TY - GEN

T1 - Scalable spectrum allocation for large networks based on sparse optimization

AU - Zhuang, Binnan

AU - Guo, Dongning

AU - Wei, Ermin

AU - Honig, Michael L.

N1 - Publisher Copyright:
© 2017 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

PY - 2017/8/9

Y1 - 2017/8/9

N2 - Joint allocation of spectrum and user association is considered for a large cellular network. The objective is to optimize a network utility function such as average delay given traffic statistics collected over a slow timescale. A key challenge is scalability: given n access points (APs), there are O(2n) ways in which the APs can share the spectrum. The number of variables is reduced from O(2n) to O(nk), where k is the number of users, by optimizing over local overlapping neighborhoods, defined by interference conditions, and by exploiting the existence of sparse solutions in which the spectrum is divided into k+1 segments. We reformulate the problem by optimizing the assignment of subsets of active APs to those segments. An ℓo constraint enforces a one-to-one mapping of subsets to spectrum segments, and an iterative (reweighted ℓ1) algorithm is used to find an approximate solution. Numerical results for a network with 100 APs serving several hundred users show the proposed method achieves a substantial increase in total throughput relative to benchmark schemes.

AB - Joint allocation of spectrum and user association is considered for a large cellular network. The objective is to optimize a network utility function such as average delay given traffic statistics collected over a slow timescale. A key challenge is scalability: given n access points (APs), there are O(2n) ways in which the APs can share the spectrum. The number of variables is reduced from O(2n) to O(nk), where k is the number of users, by optimizing over local overlapping neighborhoods, defined by interference conditions, and by exploiting the existence of sparse solutions in which the spectrum is divided into k+1 segments. We reformulate the problem by optimizing the assignment of subsets of active APs to those segments. An ℓo constraint enforces a one-to-one mapping of subsets to spectrum segments, and an iterative (reweighted ℓ1) algorithm is used to find an approximate solution. Numerical results for a network with 100 APs serving several hundred users show the proposed method achieves a substantial increase in total throughput relative to benchmark schemes.

UR - http://www.scopus.com/inward/record.url?scp=85027437829&partnerID=8YFLogxK

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U2 - 10.1109/ISIT.2017.8006983

DO - 10.1109/ISIT.2017.8006983

M3 - Conference contribution

AN - SCOPUS:85027437829

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 2518

EP - 2522

BT - 2017 IEEE International Symposium on Information Theory, ISIT 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Symposium on Information Theory, ISIT 2017

Y2 - 25 June 2017 through 30 June 2017

ER -