introduce a new load balancing user association scheme for mmWave MIMO cellular networks which consider these dependencies. We formulate the user association problem as mixed integer nonlinear programming and design a polynomial-time algorithm, called worst connection swapping (WCS), to find a near-optimal solution. Simulation results confirm that the proposed user association scheme improves network performance significantly by adjusting the interference according to the association, and under the max-min fairness, also enhances cell-edge users' transmission rates. We also show how the proposed algorithm can be applied under mobility. Furthermore, the proposed WCS algorithm outperforms other generic algorithms for combinatorial programming such as the genetic algorithm in both accuracy and speed at several orders of magnitude faster, and for small networks, where exhaustive search is possible, it reaches the optimal solution.
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ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2019.2906196