Near-optimal user-cell association schemes for real-world networks

The growing demand for wireless bandwidth makes WiFi deployments denser and pushes cellular networks to adopt a denser, small-cell architecture. In such dense environments, users have multiple options when it comes to selecting an access point (AP) to associate with the network, and the user-cell association scheme that is used has a large impact on overall network performance. Industry is currently using simplistic, sub-optimal approaches to select an AP for each user, while academia has produced optimal schemes under unrealistic assumptions, which prevents them from ever being used in practice. In this paper we design high-performance user-cell association schemes which can be deployed in real-world networks. The performance of the proposed schemes is shown to be near-optimal via both formal performance bounds under realistic assumptions, and simulation results under real-world setups.

[1]  Jeffrey G. Andrews,et al.  User Association for Load Balancing in Heterogeneous Cellular Networks , 2012, IEEE Transactions on Wireless Communications.

[2]  Leszek Gasieniec,et al.  Proceedings of the eighteenth annual ACM-SIAM symposium on discrete algorithms , 2007, SODA 2007.

[3]  Yishay Mansour,et al.  Strong price of anarchy , 2007, SODA '07.

[4]  Paramvir Bahl,et al.  Towards an Architecture for Efficient Spectrum Slicing , 2007 .

[5]  Alec Wolman,et al.  Beacon-Stuffing: Wi-Fi without Associations , 2007, Eighth IEEE Workshop on Mobile Computing Systems and Applications.

[6]  Paramvir Bahl,et al.  Cell Breathing in Wireless LANs: Algorithms and Evaluation , 2007, IEEE Transactions on Mobile Computing.

[7]  Carlo Fischione,et al.  Optimizing Client Association in 60 GHz Wireless Access Networks , 2013, ArXiv.

[8]  LiLi,et al.  Fairness and load balancing in wireless LANs using association control , 2007 .

[9]  Jan Karel Lenstra,et al.  Approximation algorithms for scheduling unrelated parallel machines , 1987, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).

[10]  Ashish Goel,et al.  Approximate majorization and fair online load balancing , 2001, TALG.

[11]  Seung-Jae Han,et al.  Fairness and Load Balancing in Wireless LANs Using Association Control , 2004, IEEE/ACM Transactions on Networking.

[12]  Giuseppe Caire,et al.  Optimal User-Cell Association for Massive MIMO Wireless Networks , 2014, IEEE Transactions on Wireless Communications.

[13]  Mung Chiang,et al.  RAT selection games in HetNets , 2013, 2013 Proceedings IEEE INFOCOM.

[14]  Yang Richard Yang,et al.  Proportional Fairness in Multi-Rate Wireless LANs , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[15]  Yoshihisa Kishiyama,et al.  A novel architecture for LTE-B :C-plane/U-plane split and Phantom Cell concept , 2012, 2012 IEEE Globecom Workshops.

[16]  Amos Fiat,et al.  On-line routing of virtual circuits with applications to load balancing and machine scheduling , 1997, JACM.

[17]  Seung-Jae Han,et al.  Cell Breathing Techniques for Load Balancing in Wireless LANs , 2006, IEEE Transactions on Mobile Computing.

[18]  Jan Karel Lenstra,et al.  Approximation algorithms for scheduling unrelated parallel machines , 1987, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).

[19]  Alec Wolman,et al.  Beacon-Stuffing: Wi-Fi without Associations , 2007 .

[20]  Jeffrey G. Andrews,et al.  An overview of load balancing in hetnets: old myths and open problems , 2013, IEEE Wireless Communications.