Minimizing the probability of collision in wireless sensor networks using cooperative diversity and optimal power allocation

It is well known that traditional water-filling provides a closed form solution for capacity maximization in orthogonal frequency division multiplex (OFDM) system. In this paper, cooperative power allocation is investigated in a two-transmitter multi-receiver model for OFDM systems. The local full channel state information (CSI) is available at the two transmitters respectively, where each transmitter has an individual power constrain. The transmitters first cooperate by sharing CSI, and then jointly optimize power allocation in the metric of sum throughput, which can be modeled as a convex optimization problem. Through an application of Karush-KuhnTucker (KKT) conditions, the convex optimization problem is reformulated as a simplified convex one. Then the closed form solution is derived, which takes a form similar to classic waterfilling principle. Based on the solution, the optimal cooperative power allocation algorithm is constructed, the structure of which can be explained as a cooperative water-filling relative to the traditional water-filling. Finally, numerical simulation is given to evaluate and demonstrate the performance of the optimal cooperative water-filling scheme.

Energy efficient communication is a key requirement of energy-constrained wireless sensor networks. Cooperative diversity can be applied to wireless sensor networks to significantly reduce node energy consumption. However, judicious selection and coordination of cooperation partners is essential to exploiting this energy saving potential of cooperation. In this paper we investigate optimal partner choice and power allocation for energy efficient cooperation in wireless sensor networks. Our insights lead us to formulate power allocation and partner choice heuristics which form a simple and practical cooperation strategy for energy-constrained wireless sensor networks, allowing nodes to autonomously make near-optimal cooperation decisions. We show that the power allocation optimisation problem is non-linear, necessitating the use of a search to find the optimum solution. We present the resulting cooperative energy savings in terms of network geometry for a range of potential partner locations. Our results reveal that the partner-destination and the source-partner channels have roughly equal influence over cooperation decisions for optimal energy efficiency. We use this observation to devise a simple yet near-optimal power allocation heuristic.

Recent research has shown that the cooperative diversity can efficiently combat the fading effects caused by the hostile wireless channels just as the multiple-input multiple-output (MIMO) antenna systems do. Besides, due to the inherent cost and size constraints by many small area wireless networks, e.g. wireless ad hoc networks and wireless sensor networks, in such environments, it would be almost impossible to deploy the antenna array in a mobile node. However, cooperative diversity can provide an economical and viable solution by sharing each mobile node’s single-antenna with others to form a virtual antenna array, while it still can maintain significant performance gains similar to MIMO systems. Meanwhile, the adaptive modulation is a proven technique which can significantly increase the spectral efficiency when perfect channel estimation can be achieved, and many wireless standards have adopted it as an implementation option. It also has been shown that combining these two techniques can greatly raise the system efficiency. Nevertheless, in the multiple nodes cooperative communication networks, the randomness of demodulation process at each relay node makes the task of correctly selecting the forwarding relay nodes very complicated. In view of this problem, a novel adaptive node selection algorithm is proposed for the destination node to effectively select the forwarding relay nodes to help the source node transfer the signals. In this paper, the decode-and-forward (DF) protocol is employed as the cooperative diversity signaling, and the constant-power variable-rate M-ary phase shift keying (M-PSK) is adopted as the adaptive modulation scheme. At the destination node, the maximal-ratio-combining (MRC) method is used to combine all of the signals from diversity branches with the main path transmitted directly from the source node. Because of the random phenomenon of the demodulation process, the outage requirement is used as the baseline in the first stage of the proposed node selection algorithm to choose the maximal transmission rate. Hence the maximal overall system throughput in terms of rate can be achieved. In the meantime, the first candidate forwarding sets of the relay nodes which collectively meet the required outage probability are also been chosen. Then in the second stage, we can further refine the number of the relay nodes among the first candidate forwarding sets by using the following criterion — maximum average rate per node. It will screen out the first candidate sets with the minimum number of the relay nodes. If only one candidate set is left at the end of the second stage, it will be the end of the proposed algorithm. However, if the result of the screening still has more than one set, then the final election among the second candidate sets would be the one which can give the minimum outage probability. In the simulation results, our proposed node selection algorithm can even further improve the spectral efficiency while the deleteriously fading effect induced by the wireless channels can also be effectively removed.

