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Resource allocation based on channel distribution information for elastic and streaming traffic in OFDMA networks: a heuristic algorithm

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Publication date2009
Host publicationVehicular Technology Conference Fall (VTC 2009-Fall), 2009 IEEE 70th
Place of PublicationNew York
PublisherIEEE
Pages813-817
Number of pages5
ISBN (Electronic)9781424425150
ISBN (Print)9781424425143
Original languageEnglish
Event70th IEEE Vehicular Technology Conference - Anchorage, United Kingdom
Duration: 20/09/200923/09/2009

Conference

Conference70th IEEE Vehicular Technology Conference
CountryUnited Kingdom
Period20/09/0923/09/09

Publication series

NameIEEE VTS Vehicular Technology Conference Proceedings
PublisherIEEE
ISSN (Print)1090-3038

Conference

Conference70th IEEE Vehicular Technology Conference
CountryUnited Kingdom
Period20/09/0923/09/09

Abstract

In this paper, we propose a low complexity heuristic algorithm for radio resource allocation in Orthogonal Frequency Division Multiple Access (OFDMA) systems based on subcarrier channel distribution information (CDI). We consider practical rate adaptation in which rate is adapted using a predefined set of modulation levels, which is in contrast to previous works that consider continuous rate. We formulate the problem of resource allocation in an OFDMA system with streaming traffic which requires a minimum guaranteed average rate, and elastic traffic with flexible rate requirements. The main objective is to maximize the total transmission rate of the elastic users, while average rate guarantees for streaming traffic as well as maximum transmission power constraints are satisfied. To reduce the computational complexity, we decouple the resource allocation problem into two sub-problems corresponding to two traffic types. For streaming traffic, we optimally allocate subcarrier and power and then the remaining radio resources including the unassigned subcarriers and unallocated transmission power of the base station are optimally allocated to the elastic traffic. We then develop a heuristic algorithm based on Lagrangian method to obtain an approximation of the optimal solution. Using simulations, we study the impact of number of fading regions. Simulations also provides insight on the trade-off between the number of streaming and elastic users.