Congestion control algorithms for wireless networks are often designed based on a model of the wireless network and its corresponding network utility maximization (NUM) problem. The NUM problem is important to researchers and industry because the wireless medium is a scarce resource, and currently operating protocols such as 802.11 often result in extremely unfair allocation of data rates. The NUM approach offers a systematic framework to build rate control protocols that guarantee fair, optimal rates. However, classical models used with the NUM approach do not incorporate partial carrier sensing and interference, which can lead to significantly suboptimal performance when actually deployed. We quantify the potential performance loss of the classical controllers by developing a new model for wireless networks, called the first-principles model, that accounts for partial carrier sensing and interference. The first-principles model reduces to the classical models precisely when these partial effects are ignored. Because the classical models can only describe a subset of the topologies described by the first-principles model, the score for the first-principles model gives an upper bound on the performance of the others. This gives us a systematic tool to determine when the classical controllers perform well and when they do not. We construct several representative topologies and report numerical results on the scores obtained by each controller and the first-principles optimal score.



College and Department

Physical and Mathematical Sciences; Computer Science



Date Submitted


Document Type





BYU, thesis, wireless, network, optimization, model, interference, carrier sensing, random set