University of Southampton Research Repository

An ad hoc wireless LAN is a collection of wireless mobile nodes dynamically forming a temporary network without the use of any pre-existing network infrastructure or centralized administration. Due to its distributed nature, flexibility, robustness and ease of installation, ad hoc wireless LAN has greatly increased the scope for research in wireless communications. Since there is no defined structure, congestion control for systems where each ad hoc node can request certain bandwidth can pose the challenge of uncertain delay and instability and thus remains as a challenge in research. An ideal congestion control scheme for multi-hop ad hoc network would have to ensure that the bandwidth requests and input and output rates are regulated from chosen bridges and also from source and destination controllers. In this thesis, a novel congestion control scheme for multihop wireless LAN based on time-delay model is developed. The design of the proposed control model is derived from internal model control principles, with the control being done by the model reference controller and the error controller. Based on the congestion scenarios, the reference controller sets up a feasible reference value for the queue length, while the error controller feeds back rate-based compensation for the error between the reference and instantaneous queue lengths to combat against congestive disturbances. The proposed scheme makes use of Smith Predictor in the error controller to compensate for backward delay time, which is often referred to as “dead time” in control-engineering terms, to mitigate the stability problems that may occur. Underpinning the continuous-time model, a discretized and simplified digital-filter based solution is devised to make use of fast digital-filters available to date, without causing problem to scalability of the rate-based scheme and to propose a hardware based solution. The control objectives will be set with an aim to ensure full-link utilization and to achieve maximum rate recovery as soon as the congestion has been cleared under system stability. Simulations are performed to illustrate the performance of the controller under different congestion scenarios.