We use tools and techniques from information theory to improve the design of Wireless Sensor Networks (WSNs). We do this by first developing a model for WSNs that is analogous to models of communication systems in information theory. In particular, we define the notion of WSN Coding, which is analogous to source coding from information theory, and the Collection Channel, which is analogous to a transport channel in information theory. We then use source coding theorems from information theory to develop three results that aid in WSN design. First, we propose a new top-level design metric for WSNs. Second, we develop an efficiency measure for the sensing process in a WSN. Finally, we use techniques from source coding schemes to suggest new designs for WSNs and the sensors they contain. We strive for tools that apply under the most general conditions possible so that designers can use them in any WSN. However, we also apply each tool to a specific example WSN illustrate the tool's value.

One of the fundamental assumptions made in the design of wireless networks is that the wireless devices have to be half-duplex, i.e., they cannot simultaneously transmit and receive in the same frequency band. The key deterrent in implementing a full-duplex wireless device, which can simultaneously transmit and receive in the same frequency band, is the large power differential between the self-interference from a device's own transmissions and the signal of interest coming from a distant source. In this thesis, we revisit this basic assumption and propose a full-duplex radio design. The design suppresses the self-interference signal by employing a combination of passive suppression, and active analog and digital cancellation mechanisms. The active cancellations are designed for wideband, multiple subcarrier (OFDM), and multiple antenna (MIMO) wireless communications systems. We then implement our design as a 20 MHz MIMO OFDM system with a 2.4 GHz center frequency, suitable for Wi-Fi systems. We perform extensive over-the-air tests to characterize our implementation. Our main contributions are the following: (a) the average amount of active cancellation increases as the received self-interference power increases and as a result, the rate of a full-duplex link increases as the transmit power of communicating devices increases, (b) applying digital cancellation after analog cancellation can sometimes increase the self-interference and the effectiveness of digital cancellation in a full-duplex system will depend on the performance of the cancellation stages that precede it, (c) our full-duplex device design achieves an average of 85 dB of self-interference cancellation over a 20 MHz bandwidth at 2.4 GHz, which is the best cancellation performance reported to date, (d) our full-duplex device design achieves 30-84% higher ergodic rates than its half-duplex counterpart for received powers in the range of [-75, -60] dBm. As a result, our design is the first one to achieve Wi-Fi ranges; in comparison, no implementation to date has achieved Wi-Fi ranges. Consequently, we have conclusively demonstrated that Wi-Fi full-duplex is practically feasible and hence shown that one of the commonly made assumptions in wireless networks is not fundamental.

In this thesis, we study a three-node full-duplex network, where the infrastructure node has simultaneous up- and downlink communication in the same frequency band with two half-duplex nodes. In addition to self-interference at the full-duplex infrastructure node, the three-node network has to contend with the inter-node interference between the two half-duplex nodes. The two forms of interferences differ in one important aspect that the self-interference is known at the interfered receiver. Therefore, we propose to leverage a wireless side-channel to manage the inter-node interference. We characterize the impact of inter-node interference on the network achievable rate region with and without a side-channel between the nodes. We present four distributed full-duplex inter-node interference cancellation schemes, which leverage the device-to-device wireless side-channel for improved interference cancellation. Of the four, bin-and-cancel is asymptotically optimal in high signal-to-noise ratio limit which uses Han-Kobayashi common-private message splitting and achieves within 1 bits/s/Hz of the capacity region for all values of channel parameters. The other three schemes are simpler compared to bin-and-cancel but achieve the near-optimal performance only in certain regimes of channel values. Asymptotic multiplexing gains of all proposed schemes are derived to show analytically that leveraging the side channel can be highly beneficial in increasing the multiplexing gain of the system exactly in those regimes where inter-node interference has the highest impact.

In most wireless networks, nodes have only limited local information about the state of the network, which includes connectivity and channel state information. With limited local information about the network, each node’s knowledge is mismatched; therefore, they must make distributed decisions. In this thesis, we pose the following question - if every node has network state information only about a small neighborhood, how and when should nodes choose to transmit? While link scheduling answers the above question for point-to-point physical layers which are designed for an interference-avoidance paradigm, we look for answers in cases when interference can be embraced by advanced code design, as suggested by results in network information theory. To make progress on this challenging problem, we propose two constructive distributed algorithms, one conservative and one aggressive, which achieve rates higher than link scheduling based on interference avoidance, especially if each node knows more than one hop of network state information. Both algorithms schedule sub-networks such that each sub-network can employ advanced interference-embracing coding schemes to achieve higher rates. Our innovation is in the identification, selection and scheduling of sub-networks, especially when sub-networks are larger than a single link. Using normalized sum-rate as the metric of network performance, we prove that the proposed conservative sub-network scheduling algorithm is guaranteed to have performance greater than or equal to pure coloring-based link scheduling. In addition, the proposed aggressive sub-network scheduling algorithm is shown, through simulations, to achieve better normalized sum-rate than the conservative algorithm for several network classes. Our results highlight the advantages of extending the design space of possible scheduling strategies to include those that leverage local network information.

