“CSMA-Based and Optimal link scheduling in Multihop MIMO Networks using SINR Model ”

The development of high-performance distributed scheduling algorithms for multi-hop wireless networks have become a matter of interest in recent years. The problem is challenging when studied under a physical interference model because it requires the SINR to be above a certain threshold at the receiver for decoding success. Under this SINR model, the transmission failure can be caused by interference due to simultaneous transmissions from far away nodes, which intensifies the difficulty in developing a distributed algorithm for link scheduling. In this paper, we are going to propose scheduling algorithm that uses carrier sensing and show that the algorithm is applicable to distributed implementation as well as it results in throughput optimality. This algorithm has a feature called the dual-state approach. It separates the transmission schedules from the system state means control state ans data state are separated hence can be shown to improve delay performance

“CSMA-Based Link Scheduling in Multihop MIMO Networks using SINR Model ”

The main aim of this study to resolve the problem of distributed scheduling in multi-hop MIMO networks. We will first develop a “MIMO pipe” model which will provide the required SINR , which gives the rate-reliability tradeoff in MIMO communications.Here we are going to study development of CSMA-based MIMO-pipe scheduling especially under the SINR model.We are going to choose the SINR model over the conventionally studied matching or protocol-based interference models because it has ability to capture the impact of interference in wireless networks. Here each node is equipped with an antenna array. In CSMA based scheduling, nodes will first sense the channel activity before attempting transmissions, whenever the channel is sensed to be idle, the nodes will continue with data transmissions. When the channel is detected to be busy, the nodes have to wait for a random amount of backoff time before reattempting the transmission.We will study that protocol model based throughput-optimal CSMA based scheduling, would not work well under the SINR model because its has dynamic and intrinsic link coupling. To tackle this challenge,CSMA-based MIMO-pipe scheduling is develpoed in both discrete-time system and continuous-time system

Wireless Network Stability in the SINR Model

We study the stability of wireless networks under stochastic arrival processes of packets, and design efficient, distributed algorithms that achieve stability in the SINR (Signal to Interference and Noise Ratio) interference model. Specifically, we make the following contributions. We give a distributed algorithm that achieves $\Omega(\frac{1}{\log^2 n})$-efficiency on all networks (where $n$ is the number of links in the network), for all length monotone, sub-linear power assignments. For the power control version of the problem, we give a distributed algorithm with $\Omega(\frac{1}{\log n(\log n + \log \log \Delta)})$-efficiency (where $\Delta$ is the length diversity of the link set).Comment: 10 pages, appeared in SIROCCO'1

Beyond Geometry : Towards Fully Realistic Wireless Models

Signal-strength models of wireless communications capture the gradual fading of signals and the additivity of interference. As such, they are closer to reality than other models. However, nearly all theoretic work in the SINR model depends on the assumption of smooth geometric decay, one that is true in free space but is far off in actual environments. The challenge is to model realistic environments, including walls, obstacles, reflections and anisotropic antennas, without making the models algorithmically impractical or analytically intractable. We present a simple solution that allows the modeling of arbitrary static situations by moving from geometry to arbitrary decay spaces. The complexity of a setting is captured by a metricity parameter Z that indicates how far the decay space is from satisfying the triangular inequality. All results that hold in the SINR model in general metrics carry over to decay spaces, with the resulting time complexity and approximation depending on Z in the same way that the original results depends on the path loss term alpha. For distributed algorithms, that to date have appeared to necessarily depend on the planarity, we indicate how they can be adapted to arbitrary decay spaces. Finally, we explore the dependence on Z in the approximability of core problems. In particular, we observe that the capacity maximization problem has exponential upper and lower bounds in terms of Z in general decay spaces. In Euclidean metrics and related growth-bounded decay spaces, the performance depends on the exact metricity definition, with a polynomial upper bound in terms of Z, but an exponential lower bound in terms of a variant parameter phi. On the plane, the upper bound result actually yields the first approximation of a capacity-type SINR problem that is subexponential in alpha

Wireless Scheduling with Power Control

We consider the scheduling of arbitrary wireless links in the physical model of interference to minimize the time for satisfying all requests. We study here the combined problem of scheduling and power control, where we seek both an assignment of power settings and a partition of the links so that each set satisfies the signal-to-interference-plus-noise (SINR) constraints. We give an algorithm that attains an approximation ratio of $O(\log n \cdot \log\log \Delta)$, where $n$ is the number of links and $\Delta$ is the ratio between the longest and the shortest link length. Under the natural assumption that lengths are represented in binary, this gives the first approximation ratio that is polylogarithmic in the size of the input. The algorithm has the desirable property of using an oblivious power assignment, where the power assigned to a sender depends only on the length of the link. We give evidence that this dependence on $\Delta$ is unavoidable, showing that any reasonably-behaving oblivious power assignment results in a $\Omega(\log\log \Delta)$-approximation. These results hold also for the (weighted) capacity problem of finding a maximum (weighted) subset of links that can be scheduled in a single time slot. In addition, we obtain improved approximation for a bidirectional variant of the scheduling problem, give partial answers to questions about the utility of graphs for modeling physical interference, and generalize the setting from the standard 2-dimensional Euclidean plane to doubling metrics. Finally, we explore the utility of graph models in capturing wireless interference.Comment: Revised full versio