Title
What user-cell association algorithms will perform best in mmWave massive MIMO ultra-dense HetNets?
Abstract
With increasing cell density and the heterogeneity in the network, optimal user-cell association which is a well known open problem, will become an even more challenging issue. Contrary to the current studies that address user-cell association problem for convectional HetNets with massive MIMO deployments in HF (high frequencies) ranges, in this paper we investigate user-cell association problem for dense two-tier networks with massive MIMO deployment both at macro and femto-tier operating in HF and mmWave spectrum, respectively. We evaluate the performance of four user-cell association algorithms for massive MIMO deployment in a two-tier network under two different deployment scenarios: 1) HF-HF (both tiers operating in HF band); 2) HF-mmWave (MBSs operating in HF while FBSs in mmWave bands. To this end, we model the association problem in form of a convex network utility maximization problem as a function of the downlink user throughput. Contrary to the existing load aware association schemes that preclude the effect of bandwidth disparity in HF and mmWave bands, we propose a modified utility function that takes into account the effect of large bandwidth at mmWave bands. The problem is solvable through centralized as well as distributed or user centric load aware user association schemes.
Year
DOI
Venue
2017
10.1109/PIMRC.2017.8292248
2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)
Keywords
Field
DocType
Massive MIMO,mmWave network,HetNet,user-association schemes,load balancing,proportional fairness
Association scheme,Open problem,Computer science,Load balancing (computing),MIMO,Computer network,Algorithm,Bandwidth (signal processing),Throughput,Heterogeneous network,Telecommunications link
Conference
ISBN
Citations 
PageRank 
978-1-5386-3532-2
1
0.35
References 
Authors
16
3
Name
Order
Citations
PageRank
Sinasi Cetinkaya110.35
Umair Sajid Hashmi242.09
Ali Imran338240.89