This body of work forms a detailed and comprehensive guide for those interested in performing broadband wireless channel measurements. Discussion addresses the theoretical and practical aspects of designing and implementing a sliding correlator channel sounder, as well as how such a system may be used to measure and model the ultra-wideband wireless channel. The specific contributions of this work are as follows: Developed a systematic methodology for designing optimal sliding correlator-based channel sounders. Constructed a UWB channel sounder based upon a 17-bit LFSR that attained 1.66 ns of temporal resolution and 34 dB of dynamic range. Performed an exemplary measurement campaign of the UWB channel from which UWB angular spreads and RMS delay spreads are reported. The design procedure developed in Chapter 3 will allow researchers to build optimal channel sounders for investigating next-generation wireless channels. Chapter 4 s discussion addresses the real-world challenges of constructing a high performance sliding correlator channel sounder. Finally, the measurement campaign discussed in Chapter 5 outlines a procedure for investigating the spatio-temporal characteristics of the wireless channel and provides some of the first examples of UWB angular spread measurements.

Array-to-array, or multiple-input multiple-output (MIMO), links are known to provide extremely high spectral efficiencies in rich multipath environments, such as indoor wireless environments. The selection of a subset of receiver array antennas for a MIMO wireless link has been studied by many as a way to reduce cost and complexity in a MIMO system while providing diversity gain. Combined with a switched multi-beam beamformer, it becomes the beam selection system that can gain high signal-to-interference ratio (SIR) improvement in an interference-imited environment. The objective of this research is to evaluate the performance of low-complexity antenna or beam subset selection methods for small MIMO networks. The types of networks include (1) point-to-point MIMO links with out-of-system interference, (2)multi-user networks with a single, but possibly spatially distributed access point. We evaluate various selection techniques on measured indoor channels, which has not been done before. We propose a new practical selection metric, the peak-to-trough ratio of orthogonal frequency division multiplexing (OFDM) training symbols. We also compare antenna and beam selection on measured indoor channels under more general conditions than has previously been done. Finally, we consider some channel modeling issues associated with beamformers. We investigate the validity of three types of statistical MIMO channel models. A new beamformer is designed based on the ideal of the ``Weichselberger model.'

In the literature, most distributed detection developed so far mainly focuses on the test rule based on fixed sample size. However, in the real situations, sequential tests are more suitable to be utilized since it might achieve the same detection performance by using fewer number of samples as compared with the fixed-sample-size test. Thus, this theses will propose a new distributed sequential detection approach for the applications in wireless sensor networks(WSNs) and cognitive radios(CRs). First we refer to the sequential detection, and it has been developed by Wald in 1994, which is well known as the sequential probability ratio test (SPRT). The SPRT is proved to be able to decrease the required average sample numbers or reducing the average detection time. Indeed, the SPRT is the optimal sequential detection in terms of the minimizing the required number of samples given the constraint of false alarm and miss probabilities when the observation samples are independent and identical distributed (i.i.d.). However, if the observation samples are not dentically distributed, by simulation results show that the SPRT is not the optimal test. Based on a heuristic approach, this thesis then developed a new distributed detection scheme based on the sorted samples. Finally , the simulation results obtained by this thesis shows that the proposed scheme can further reduce the number of samples required for making the final decision as compared with SPRT.

In the thesis, we propose a non-line of sight (NLOS) mitigation approach based on the interacting multiple model (IMM) algorithm. The IMM-based structure, composed of a biased Kalman filter (BKF) and a Kalman filter with NLOS-discarding process (KF-D), is capable of mitigating the ranging error caused by the NLOS effects, and therefore improving the performance and accuracy in wireless location systems. The NLOS effect on signal transmission is one of the major factors that affect the accuracy of the time-based location systems. Effective NLOS identification and mitigation usually count on pre-determined statistic distribution and hypothesis assumption in the signals. Because the variance of the NLOS error is much large than that of measurement noise, hypothesis testing on the LOS/NLOS status can be formulated.The BKF combines the sliding window and decides the status by using hypothesis testing. The calculated variance and the detection result are used in switching between the biased and unbiased modes in the Kalman filter. In the contrast, the KF-D scheme identifies the NLOS status and tries to eliminate the NLOS effects by directly using the estimated results from the LOS stage. The KF-D scheme can achieve reasonably good NLOS mitigation if the estimates in the LOS status are obtained. Due to the discarding process, changes of the state vector within the NLOS stage are possibly ignored, and will cause larger errors in the state estimates. The BKF and KF-D can make up for each other by formulating the filters in an IMM structure, which could tune up the probabilities of BKF and KF-D. In our approach, the measured data are smoothed by sliding window and a BKF. The variance of data and the hypothesis test result are passed to the two filters. The BKF switches between the biased/unbiased modes by using the result. The KF-D may receive the estimated value from BKF based on the results. The probability computation unit changes the weights to get the estimated TOA values. With the simulations in ultra-wideband (UWB) signals, it can be seen that the proposed IMM-based approach can effectively mitigate the NLOS effects and increase the accuracy in wireless position.

Thesis (Ph. D.)--Rutgers University, 2008. / "Graduate Program in Electrical and Computer Engineering." Includes bibliographical references (p. 93-99).

Thesis (Ph. D.)--Rutgers University, 2009. / "Graduate Program in Computer Science." Includes bibliographical references (p. 103-106).