Various communication services have been provided. They include environmental monitoring and/or control, ad-hoc communication between mobile nodes, and inter-vehicle communication in intelligent transport systems. As a means of facilitating the above advanced communication services, autonomous decentralized networks, such as wireless sensor networks (Akyildiz et al., 2002; Rajagopalan & Varshney, 2006), mobile ad-hoc networks (Perkins & Royer, 1999; Johnson et al., 2003; Clausen & Jaquet, 2003; Ogier et al., 2003), and wireless mesh networks (Yamamoto et al., 2009), have been intensively researched with great interests. Especially, a wireless sensor network, which is a key network to construct ubiquitous information environments, has great potential as a means of realizing a wide range of applications, such as natural environmental monitoring, environmental control in residential spaces or plants, object tracking, and precision agriculture (Akyildiz et al., 2002). Recently, there is growing expectation for a new network service by a wireless sensor network consisting of a lot of static sensor nodes arranged in a service area and a few mobile robots as a result of the strong desire for the development of advanced systems that can flexibly function in dynamically changing environments (Matsumoto et al., 2009). In this chapter, a large scale and dense wireless sensor network made up of many static sensor nodes with global positioning system, which is a representative network to actualize the above-mentioned sensor applications, is assumed. In a large scale and dense wireless sensor network, generally, hundreds or thousands of static sensor nodes limited resources, which are compact and inexpensive, are placed in a service area, and sensing data of each node is gathered to a sink node by inter-node wireless multi-hop communication. Each sensor node consists of a sensing function to measure the status (temperature, humidity, motion, etc.) of an observation point or object, a limited function of information processing, and a simplified wireless communication function, and it generally operates on a resource with a limited power-supply capacity such as a battery. Therefore, a data gathering scheme and/or a routing protocol capable of meeting the following requirements is mainly needed to prolong the lifetime of a large scale and dense wireless sensor network composed of hundreds or thousands of static sensor nodes limited resources. 1. Efficiency of data gathering 2. Balance of communication load among sensor nodes 3. Adaptability to network topology changes

Optimal power allocation (OPA) is considered to be one of the key issues in designing a wireless sensor network (WSN). Generally, the OPA in WSN can be formulated as a numerical optimization problem with constraints. Differential evolution (DE) has been proved to be a very efficient evolutionary algorithm for global numerical optimization. Based on this consideration, in this paper, an empirical study is conducted to evaluate the performance of DE for the OPA. Different mutation strategies and different parameter settings are used in DE to test the influence of them when optimizing the OPA. The sensors in WSN are scaled up to 200. Experimental results indicate that the parameters of CR and F are sensitive to the performance for the OPA. In addition, with the same parameter setting, the strategy selection is stable in DE.

In this paper, we consider the two-way relay channel (TWRC) over which communication is performed using space-time block codes (STBC) with physical-layer network coding (PNC) protocol. The three-node two-way relaying (TWR) model consists of two end nodes (sources) simultaneously communicating with each other over a relay node where each node is equipped with two antennas and uses Alamouti's STBC to provide diversity. We consider non-reciprocal channels where fading channel coefficients are independent for opposite directions of the same link. We first derive closed form expressions for the outage probability of the STBC-TWR system and uncoded TWRC assuming equal transmit power at each node and decode-and-forward (DF) strategy at the relay. We show that the STBC-TWR system significantly improves the uncoded TWRC outage performance. Then, to further improve the performance, we propose an optimal power allocation in TWR scheme employing Alamouti's STBC and PNC protocol. The optimal power allocation is obtained by maximizing the sum-rate under the total power constraint. We show that the optimal power allocation considerably improve the outage performance as well as the sum-rate compared to the equal-power case.

