We are motivated by the need, in some applications, for impromptu or as-you-go deployment of wireless sensor networks. A person walks along a line, making link quality measurements with the previous relay at equally spaced locations, and deploys relays at some of these locations, so as to connect a sensor placed on the line with a sink at the start of the line. In this paper, we extend our earlier work on the problem (see [1]) to incorporate two new aspects: (i) inclusion of path outage in the deployment objective, and (ii) permitting the deployment agent to make measurements over several consecutive steps before selecting a placement location among them (which we call backtracking). We consider a light traffic regime, and formulate the problem as a Markov decision process. Placement algorithms are obtained for two cases: (i) the distance to the source is geometrically distributed with known mean, and (ii) the average cost per step case. We motivate the per-step cost function in terms of several known forwarding protocols for sleep-wake cycling wireless sensor networks. We obtain the structures of the optimal policies for the various formulations, and provide some sensitivity results about the policies and the optimal values. We then provide a numerical study of the algorithms, thus providing insights into the advantage of backtracking, and a comparison with simple heuristic placement policies.
[label=( * )] The framework of @cite_1 requires the link of each hop to have a certain outage probability. In practice, as the deployment agent walks away from the previously placed node, he can reach a point where even the maximum node power does not provide a link of the desired quality to the previous relay, and walking any farther is unlikely to provide a workable link. At this point the deployment is considered to have failed. In our present paper, we do not bound the outage probability of each hop but make the sum outage over all the hops a part of the optimization objective.
@cite_1
2952542244
This paper presents the evaluation of the multi-hop aggregate information efficiency of the slotted and unslotted ALOHA protocols. We consider a multi-hop wireless network where the nodes are spatially characterized by a Poisson point process and the traffic generation also follows a Poisson distribution. By applying the properties of stochastic geometry, we derive a closed-form lower bound on the outage probability as a function of the required communication rate, the single-hop distance, the number of hops and the maximum number of retransmissions. The results indicate that slotted ALOHA always outperforms its unslotted version, demonstrating the importance of synchronization in distributed networks. In addition, we show that it is always possible to optimize the network efficiency by properly setting the required rate for a given packet density. Finally, in the scenario considered, the use of retransmissions and multiple hops never achieves the best performance if compared to the option of single-hop links without retransmissions. We consider a frequency-flat fading multihop network with a single active source-destination pair terminals communicating over multiple hops through a set of intermediate relay terminals. We use Shannon-theoretic tools to analyze the tradeoff between energy efficiency and spectral efficiency (known as the power-bandwidth tradeoff) for a simple communication protocol based on time-division decode-and-forward relaying in meaningful asymptotic regimes of signal-to-noise ratio (SNR) under a system-wide power constraint on source and relay transmissions. The impact of multi-hopping and channel fading on the key performance measures of the high and low SNR regimes is investigated to shed new light on the possible enhancements in power bandwidth efficiency and link reliability. In contrast to the common belief that in fading environments communicating over multiple hops suffers significantly in performance due to the worst link limitation, our results indicate that hopping could significantly improve the outage behavior over slow-fading networks and stabilize links against the random channel fluctuations. In particular, we prove that there exists an optimal number of hops that minimizes the end-to-end outage probability and characterize the dependence of this optimal number on the fading statistics and target energy and spectral efficiencies. We study the problem of optimal sequential ("as-you-go") deployment of wireless relay nodes as a person walks along a line of random length (with a known distribution). The objective is to create an impromptu multihop wireless network for connecting a packet source to be placed at the end of the line with a sink node located at the starting point, to operate in the light traffic regime. As the deployment person walks along the line from the sink towards the source, at every step, he measures the channel quality to one (or more) previously placed relays, and places the relay nodes based on these measurements, so as to minimize either the sum power or the maximum power from the source to the sink node in the resultant network, subject to a constraint on the expected number of relays placed. For each of these two objectives, two different relay selection strategies are considered: (i) each relay communicates with the sink via its immediate previous relay, (ii) the communication path can skip some of the deployed relays. With appropriate modeling assumptions, we formulate each of these problems as a Markov decision process (MDP). We provide the optimal policy structures for all these cases, and provide illustrations, via numerical results, for some typical parameters. In this paper we consider a network where the nodes locations are modeled by a realization of a Poisson point process and remains fixed or changes very slowly over time. Most of the literature focuses on the spatial average of the link outage probabilities. But each link in the network has an associated link-outage probability that depends on the fading, path loss, and the relative locations of the interfering nodes. Since the node locations are random, the outage probability of each link is a random variable and in this paper we obtain its distribution, instead of just the spatial average. This work supplements the existing results which focus mainly on the average outage probability averaged over space. We propose a new notion of transmission capacity (TC) based on the outage distribution, and provide asymptotically tight bounds for the TC.