Distributed secrecy for information theoretic sensor network models

This dissertation presents a novel problem inspired by the characteristics of sensor networks. The basic setup through-out the dissertation is that a set of sensor nodes encipher their data without collaboration and without any prior shared secret materials. The challenge is dealt by an eavesdropper who intercepts a subset of the enciphered data and wishes to gain knowledge of the uncoded data. This problem is challenging and novel given that the eavesdropper is assumed to know everything, including secret cryptographic keys used by both the encoders and decoders. We study the above problem using information theoretic models as a necessary first step towards an understanding of the characteristics of this system problem. This dissertation contains four parts. The first part deals with noiseless channels, and the goal is for sensor nodes to both source code and encipher their data. We derive inner and outer regions of the capacity region (i.e the set of all source coding and equivocation rates) for this problem under general distortion constraints. The main conclusion in this part is that unconditional secrecy is unachievable unless the distortion is maximal, rendering the data useless. In the second part we thus provide a practical coding scheme based on distributed source coding using syndromes (DISCUS) that provides secrecy beyond the equivocation measure, i.e. secrecy on each symbol in the message. The third part deals with discrete memoryless channels, and the goal is for sensor nodes to both channel code and encipher their data. We derive inner and outer regions to the secrecy capacity region, i.e. the set of all channel coding rates that achieve (weak) unconditional secrecy. The main conclusion in this part is that interference allows (weak) unconditional secrecy to be achieved in contrast with the first part of this dissertation. The fourth part deals with wireless channels with fading and additive Gaussian noise. We derive a general outer region and an inner region based on an equal SNR assumption, and show that the two are partially tight when the maximum available user powers are admissible

Analysis and design of physical-layer network coding for relay networks

Physical-layer network coding (PNC) is a technique to make use of interference in wireless transmissions to boost the system throughput. In a PNC employed relay network, the relay node directly recovers and transmits a linear combination of its received messages in the physical layer. It has been shown that PNC can achieve near information-capacity rates. PNC is a new information exchange scheme introduced in wireless transmission. In practice, transmitters and receivers need to be designed and optimized, to achieve fast and reliable information exchange. Thus, we would like to ask: How to design the PNC schemes to achieve fast and reliable information exchange? In this thesis, we address this question from the following works: Firstly, we studied channel-uncoded PNC in two-way relay fading channels with QPSK modulation. The computation error probability for computing network coded messages at the relay is derived. We then optimized the network coding functions at the relay to improve the error rate performance. We then worked on channel coded PNC. The codes we studied include classical binary code, modern codes, and lattice codes. We analyzed the distance spectra of channel-coded PNC schemes with classical binary codes, to derive upper bounds for error rates of computing network coded messages at the relay. We designed and optimized irregular repeat-accumulate coded PNC. We modified the conventional extrinsic information transfer chart in the optimization process to suit the superimposed signal received at the relay. We analyzed and designed Eisenstein integer based lattice coded PNC in multi-way relay fading channels, to derive error rate performance bounds of computing network coded messages. Finally we extended our work to multi-way relay channels. We proposed a opportunistic transmission scheme for a pair-wise transmission PNC in a single-input single-output multi-way relay channel, to improve the sum-rate at the relay. The error performance of computing network coded messages at the relay is also improved. We optimized the uplink/downlink channel usage for multi-input multi-output multi-way relay channels with PNC to maximize the degrees of freedom capacity. We also showed that the system sum-rate can be further improved by a proposed iterative optimization algorithm

On the Intersection of Communication and Machine Learning

The intersection of communication and machine learning is attracting increasing interest from both communities. On the one hand, the development of modern communication system brings large amount of data and high performance requirement, which challenges the classic analytical-derivation based study philosophy and encourages the researchers to explore the data driven method, such as machine learning, to solve the problems with high complexity and large scale. On the other hand, the usage of distributed machine learning introduces the communication cost as one of the basic considerations for the design of machine learning algorithm and system.In this thesis, we first explore the application of machine learning on one of the classic problems in wireless network, resource allocation, for heterogeneous millimeter wave networks when the environment is with high dynamics. We address the practical concerns by providing the efficient online and distributed framework. In the second part, some sampling based communication-efficient distributed learning algorithm is proposed. We utilize the trade-off between the local computation and the total communication cost and propose the algorithm with good theoretical bound. In more detail, this thesis makes the following contributionsWe introduced an reinforcement learning framework to solve the resource allocation problems in heterogeneous millimeter wave network. The large state/action space is decomposed according to the topology of the network and solved by an efficient distribtued message passing algorithm. We further speed up the inference process by an online updating process.We proposed the distributed coreset based boosting framework. An efficient coreset construction algorithm is proposed based on the prior knowledge provided by clustering. Then the coreset is integrated with boosting with improved convergence rate. We extend the proposed boosting framework to the distributed setting, where the communication cost is reduced by the good approximation of coreset.We propose an selective sampling framework to construct a subset of sample that could effectively represent the model space. Based on the prior distribution of the model space or the large amount of samples from model space, we derive a computational efficient method to construct such subset by minimizing the error of classifying a classifier