Understanding Packet Delivery Performance In Dense Wireless Sensor Networks ∗ Computer Science Department University of Southern California Los Angeles, CA 90089-0781 Jerry Zhao Computer Science Department University of Southern California Los Angeles, CA 90089-0781 Ramesh Govindan zhaoy@usc.edu ABSTRACT Wireless sensor networks promise fine-grain monitoring in a wide variety of environments. Many of these environ- ments (e.g., indoor environments or habitats) can be harsh for wireless communication. From a networking perspec- tive, the most basic aspect of wireless communication is the packet delivery performance: the spatio-temporal charac- teristics of packet loss, and its environmental dependence. These factors will deeply impact the performance of data acquisition from these networks. In this paper, we report on a systematic medium-scale (up to sixty nodes) measurement of packet delivery in three different environments: an indoor office building, a habitat with moderate foliage, and an open parking lot. Our findings have interesting implications for the design and evaluation of routing and medium-access protocols for sensor networks. ramesh@usc.edu spectrum under use, the particular modulation schemes un- der use, and possibly on the communicating devices them- selves. Communication quality can vary dramatically over time, and has been reputed to change with slight spatial displacements. All of these are true to a greater degree for ad-hoc (or infrastructure-less) communication than for wire- less communication to a base station. Given this, and the paucity of large-scale deployments, it is perhaps not surpris- ing that there have been no medium to large-scale measure- ments of ad-hoc wireless systems; one expects measurement studies to reveal high variability in performance, and one suspects that such studies will be non-representative. Wireless sensor networks [5, 7] are predicted on ad-hoc wireless communications. Perhaps more than other ad-hoc wireless systems, these networks can expect highly variable wireless communication. They will be deployed in harsh, inaccessible, environments which, almost by definition will exhibit significant multi-path communication. Many of the current sensor platforms use low-power radios which do not have enough frequency diversity to reject multi-path prop- agation. Finally, these networks will be fairly densely de- ployed (on the order of tens of nodes within communica- tion range). Given the potential impact of these networks, and despite the anecdotal evidence of variability in wireless communication, we argue that it is imperative that we get a quantitative understanding of wireless communication in sensor networks, however imperfect. Our paper is a first attempt at this. Using up to 60 Mica motes, we systematically evaluate the most basic aspect of wireless communication in a sensor network: packet delivery. Particularly for energy-constrained networks, packet de- livery performance is important, since that translates to net- work lifetime. Sensor networks are predicated using low- power RF transceivers in a multi-hop fashion. Multiple short hops can be more energy-efficient than one single hop over a long range link. Poor cumulative packet delivery per- formance across multiple hops may degrade performance of data transport and expend significant energy. Depending on the kind of application, it might significantly undermine application-level performance. Finally, understanding the dynamic range of packet delivery performance (and the ex- tent, and time-varying nature of this performance) is impor- tant for evaluating almost all sensor network communication protocols. We study packet delivery performance at two layers of the communication stack (Section 3). At the physical-layer and in the absence of interfering transmissions, packet de- Categories and Subject Descriptors C.2.1 [Network Architecture and Design]: Wireless communication; C.4 [Performance of Systems]: Perfor- mance attributes, Measurement techniques General Terms Measurement, Experimentation Keywords Low power radio, Packet loss, Performance measurement 1. INTRODUCTION Wireless communication has the reputation of being no- toriously unpredictable. The quality of wireless communica- tion depends on the environment, the part of the frequency ∗ This work is supported in part by NSF grant CCR-0121778 for the Center for Embedded Systems. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. SenSys’03, November 5–7, 2003, Los Angeles, California, USA. Copyright 2003 ACM 1-58113-707-9/03/0011 ... $ 5.00.

Synchronization of tiny sensor nodes forming Wireless Sensor Networks (WSNs) is a challenging problem due to frequent topological changes, node failures and power, memory and computation constraints. These difficulties promote a self-organizing solution for the problem of time synchronization in WSNs to be quite desirable. Current self-organizing time synchronization protocols in WSNs have drawbacks: They either provide synchronicity but not a common notion of time for the nodes in the network or they demand keeping track of the time information of the neighboring nodes. The latter drawback becomes quite crucial especially on dense WSNs, which makes available self-organizing time synchronization protocols impractical. This paper provides a novel self-organizing time synchronization protocol for WSNs which does not require keeping track of the neighboring nodes. The main component of our protocol is a computationally light "adaptive-value tracking" algorithm which synchronizes the rate of each sensor node to that of all its neighboring nodes through successive feedbacks. We show by simulations that the proposed protocol achieves a tight synchronization which results in the desired property of global time notion after a finite amount of time on dense networks. Although there is no formal proof yet of the protocol's convergence, we anticipate this protocol could be used as a practical time synchronization approach.

Large wireless sensor networks can contain hundreds or thousands of sensor nodes. Due to wireless sensor network’s properties of low-energy-efficiency, large-scale, low cost, and lossy nature, the development of efficient routing protocols for these large and dense wireless sensor networks is an interesting research topic. This research focuses on the design and implementation of protocols for dense and wireless sensor networks. More specifically, we propose to combine an underlying topology with Xmesh, the multihop routing strategy of Crossbow Technology’s motes. In an effort to limit the path lengths, we propose to impose an underlying connectivity graph for Xmesh. The underlying connectivity graph is a virtual topology of the network, hence the name “topology-based routing.” Instead of being always forwarded to the node with the best link quality among all neighbors, a packet is being routed according to the shortest path routing of the underlying graph which guarantees a bounded path length. Cayley graphs from the Borel subgroup have been known as the densest degree-4 graphs and all Cayley graphs are vertex transitive. In this work, we propose a topology-based routing for Xmesh with Cayley graphs as the underlying topology. We show that, indeed, by imposing a Cayley graph as an underlying graph, the average path lengths between nodes is smaller and that the averaged power consumed is less than the original Xmesh.

