Abstract
MIMO systems are of interest to meet the expected demand for higher data rates and lower delays in future wireless systems. In addition, multi-carrier systems are of interest to combat frequency-selective fading experienced over the larger bandwidth these future broadband systems will use. The introduction of these spatial and frequency resources adds extra dimensions and complexity for any scheduling algorithm in a multiuser system. In this paper, we investigate scheduling through utility functions implemented via genetic algorithms in order to reduce complexity. This paper extends our prior work for a single-carrier MIMO system using dirty paper coding to the multi-carrier case. Here, the users that are scheduled, the order they are encoded in, and the subcarrier frequencies they are assigned to will all affect the performance of the scheduling algorithm. We demonstrate that the genetic algorithm is still able to achieve a similar near-optimal performance relative to an exhaustive search with the same relative reduction in complexity. Additionally, with the use of OFDM, an increase in capacity is seen relative to the single-carrier case.
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Elliott, R.C., Krzymień, W.A. (2007). Downlink Scheduling for Multiple Antenna Multi-Carrier Systems with Dirty Paper Coding Via Genetic Algorithms. In: Plass, S., Dammann, A., Kaiser, S., Fazel, K. (eds) Multi-Carrier Spread Spectrum 2007. Lecture Notes Electrical Engineering, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6129-5_5
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DOI: https://doi.org/10.1007/978-1-4020-6129-5_5
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