TY - GEN
T1 - Iterative water-filling for load-balancing in wireless LAN or microcellular networks
AU - Chen, Jeremy K.
AU - Rappaport, Theodore S.
AU - De Veciana, Gustavo
PY - 2006
Y1 - 2006
N2 - This paper presents an efficient iterative load-balancing algorithm for time and bandwidth allocation among access points (APs) and users subject to heterogeneous fairness and application requirements. The algorithm can be carried out either at a central network switch with site-specific propagation predictions, or in a decentralized manner. The algorithm converges to maximum network resource utilization from any starting point, and usually converges in 3 to 9 iterations in various network conditions including users joining, leaving, and moving within a network and various network sizes. Such a fast convergence allows real-time implementations of our algorithm. Simulation results show that our algorithm has merits over other schemes especially when users exhibit clustered patterns: Our algorithm, when assuming multiple radios at each user, achieves 48% gain of median throughput as compared with the max-min fair load-balancing scheme (also with the multi-radio assumption) while losing 14% of fairness index; we also achieve 26% gain of median throughput and 52% gain of fairness index over the Strongest-Signal-First scheme (which assumes each user has only a single radio). When only a single radio is used, our algorithm is similar to the max-min fairness scheme, and is still better than SSF with 44% gain of 25-percentile throughput and 37% gain of fairness index.
AB - This paper presents an efficient iterative load-balancing algorithm for time and bandwidth allocation among access points (APs) and users subject to heterogeneous fairness and application requirements. The algorithm can be carried out either at a central network switch with site-specific propagation predictions, or in a decentralized manner. The algorithm converges to maximum network resource utilization from any starting point, and usually converges in 3 to 9 iterations in various network conditions including users joining, leaving, and moving within a network and various network sizes. Such a fast convergence allows real-time implementations of our algorithm. Simulation results show that our algorithm has merits over other schemes especially when users exhibit clustered patterns: Our algorithm, when assuming multiple radios at each user, achieves 48% gain of median throughput as compared with the max-min fair load-balancing scheme (also with the multi-radio assumption) while losing 14% of fairness index; we also achieve 26% gain of median throughput and 52% gain of fairness index over the Strongest-Signal-First scheme (which assumes each user has only a single radio). When only a single radio is used, our algorithm is similar to the max-min fairness scheme, and is still better than SSF with 44% gain of 25-percentile throughput and 37% gain of fairness index.
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U2 - 10.1109/vetecs.2006.1682787
DO - 10.1109/vetecs.2006.1682787
M3 - Conference contribution
AN - SCOPUS:34047149299
SN - 0780393929
SN - 9780780393929
T3 - IEEE Vehicular Technology Conference
SP - 117
EP - 121
BT - 2006 IEEE 63rd Vehicular Technology Conference, VTC 2006-Spring - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2006 IEEE 63rd Vehicular Technology Conference, VTC 2006-Spring
Y2 - 7 May 2006 through 10 July 2006
ER -