In a wireless mesh network (WMN) with a number of stationary wireless routers, the aggregate capacity can be increased when each router is equipped with multiple network interface cards (NICs) and each NIC is assigned to a distinct orthogonal frequency channel. In this paper, given the logical topology of the network, we mathematically formulate a crosslayer fair bandwidth sharing problem as a non-linear mixedinteger network utility maximization problem. An optimal joint design, based on exact binary linearization techniques, is proposed which leads to a global maximum. A near-optimal joint design, based on approximate dual decomposition techniques, is also proposed which is practical for deployment. Performance is assessed through several numerical examples in terms of network utility, aggregate network throughput, and fairness index. Results show that our proposed designs can lead to multi-channel WMNs which are more efficient and fair compared to their singlechannel counterparts. The performance gain on both efficiency and fairness increase as the number of available NICs per router or the number of available frequency channels increases.

Abstract — The performance of conventional gateway access optimization techniques deteriorate dramatically when traffic load is dynamic. In this article, we propose a novel gateway access algorithm called ‘Cog Gap’, which is a cognitive method and is designed for Wireless Mesh Networks to maximize the network utilization. The proposed Cog Gap utilizes a destination-hub access model, where multiple gateway nodes are connected by wired links, and packets from a source node can be sent from any connected gateway nodes to increase transmission opportunities. In Cog Gap, we use the Hidden Markov Model (HMM) and the expectation maximization method to handle uncertain traffic pattern and the loss of probing results. A traffic allocation algorithm is then proposed to optimize dynamic multi-gateway access. By modeling the route state determination and transition, we transform the opportunistic gateway access problem into a Markov decision process (MDP) problem. A heuristic and adaptive algorithm named hindsight optimal is used in solving MDP. Simulation results have proven that the proposed Cog Gap algorithm can make full use of the transmission opportunities and does not incur noticeable protocol overhead.

Abstract — In highly dynamic wireless mesh networks, channel quality variations will affect network performance seriously. Channel assignment and scheduling algorithms have been applied in wireless mesh networks (WMN), so as to maximize network resource utilization. However, existing seminar works are mainly focusing on given set of channel quality values, which have not considered the channel quality variations in time scale. With highly dynamic channel quality, scheduling algorithm might possibly executed time to time, which will eventually deteriorate network performance. In this paper, we propose a stochastic programming model in order to reduce highly dynamic scheduling overhead and improve network utilization in heterogeneous wireless mesh networks. Since it has been proved that, achieving the optimal result is NP-hard. A heuristic solution with two-stage maximum rematching algorithm is proposed, and simulation results show that, our two-stage dynamic scheduling algorithm is efficient as channels in network are highly dynamic on communication quality. I.

Abstract — Nowadays wireless mesh routers are facilitating with more wireless channels than ever because of the advanced wireless communication technologies such as OFDM, SDR and CR(cognitive radio). With multi-radio and multichannel communication capability, spectrum heterogeneity are widely existing in multi-radio wireless systems, such that network performances usually suffer from channel bandwidth and transmission power discrepancy. Many seminar works having been proposed are generally focusing on throughput maximization in a given network configuration, which would suffer from highly dynamic network topology and variable spectrum conditions. In this paper, we prove that, heterogeneity in wireless network would lead to resource constrained regions, and unfair wireless resource allocation would deteriorate throughput on some links. In this paper, we propose a fair

This paper considers the problem of minimizing outage probabilities in the downlink of a multiuser, multicell OFDMA cellular network with frequency selective fading, imperfect channel state information and frequency hopping. The task is to determine the allocation of powers and subcarriers for users to ensure that the user outage probabilities are as low as possible. We formulate a min-max outage probability problem and solve it under the constraint that the transmit power spectrum at each base station is flat. In particular, we obtain a subchannel allocation algorithm that has complexity O(L log L) in L, the number of users in the cell. We also consider suboptimal but implementable approaches with and without the flat transmit power spectrum constraint. We conclude that the flat transmit spectrum approach has merit, and warrants further study. Index Terms Cellular network, resource allocation, power control, orthogonal frequency division multiple access (OFDMA), subcarrier allocation, power spectrum, fading channels, outage capacity, fast frequency hopping, interference averaging. I.

Abstract In highly dynamic and heterogeneous wireless mesh networks (WMN), link quality will seriously affect network performance. Two challenges hinder us from achieving a highly efficient WMN. One is the channel dynamics. As in real network deployment, channel qualities are changing over time, which would seriously affect network bandwidth and reliability. Existing works are limited to the assumption that link quality values are fixed, and optimal scheduling algorithms are working on the fixed values, which would inevitably suffer from the link quality dynamics. Another challenge is the channel diversity. In single channel wireless networks, channel assignment and scheduling are NP-hard. And in multichannel wireless networks, it could be even harder for higher throughput and efficient scheduling. In this study, we firstly characterize the stochastic behavior on wireless communications in a Markov process, which is based on statistical methodology. Secondly, on exploiting the stochastic behavior on wireless channels, we propose a stochastic programming model in achieving maximized network utilization. Considering the NP-hardness, we propose a heuristic solution for it. The key idea in the proposed algorithm is a two-stage matching process named “Rematch. ” Indeed, our solution to the stochastic network scheduling is a cross-layer approach. Also, we have proved that it is 2-approximate to the optimal result. Moreover, extensive simulations have been done, showing the efficiency of “Rematch ” in highly dynamic and distributed wireless mesh networks.

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