MAC Centered Cooperation - Synergistic Design of Network Coding, Multi-Packet Reception, and Improved Fairness to Increase Network Throughput

We design a cross-layer approach to aid in develop- ing a cooperative solution using multi-packet reception (MPR), network coding (NC), and medium access (MAC). We construct a model for the behavior of the IEEE 802.11 MAC protocol and apply it to key small canonical topology components and their larger counterparts. The results obtained from this model match the available experimental results with fidelity. Using this model, we show that fairness allocation by the IEEE 802.11 MAC can significantly impede performance; hence, we devise a new MAC that not only substantially improves throughput, but provides fairness to flows of information rather than to nodes. We show that cooperation between NC, MPR, and our new MAC achieves super-additive gains of up to 6.3 times that of routing with the standard IEEE 802.11 MAC. Furthermore, we extend the model to analyze our MAC's asymptotic and throughput behaviors as the number of nodes increases or the MPR capability is limited to only a single node. Finally, we show that although network performance is reduced under substantial asymmetry or limited implementation of MPR to a central node, there are some important practical cases, even under these conditions, where MPR, NC, and their combination provide significant gains

Approaching Optimal Centralized Scheduling with CSMA-based Random Access over Fading Channels

Carrier Sense Multiple Access (CSMA) based distributed algorithms can attain the largest capacity region as the centralized Max-Weight policy does. Despite their capability of achieving throughput-optimality, these algorithms can either incur large delay and have large complexity or only operate over non-fading channels. In this letter, by assuming arbitrary back-off time we first propose a fully distributed randomized algorithm whose performance can be pushed to the performance of the centralized Max-Weight policy not only in terms of throughput but also in terms of delay for completely-connected interference networks with fading channels. Then, inspired by the proposed algorithm we introduce an implementable distributed algorithm for practical networks with a reservation scheme. We show that the proposed practical algorithm can still achieve the performance of the centralized Max-Weight policy.Comment: accepted to IEEE Communications Letter

Approaching Throughput-optimality in Distributed CSMA Scheduling Algorithms with Collisions

It was shown recently that CSMA (Carrier Sense Multiple Access)-like distributed algorithms can achieve the maximal throughput in wireless networks (and task processing networks) under certain assumptions. One important, but idealized assumption is that the sensing time is negligible, so that there is no collision. In this paper, we study more practical CSMA-based scheduling algorithms with collisions. First, we provide a Markov chain model and give an explicit throughput formula which takes into account the cost of collisions and overhead. The formula has a simple form since the Markov chain is "almost" time-reversible. Second, we propose transmission-length control algorithms to approach throughput optimality in this case. Sufficient conditions are given to ensure the convergence and stability of the proposed algorithms. Finally, we characterize the relationship between the CSMA parameters (such as the maximum packet lengths) and the achievable capacity region.Comment: To appear in IEEE/ACM Transactions on Networking. This is the longer versio

Decentralised Learning MACs for Collision-free Access in WLANs

By combining the features of CSMA and TDMA, fully decentralised WLAN MAC schemes have recently been proposed that converge to collision-free schedules. In this paper we describe a MAC with optimal long-run throughput that is almost decentralised. We then design two \changed{schemes} that are practically realisable, decentralised approximations of this optimal scheme and operate with different amounts of sensing information. We achieve this by (1) introducing learning algorithms that can substantially speed up convergence to collision free operation; (2) developing a decentralised schedule length adaptation scheme that provides long-run fair (uniform) access to the medium while maintaining collision-free access for arbitrary numbers of stations