Relay Selection Strategies for Multi-hop Cooperative Networks

In this dissertation we consider several relay selection strategies for multi-hop cooperative networks. The relay selection strategies we propose do not require a central controller (CC). Instead, the relay selection is on a hop-by-hop basis. As such, these strategies can be implemented in a distributed manner. Therefore, increasing the number of hops in the network would not increase the complexity or time consumed for the relay selection procedure of each hop. We first investigate the performance of a hop-by-hop relay selection strategy for multi-hop decode-and-forward (DF) cooperative networks. In each relay cluster, relays that successfully receive and decode the message from the previous hop form a decoding set for relaying, and the relay which has the highest signal-to-noise ratio (SNR) link to the next hop is then selected for retransmission. We analyze the performance of this method in terms of end-to-end outage probability, and we derive approximations for the ergodic capacity and the effective ergodic capacity of this strategy. Next we propose a novel hop-by-hop relay selection strategy where the relay in the decoding set with the largest number of ``good\u27\u27 channels to the next stage is selected for retransmission. We analyze the performance of this method in terms of end-to-end outage probability in the case of perfect and imperfect channel state information (CSI). We also investigate relay selection strategies in underlay spectrum sharing cognitive relay networks. We consider a two-hop DF cognitive relay network with a constraint on the interference to the primary user. The outage probability of the secondary user and the interference probability at the primary user are analyzed under imperfect CSI scenario. Finally we introduce a hop-by-hop relay selection strategy for underlay spectrum sharing multi-hop relay networks. Relay selection in each stage is only based on the CSI in that hop. It is shown that in terms of outage probability, the performance of this method is nearly optimal

Jointly Optimal Channel Pairing and Power Allocation for Multichannel Multihop Relaying

We study the problem of channel pairing and power allocation in a multichannel multihop relay network to enhance the end-to-end data rate. Both amplify-and-forward (AF) and decode-and-forward (DF) relaying strategies are considered. Given fixed power allocation to the channels, we show that channel pairing over multiple hops can be decomposed into independent pairing problems at each relay, and a sorted-SNR channel pairing strategy is sum-rate optimal, where each relay pairs its incoming and outgoing channels by their SNR order. For the joint optimization of channel pairing and power allocation under both total and individual power constraints, we show that the problem can be decoupled into two subproblems solved separately. This separation principle is established by observing the equivalence between sorting SNRs and sorting channel gains in the jointly optimal solution. It significantly reduces the computational complexity in finding the jointly optimal solution. It follows that the channel pairing problem in joint optimization can be again decomposed into independent pairing problems at each relay based on sorted channel gains. The solution for optimizing power allocation for DF relaying is also provided, as well as an asymptotically optimal solution for AF relaying. Numerical results are provided to demonstrate substantial performance gain of the jointly optimal solution over some suboptimal alternatives. It is also observed that more gain is obtained from optimal channel pairing than optimal power allocation through judiciously exploiting the variation among multiple channels. Impact of the variation of channel gain, the number of channels, and the number of hops on the performance gain is also studied through numerical examples.Comment: 15 pages. IEEE Transactions on Signal Processin

Reliable multi-hop routing with cooperative transmissions in energy-constrained networks

We present a novel approach in characterizing the optimal reliable multi-hop virtual multiple-input single-output (vMISO) routing in ad hoc networks. Under a high node density regime, we determine the optimal cardinality of the cooperation sets at each hop on a path minimizing the total energy cost per transmitted bit. Optimal cooperating set cardinality curves are derived, and they can be used to determine the optimal routing strategy based on the required reliability, transmission power, and path loss coefficient. We design a new greedy geographical routing algorithm suitable for vMISO transmissions, and demonstrate the applicability of our results for more general networks

Jointly Optimal Channel Pairing and Power Allocation for Multichannel Multihop Relaying