Fundamental limits and optimal operation in large wireless networks

Wireless adhoc networks consist of users that want to communicate with each other over a shared wireless medium. The users have transmitting and receiving capabilities but there is no additional infrastructure for assisting communication. This is in contrast to existing wireless systems, cellular networks for example, where communication between wireless users heavily relies on an additional infrastructure of base stations connected with a high-capacity wired backbone. The fact that they are infrastructureless makes wireless adhoc networks inexpensive, easy to build and robust but at the same time technically more challenging. The fundamental challenge is how to deal with interference: many simultaneous transmissions have to be accommodated on the same wireless channel when each of these transmissions constitutes interference for the others, degrading the quality of the communication. The traditional approach to wireless adhoc networks is to organize users so that they relay information for each other in a multi-hop fashion. Such multi-hopping strategies face scalability problems at large system size. As shown by Gupta and Kumar in their seminal work in 2000, the maximal communication rate per user under such strategies scales inversely proportional to the square root of the number of users in the network, hence decreases to zero with increasing system size. This limitation is due to interference that precludes having many simultaneous point-to-point transmissions inside the network. In this thesis, we propose a multiscale hierarchical cooperation architecture for distributed MIMO communication in wireless adhoc networks. This novel architecture removes the interference limitation at least as far as scaling is concerned: we show that the per-user communication rate under this strategy does not degrade significantly even if there are more and more users entering into the network. This is in sharp contrast to the performance achieved by the classical multi-hopping schemes. However, the overall picture is much richer than what can be depicted by a single scheme or a single scaling law formula. Nowadays, wireless adhoc networks are considered for a wide range of practical applications and this translates to having a number of system parameters (e.g., area, power, bandwidth) with large operational range. Different applications lie in different parameter ranges and can therefore exhibit different characteristics. A thorough understanding of wireless adhoc networks can only be obtained by exploring the whole parameter space. Existing scaling law formulations are insufficient for this purpose as they concentrate on very small subsets of the system parameters. We propose a new scaling law formulation for wireless adhoc networks that serves as a mathematical tool to characterize their fundamental operating regimes. For the standard wireless channel model where signals are subject to power path-loss attenuation and random phase changes, we identify four qualitatively different operating regimes in wireless adhoc networks with large number of users. In each of these regimes, we characterize the dependence of the capacity on major system parameters. In particular, we clarify the impact of the power and bandwidth limitations on performance. This is done by deriving upper bounds on the information theoretic capacity of wireless adhoc networks in Chapter 3, and constructing communication schemes that achieve these upper bounds in Chapter 4. Our analysis identifies three engineering quantities that together determine the operating regime of a given wireless network: the short-distance signal-to-noise power ratio (SNRs), the long-distance signal-to-noise power ratio (SNRl) and the power path-loss exponent of the environment. The right communication strategy for a given application is dictated by its operating regime. We show that conventional multi-hopping schemes are optimal when the power path-loss exponent of the environment is larger than 3 and SNRs ≪ 0 dB. Such networks are extremely power-limited. On the other hand, the novel architecture proposed in this thesis, based on hierarchical cooperation and distributed MIMO, is the fundamentally right strategy for wireless networks with SNRl ≫ 0 dB. Such networks experience no power limitation. In the intermediate cases, captured by the remaining two operating regimes, neither multi-hopping nor hierarchical-MIMO achieves optimal performance. We construct new schemes for these regimes that achieve capacity. The proposed characterization of wireless adhoc networks in terms of their fundamental operating regimes, is analogous to the familiar understanding of the two operating regimes of the point-to-point additive white Gaussian noise (AWGN) channel. From an engineering point of view, one of the most important contributions of Shannon's celebrated capacity formula is to identify two qualitatively different operating regimes on this channel. Determined by its signal-to-noise power ratio (SNR), an AWGN channel can be either in a bandwidth-limited (SNR ≫ 0 dB) or a power-limited (SNR ≪ 0 dB) regime. Communication system design for this channel has been primarily driven by the operating regime one is in