In this paper, we present a novel algorithm for partner selection and power allocation in the amplify-and-forward cooperative diversity that minimizes the required total transmit power by given outage probability constraint. We represent the problem with new formulation and solve the optimal power allocation by KKT method for a fixed set of partners. For optimal partner selection, we use a novel algorithm with low complexity to find the best set with minimum required power. We present simulation results to demonstrate that the outcomes of the proposed algorithm are very close to results of full search for optimal set.

Sensing coverage is a fundamental design issue in wireless sensor networks (WSNs), while sensor scheduling ensures coverage degree to the monitored event and extends the network lifetime.In this paper, we address k-coverage scheduling problem in dense WSNs, we maintain a connected k-coverage energy efficiently through a novel Hard-Core based Coordinated Scheduling (HCCS), in which hardcore is a thinning process in stochastic geometry that inhibits more than one active sensor covering any area redundantly in a minimum distance. As compared with existing coordinated scheduling, HCCS allows coordination between sensors with little communication overhead. Moreover, due to the traditional sensing models in k-coverage analysis is unsuitable to describe the characteristic of transmit channel in dense WSNs, we propose a novel sensing model integrating Rayleigh Fading and Distribution of Active sensors (RFDA), and derive the coverage measure and k-coverage probability for the monitored event under RFDA. In addition, we analyze the influence factors, i.e. the transmit condition and monitoring degree to the k-coverage probability. Finally, through Monte Carlo simulations, it is shown that the k-coverage probability of HCCS outperforms that of its random scheduling counterpart.

In this paper, we consider the three-node two-way relay channel (TWRC) over which communication is performed using space-time block codes (STBC) with physical-layer network coding (PNC) protocol. Two end nodes simultaneously communicate with each other over a relay node where each node is equipped with two antennas and uses Alamouti's STBC to provide diversity. First, a closed form expression for the outage probability of the STBC-TWR system is derived, assuming nonreciprocal channels, equal transmit power at each node and decode-and-forward (DF) strategy at the relay. It is shown that the STBC-TWR system significantly improves the uncoded TWRC outage performance. Then, to further improve the performance, an optimal power allocation to maximize the sum-rate under the total power constraint, is proposed. It is shown that the optimal power allocation considerably improve the sum-rate as well as the outage performance compared to the equal-power case.

For energy-constrained wireless sensor networks (WSNs), the topology control issue is fundamental and important to maximize the overall network lifetime. Recently a two-tiered network model has been proposed for this purpose. It is a cluster-based network model composed of application and sensor nodes. In this model the application nodes are easy to run out of energy because they not only serve as cluster heads for aggregating data packets from the sensor nodes in their clusters but also are responsible for forming a connected network topology for information dissemination at the higher tier. In order to balance nodes' power consumption and extend the topological lifetime of a WSN with regard to a certain amount of initial energy provision, we propose a logical three-tiered network model which consist of relay nodes (RNs), application nodes (ANs) and sensor nodes (SNs). Under this architecture, the goal of lower-tier SNs is to sense the playing fields and middle-tier ANs only need to gather data from their clusters; Upper-tier RNs are designed to route information as efficiently as possible. In this paper, we first formulate the three-tiered WSN's model as well as the power consumption model of WSNs. Then considering one dimension relaying, we figure out the RNs' optimal placement for each AN which can considerably minimize the total power consumption for WSNs. Finally, we give some criteria for two-dimension relaying.

The area of wireless sensor networks (WSNs) has gained significant attention from researchers due to its expansive range of applications, such as industrial regulation, human detection, and medical diagnosis. WSN is a vast number of geographically scattered devices that use sensor nodes to communicate and gather information from the target region. In clustered WSNs, the cluster head (CH) is deliberated as the relay node at a higher energy level than the non-CH nodes. The relay nodes perform more tasks related to the non-CHs, and these relay nodes are restricted by energy and communication capacity. Therefore, balancing the load of the relay node is a significant concern for improving the performance of the WSNs. Clustering is a well-known technique enforced to balance the load of the relay nodes. Often, densely loaded relay nodes dissolve their energy in less time and may cause changes in the topology of the network. In this study, we propose a Quasi-oppositional based Jaya load balancing strategy (QOJ-LBS) with a novel fitness function to address the issue of load balancing. The novel fitness function derived from the convex combination of the least lifespan of the relay node across the network and the entropy value of the lifespan of all relay nodes. The proposed QOJ-LBS justifies the network performance under two different WSN conditions called scenario-1 and scenario-2 with single-hop and multi-hop routing. The experimental analysis shows that improvement in network lifespan, total energy utilization, and the number of active sensor nodes of WSN is statistically significant in proposed QOJ-LBS compared to other state-of-the-art algorithms.

Efficient coding techniques algorithm for cluster-heads communication in wireless sensor networks