Measurement Based Self-Optimization in Random Access Communications

Details Measurement Based Self-Optimization in Random Access Communications Measurement Based Self-Optimization in Random Access Communications

2011-07-06

arxiv.org/abs/1107.1158v1

Computer Science

Networking and Internet Architecture

30 pages, 10 figures, submitted to the IEEE Trans. on Wireless Communications

Scientific paper

This work considers a single-cell random access channel in cellular wireless networks and provides an algorithmic approach to the problem of optimal coordination of user actions. In the scenario considered, an access effort is successful if (a) the signal is detected at the receiver and (b) no collision occurs. The first event is controlled by the user transmission power while the second one by the choice of access (back-off) probability. These constitute the user action pair. The algorithm aims at exploiting information from measurements and user reports, in order to estimate current values of the system situation. Based on these estimates, two optimization problems can be formulated and solved for the so called contention level and transmission power level at the base station side. The methodology to find the optimal values is based on minimization of a drift function. The two values are broadcast in order to help the users update their actions ``almost optimally``. In this way the wireless cell can achieve self-optimization, without external coordination, by relying on such intelligent information exchange and parameter estimation. Numerical results illustrate the great benefits of the proposed algorithm, compared to scenarios where the actions remain fixed, at a very low or even zero cost in power expenditure and delay.

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