In this paper we consider routing in random wireless-adhoc-networks (WANETs), where each node is equipped with a single antenna. Our analysis uses a proper model of the physical layer together with an abstraction of higher communication layers. We assume that the nodes are distributed according to a Poisson-point-process and consider routing schemes that select the next relay based on the geographical locations, the channel gains of its neighbor nodes and the statistical characterization of all other nodes. While many routing problems are formulated as optimization problems, the optimal distributed solution is rarely accessible. In this work, we present the exact optimal solution for the scenario analyzed. The optimal routing is given as a maximization of a routing metric which depends solely on the known partial channel state information (CSI) and includes an expectation with respect to the interference statistics. The optimal routing scheme is important because it gives an upper bound on the performance of any other routing scheme. We also present sub-optimal routing schemes that only use part of the available knowledge and require much lower computational complexity. Numerical results demonstrate that the performance of the low complexity schemes is close to optimal and outperforms other tested routing schemes.The authors are with the

In this paper we consider opportunistic routing in multiple-input-multiple-output (MIMO) random wireless ad-hoc networks (WANETs). Our analysis uses a proper model of the physical layer together with an abstraction of the higher communication layers. We assume that the nodes are distributed according to a Poisson-Point-Process and consider a routing scheme that opportunistically selects the next relay and the number of spatially multiplexed data streams. The routing decisions are based on geographic locations, the channel gains of the neighbor nodes and the statistical characterization of all other nodes. Unlike the single antenna case, the optimal routing scheme cannot be explicitly expressed. Hence, we propose a smart-routing scheme for MIMO that adapts the number of data streams per user to the channel conditions. Numerical results demonstrate that this scheme outperforms all previously published schemes for this scenario. The findings highlight the importance of channel state information for efficient routing, and the need for an adaptive selection of the number of data streams at each transmitter.

In this paper, we propose a novel distributed routing scheme in multihop wireless adhoc networks. We assume that the nodes are distributed according to a Poisson-Point-Process (PPP), and employ stochastic-geometric tools to derive a novel routing metric. The proposed Statistically-Optimal (SO) scheme, works in a decentralized manner in which the next relay selection exploits knowledge on the geographical location of each possible relay and on the instantaneous channel gain (fading diversity). The SO scheme maximizes the expected routing performance metric given the channel gains to the potential relays and their locations. Simulations results demonstrate that the SO scheme outperforms previously published schemes, and achieve performance which is close to the upper bound on ALOHA performance. Furthermore, the implementation of the suggested SO scheme is very simple, and the metric evaluation requires only minimal computations.

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