Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Publication date | 2004 |
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Host publication | Advances in Wired and Wireless Communication, 2004 IEEE/Sarnoff Symposium on |
Place of Publication | New York |
Publisher | IEEE |
Pages | 179-183 |
Number of pages | 5 |
ISBN (print) | 0780382196 |
<mark>Original language</mark> | English |
Event | IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication - Princeton, United Kingdom Duration: 26/04/2004 → 27/04/2004 |
Conference | IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication |
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Country/Territory | United Kingdom |
Period | 26/04/04 → 27/04/04 |
Conference | IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication |
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Country/Territory | United Kingdom |
Period | 26/04/04 → 27/04/04 |
A novel framework to model the problem of downlink resource allocation in heterogeneous CDMA cellular networks is presented which leads to utilizing the network resources in more efficient way. First, to manage fundamental coverage-capacity tradeoff for the downlink, we propose the notion of effective area to develop a Base Station (BS) Pilot Power Adjustment (PPA) scheme. Using effective area, PPA periodically adjusts BS pilot power based on both traffic load and coverage area. After adjusting the pilot powers, we use the dynamic pricing platform to formulate downlink resource allocation based on a novel defined utility function. This utility function quantifies the degree of utilization of resources. As a matter of fact, using the defined utility function, we track users' channel fluctuations and their delay constraints along with the load conditions of all BSs. Unlike previous work, we solve the problem with the general objective of maximizing the total network utility instead of achieved utility of each BS. It is shown that this problem is equivalent to finding the optimum BS assignment throughout the network which is mapped to a Multi-dimensional Multiple-choice Knapsack Problem (MMKP). Since MMKP is NP-Hard, a polynomial-time suboptimal algorithm is then modified to develop an efficient base station assignment.