We study the problem of channel pairing and power allocation in a multichannel multihop relay network to enhance the end-to-end data rate. Both amplify-and-forward (AF) and decode-and-forward (DF) relaying strategies are considered. Given fixed power allocation to the channels, we show that channel pairing over multiple hops can be decomposed into independent pairing problems at each relay, and a sorted-SNR channel pairing strategy is sum-rate optimal, where each relay pairs its incoming and outgoing channels by their SNR order. For the joint optimization of channel pairing and power allocation under both total and individual power constraints, we show that the problem can be decoupled into two subproblems solved separately. This separation principle is established by observing the equivalence between sorting SNRs and sorting channel gains in the jointly optimal solution. It significantly reduces the computational complexity in finding the jointly optimal solution. It follows that the channel pairing problem in joint optimization can be again decomposed into independent pairing problems at each relay based on sorted channel gains. The solution for optimizing power allocation for DF relaying is also provided, as well as an asymptotically optimal solution for AF relaying. Numerical results are provided to demonstrate substantial performance gain of the jointly optimal solution over some suboptimal alternatives. It is also observed that more gain is obtained from optimal channel pairing than optimal power allocation through judiciously exploiting the variation among multiple channels. Impact of the variation of channel gain, the number of channels, and the number of hops on the performance gain is also studied through numerical examples.Comment: 15 pages. IEEE Transactions on Signal Processin

Energy-delay bounds analysis in wireless multi-hop networks with unreliable radio links

Energy efficiency and transmission delay are very important parameters for wireless multi-hop networks. Previous works that study energy efficiency and delay are based on the assumption of reliable links. However, the unreliability of the channel is inevitable in wireless multi-hop networks. This paper investigates the trade-off between the energy consumption and the end-to-end delay of multi-hop communications in a wireless network using an unreliable link model. It provides a closed form expression of the lower bound on the energy-delay trade-off for different channel models (AWGN, Raleigh flat fading and Nakagami block-fading) in a linear network. These analytical results are also verified in 2-dimensional Poisson networks using simulations. The main contribution of this work is the use of a probabilistic link model to define the energy efficiency of the system and capture the energy-delay trade-offs. Hence, it provides a more realistic lower bound on both the energy efficiency and the energy-delay trade-off since it does not restrict the study to the set of perfect links as proposed in earlier works

On the problem of energy efficiency of multi-hop vs one-hop routing in wireless sensor networks

The hop distance strategy in wireless sensor networks (WSNs) has a major impact on energy consumption of each sensor mote. Long-hop routing minimizes reception cost. However, a substantial power demand is incurred for long distance transmission. Since the transceiver is the major source of power consumption in the node, optimizing the routing for hop length can extend significantly the lifetime of the network. This paper explores when multi-hop routing is more energy efficient than direct transmission to the sink and the conditions for which the two-hop strategy is optimal. Experimental evidence is provided in to support of these conclusions. The tests showed that the superiority of the multi-hop scheme depends on the source-sink distance and reception cost. They also demonstrated that the two- hop strategy is most energy efficient when the relay is at the midpoint of the total transmission radius. Our results may be used in existing routing protocols to select optimal relays or to determine whether it is better to send packets directly to the base station or through intermediate nodes

Multi-hop Diffusion LMS for Energy-constrained Distributed Estimation

We propose a multi-hop diffusion strategy for a sensor network to perform distributed least mean-squares (LMS) estimation under local and network-wide energy constraints. At each iteration of the strategy, each node can combine intermediate parameter estimates from nodes other than its physical neighbors via a multi-hop relay path. We propose a rule to select combination weights for the multi-hop neighbors, which can balance between the transient and the steady-state network mean-square deviations (MSDs). We study two classes of networks: simple networks with a unique transmission path from one node to another, and arbitrary networks utilizing diffusion consultations over at most two hops. We propose a method to optimize each node's information neighborhood subject to local energy budgets and a network-wide energy budget for each diffusion iteration. This optimization requires the network topology, and the noise and data variance profiles of each node, and is performed offline before the diffusion process. In addition, we develop a fully distributed and adaptive algorithm that approximately optimizes the information neighborhood of each node with only local energy budget constraints in the case where diffusion consultations are performed over at most a predefined number of hops. Numerical results suggest that our proposed multi-hop diffusion strategy achieves the same steady-state MSD as the existing one-hop adapt-then-combine diffusion algorithm but with a lower energy budget.Comment: 14 pages, 12 figures. Submitted for publicatio