Achievable rates are derived for reliable communication in networks with multi-access interference. Capacity is established for some such networks. A network flow formulation is developed that includes rate gains and losses caused by correlating the multi-access channel inputs.
Abstract-We consider a wireless multi-hop network and design an algorithm for jointly optimal scheduling of packet transmissions and network coding. We consider network coding across different users, however with the restriction that packets have to be decoded after one hop. We compute the stability region of this scheme and propose an online algorithm that stabilizes every arrival rate vector within the stability region. The online algorithm requires computation of stable sets in an appropriately defined conflict graph. We show by means of simulations that this inherently hard problem is tractable for some instances and that network coding extends the stability region over routing and leads, on average, to a smaller backlog.
Abstract-Consider network coded multicast traffic over a wireless network in the bandwidth limited regime. We formulate the joint medium access and subgraph optimization problem by means of a graphical conflict model. The nature of network coded flows is not captured by classical link-based scheduling and therefore requires a novel approach based on conflicting hyperarcs. By means of simulations, we evaluate the performance of our algorithm and conclude that it significantly outperforms existing scheduling techniques.
I. INTRODUCTIONIn a multi-hop wireless network an optimal strategy to multicast to a group of receivers is to use random linear network coding over an optimized subgraph. Random linear codes are capacity achieving for a given subgraph [1] and this subgraph can be computed by means of solving a linear or convex program [2]. The subgraph optimization is a fairly tractable problem and furthermore solvable in a distributed fashion making it relevant in practice. An essential assumption of [2] is that all nodes in the network transmit on orthogonal channels and thus conflicts due to interfering transmissions do not arise. This is a reasonable assumption in a power limited regime, where bandwidth is not scarce and one might simply avoid interference by orthogonalizing the entire network. However, in many if not most scenarios wireless networks are interference limited. To that end a high frequency reuse within the network is necessary which has to be achieved by carefully scheduling simultaneous transmissions.The prevalent approach to this problem is to construct an interference-free transmission schedule by means of some heuristic and then to compute an optimal subgraph over this, now essentially orthogonal, network. As an example, in [3] the authors propose a suboptimal collision-free strategy where two nodes cannot transmit simultaneously if they are within two hops. While this is a practical solution, it is not clear how it affects the overall performance of the network. Furthermore, from a systems perspective it is unsatisfying to have one component (the network coding subgraph) carefully optimized, while the other essential part (the medium access) is done in a more or less ad-hoc fashion.To that end, we suggest a framework, where subgraph optimization and channel access are treated jointly. We construct
Whereas the theory and application of optimal network coding are well studied for the single-session multicast scenario, there is no known optimal network coding strategy for a more general connection problem where there are more than one session and receivers may demand different sets of information. Though there have been a number of recent studies that demonstrate various utilities of network coding in the multisession scenario, they rely on very restricted classes of codes in terms of the coding operations allowed and/or the location of decoding. In this paper, we propose a novel inter-session network coding strategy for a general connection problem. Our coding strategy allows fairly general random linear coding over a large finite field, in which decoding is done at receivers and the mixture of information at interior nodes is controlled by evolutionary mechanisms. We demonstrate how our coding strategy may surpass existing end-to-end pairwise XOR coding schemes in terms of effectiveness and practicality.
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