In this paper, we investigate single user throughput optimization in High Speed Downlink Packet Access (HSDPA). Specifically, we have a tendency to propose offline and online optimization algorithms that regulate the Channel Quality Indicator (CQI) used by the network for scheduling of information transmission. In the offline algorithm, a given target block error rate (BLER) is achieved by adjusting CQI based mostly on ACK/NAK history. By sweeping through different target BLERs, we tend to will find the throughput optimal BLER offline. This algorithm may be used not solely to optimize throughput but conjointly to enable truthful resource allocation among multiple users in HSDPA. In the online algorithm, the CQI offset is customized using an estimated short term throughput gradient while not the need for a target BLER. An adaptive stepsize mechanism is proposed to trace temporal variation of the setting. Convergence behavior of both algorithms is analyzed. The part of the analysis that deals with constant step size gradient algorithm could be applied to different stochastic optimization techniques. The convergence analysis is confirmed by our simulations. Simulation results also yield valuable insights on the value of optimal BLER target. Each offline and on-line algorithms are shown to yield up to 25p.c of throughput improvement over the conventional approach of targeting 10percent BLER.

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