Building an Adaptive Multimedia System using the Utility Model
Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
Joint resource allocation and base-station assignment for the downlink in CDMA networks
IEEE/ACM Transactions on Networking (TON)
Multiuser adaptive subcarrier-and-bit allocation with adaptive cell selection for OFDM systems
IEEE Transactions on Wireless Communications
IEEE Transactions on Wireless Communications
Downlink Radio Resource Allocation for Multi-Cell OFDMA System
IEEE Transactions on Wireless Communications
Utility-based radio resource allocation for QoS traffic in wireless networks
IEEE Transactions on Wireless Communications
Pricing and power control in a multicell wireless data network
IEEE Journal on Selected Areas in Communications
Transmit power adaptation for multiuser OFDM systems
IEEE Journal on Selected Areas in Communications
A framework for uplink power control in cellular radio systems
IEEE Journal on Selected Areas in Communications
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Existing base station (BS) assignment methods in cellular networks are mainly driven by radio criteria since it is assumed that the only limiting resource factor is on the air interface. However, as enhanced air interfaces have been deployed, and mobile data and multimedia traffic increases, a growing concern is that the backhaul of the cellular network can become the bottleneck in certain deployment scenarios. In this paper, we extend the BS assignment problem to cope with possible backhaul congestion situations. A backhaul-aware BS assignment problem is modeled as an optimization problem using a utility-based framework, imposing constraints on both radio and backhaul resources, and mapped into a Multiple-Choice Multidimensional Knapsack Problem (MMKP). A novel heuristic BS assignment algorithm with polynomial time is formulated, evaluated and compared to classical schemes based exclusively on radio conditions. Simulation results demonstrate that the proposed algorithm can provide the same system capacity with less backhaul resources so that, under backhaul bottleneck situations, a better overall network performance is effectively achieved.