Node localization algorithms that can be easily integrated into deployed wireless sensor networks (WSNs) and which run seamlessly with proprietary lower layer communication protocols running on off-the-shelf modules can help operators of large farms and orchards avoid the difficulty, cost and/or time involved with manual or satellite-based node localization techniques. Even though the state-of-the-art node localization algorithms can achieve low error rates using distributed techniques such as belief propagation (BP), they are not well suited to WSNs deployed for precision agriculture applications with large number of nodes, few number of landmarks and lack real time update capability. The algorithm proposed here is designed for applications such as pest control and irrigation in large farms and orchards where greater power efficiency and scalability are required but location accuracy requirements are less demanding. Our algorithm uses received signal strength indicator (RSSI) values to estimate the distribution of distance between nodes then updates the location probability mass function (pmf) of nodes in a distributed manner.At every time step, the most recently communicated path loss samples and location prior pmf received from neighbouring nodes is sufficient for nodes with unknown location to update their location pmf. This renders the algorithm recursive, hence results in lower computational complexity at each time step. We propose a particular realization of the method in which only one node multicasts at each time step and neighbouring nodes update their location pmf conditioned on all communicated samples over previous time steps. This is highly compatible with realistic WSN deployments, e.g., ZigBee which are based upon the ad hoc on-demand distance vector (AODV) where nodes flood route request (RREQ) and route reply (RREP) packets. Further, beacon signals transmitted during the network formation and routing table formulation stage can provide the RSSI information required by the localization algorithm. Index TermsWireless sensor networks, distributed localization, range-based localization algorithms, path loss measurements, information aggregation, precision agriculture September 9, 2015 DRAFT 2

A key issue in the multi agent state estimation presented in social networks is the inadvertent multiple re-use of data also known as mis-information propagation or data incest. We formulate this mis-information propagation in a graph theoretic setting and give a necessary and sufficient conditions on the topology of information flow network so that the underlying state can be estimated optimally. A distributed fusion algorithm is proposed so that the social network has incest free estimates. We also provide a discussion on mis-information removal algorithm for information exchange protocols where people learn from actions of others in a social network. A sub-optimal algorithm is also presented when the information flow graph is not known. Numerical examples are provided to illustrate the performance of the proposed optimal and sub-optimal algorithms.

The proliferation of social media such as real time microblogging and online reputation systems facilitate real time sensing of social patterns and behavior. In the last decade, sensing and decision making in social networks have witnessed significant progress in the electrical engineering, computer science, economics, finance, and sociology research communities. Research in this area involves the interaction of dynamic random graphs, socio-economic analysis, and statistical inference algorithms. This monograph provides a survey, tutorial development, and discussion of four highly stylized examples: social learning for interactive sensing; tracking the degree distribution of social networks; sensing and information diffusion; and coordination of decision making via game-theoretic learning. Each of the four examples is motivated by practical examples, and comprises of a literature survey together with careful problem formulation and mathematical analysis. Despite being highly stylized, these examples provide a rich variety of models, algorithms and analysis tools that are readily accessible to a signal processing, control/systems theory, and applied mathematics audience.Comment: Foundations and Trends in Signal Processing, Now Publishers, 201

In this paper, we propose a novel multi-hop relaying scheme to improve the performance and coverage of impulseradio-based ultra-wideband (IR-UWB) systems. With regard to a simple practical realization, we focus on a non-coherent system setup in conjunction with amplify-and-forward (A&F) relaying. In particular, we propose to employ a multiple-differential encoding scheme at the source node and single differential decoding at each relay and at the destination node, respectively, so as to efficiently limit intersymbol-interference effects at the destination node. For a dual-hop system we derive a closed-form expression for the signal-to-noise ratio (SNR) at the destination node, and for the general multi-hop case we provide a simple recursive formula for SNR calculation. Based on these SNR results, we obtain a closed-form expression for the optimal transmit power allocation to the source node and the relay for a dual-hop system and a simple recursive suboptimal power allocation scheme for the multi-hop case, which permits a semi-distributed implementation with limited feedback between nodes. Simulation results illustrate the excellent performance of the proposed multiple-differential encoding scheme with A&F relaying for both uncoded and coded transmission compared to various alternative coherent and non-coherent schemes based on A&F relaying and decode-andforward (D&F) relaying. Furthermore, our simulations confirm the (near-)optimal performance of the proposed power allocation solutions.Index Terms-Ultra-wideband (UWB) communications, impulse radio (IR), amplify and forward (A&F) relaying, multiple hops, differential encoding, performance analysis, power allocation.

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