Predictive resource allocation for multicast OFDM systems
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We consider a multicast resource allocation problem for the downlink in OFDM-based wireless cellular network systems. In a conventional multicast system, to accommodate users with bad channel conditions, the transmission is based on the worst case user. We show that such a multicast system saturates the capacity when the number of users increases in fading environments. We exploit the multicarrier nature of OFDM and advances in coding techniques such as MDC (multiple description coding), in which arbitrary combinations of layers can be decoded at the receiver. Different MDC layers are carried over different subcarriers and users with good channels receive data from more subcarriers than users with poor channel conditions. We present an optimal subcarrier/bit allocation method requiring full search of possible candidates. To reduce the complexity, we propose a two-step suboptimum algorithm by separating subcarrier allocation and bit loading. Numerical results show that the proposed heuristics significantly outperform the conventional multicast transmission scheme. The difference between optimum and heuristic solutions is less than 5%.