Convergence Analysis of Mixed Timescale Cross-Layer Stochastic Optimization

This paper considers a cross-layer optimization problem driven by multi-timescale stochastic exogenous processes in wireless communication networks. Due to the hierarchical information structure in a wireless network, a mixed timescale stochastic iterative algorithm is proposed to track the time-varying optimal solution of the cross-layer optimization problem, where the variables are partitioned into short-term controls updated in a faster timescale, and long-term controls updated in a slower timescale. We focus on establishing a convergence analysis framework for such multi-timescale algorithms, which is difficult due to the timescale separation of the algorithm and the time-varying nature of the exogenous processes. To cope with this challenge, we model the algorithm dynamics using stochastic differential equations (SDEs) and show that the study of the algorithm convergence is equivalent to the study of the stochastic stability of a virtual stochastic dynamic system (VSDS). Leveraging the techniques of Lyapunov stability, we derive a sufficient condition for the algorithm stability and a tracking error bound in terms of the parameters of the multi-timescale exogenous processes. Based on these results, an adaptive compensation algorithm is proposed to enhance the tracking performance. Finally, we illustrate the framework by an application example in wireless heterogeneous network

Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey

This paper provides a comprehensive review of the domain of physical layer security in multiuser wireless networks. The essential premise of physical-layer security is to enable the exchange of confidential messages over a wireless medium in the presence of unauthorized eavesdroppers without relying on higher-layer encryption. This can be achieved primarily in two ways: without the need for a secret key by intelligently designing transmit coding strategies, or by exploiting the wireless communication medium to develop secret keys over public channels. The survey begins with an overview of the foundations dating back to the pioneering work of Shannon and Wyner on information-theoretic security. We then describe the evolution of secure transmission strategies from point-to-point channels to multiple-antenna systems, followed by generalizations to multiuser broadcast, multiple-access, interference, and relay networks. Secret-key generation and establishment protocols based on physical layer mechanisms are subsequently covered. Approaches for secrecy based on channel coding design are then examined, along with a description of inter-disciplinary approaches based on game theory and stochastic geometry. The associated problem of physical-layer message authentication is also introduced briefly. The survey concludes with observations on potential research directions in this area.Comment: 23 pages, 10 figures, 303 refs. arXiv admin note: text overlap with arXiv:1303.1609 by other authors. IEEE Communications Surveys and Tutorials, 201

Exploiting Diversity in Broadband Wireless Relay Networks

Fading is one of the most fundamental impairments to wireless communications. The standard approach to combating fading is by adding redundancy - or diversity - to help increase coverage and transmission speed. Motivated by the results in multiple-input multiple-output technologies, which are usually used at base stations or access points, cooperation commutation has been proposed to improve the performance of wireless networks which consist of low-cost single antenna devices. While the majority of the research in cooperative communication focuses on flat fading for its simplicity and easy analysis, in practice the underlying channels in broadband wireless communication systems such as cellular systems (UMTS/LTE) are more likely to exhibit frequency selective fading. In this dissertation, we consider a frequency selective fading channel model and explore distributed diversity techniques in broadband wireless relay networks, with consideration to practical issues such as channel estimation and complexity-performance tradeoffs. We first study a system model with one source, one destination and multiple decode-and-forward (DF) relays which share a single channel orthogonal to the source. We derive the diversity-multiplexing tradeoff (DMT) for several relaying strategies: best relay selection, random relay selection, and the case when all decoding relays participate. The best relay selection method selects the relay in the decoding set with the largest sum-squared relay-to-destination channel coefficients. This scheme can achieve the optimal DMT of the system at the expense of higher complexity, compared to the other two relaying strategies which do not always exploit the spatial diversity offered by the relays. Different from flat fading, we find special cases when the three relaying strategies have the same DMT. We further present a transceiver design and prove it can achieve the optimal DMT asymptotically. Monte Carlo simulations are presented to corroborate the theoretical analysis. We provide a detailed performance comparison of the three relaying strategies in channels encountered in practice. The work has been extended to systems with multiple amplify-and-forward relays. We propose two relay selection schemes with maximum likelihood sequential estimator and linear zero- forcing equalization at the destination respectively and both schemes can asymptotically achieve the optimal DMT. We next extend the results in the two-hop network, as previously studied, to multi-hop networks. In particular, we consider the routing problem in clustered multi-hop DF relay networks since clustered multi-hop wireless networks have attracted significant attention for their robustness to fading, hierarchical structure, and ability to exploit the broadcast nature of the wireless channel. We propose an opportunistic routing (or relay selection) algorithm for such networks. In contrast to the majority of existing approaches to routing in clustered networks, our algorithm only requires channel state information in the final hop, which is shown to be essential for reaping the diversity offered by the channel. In addition to exploiting the available diversity, our simple cross-layer algorithm has the flexibility to satisfy an additional routing objective such as maximization of network lifetime. We demonstrate through analysis and simulation that our proposed routing algorithm attains full diversity under certain conditions on the cluster sizes, and its diversity is equal to the diversity of more complicated approaches that require full channel state information. The final part of this dissertation considers channel estimation in relay networks. Channel state information is vital for exploiting diversity in cooperative networks. The existing literature on cooperative channel estimation assumes that block lengths are long and that channel estimation takes place within a fading block. However, if the forwarding delay needs to be reduced, short block lengths are preferred, and adaptive estimation through multiple blocks is required. In particular, we consider estimating the relay-to-destination channel in DF relay systems for which the presence of forwarded information is probabilistic since it is unknown whether the relay participates in the forwarding phase. A detector is used so that the update of the least mean square channel estimate is made only when the detector decides the presence of training data. We use the generalized likelihood ratio test and focus on the detector threshold for deciding whether the training sequence is present. We also propose a heuristic objective function which leads to a proper threshold to improve the convergence speed and reduce the estimation error. Extensive numerical results show the superior performance of using this threshold as opposed to fixed thresholds

Energy efficient wireless sensor network protocols for monitoring and prognostics of large scale systems

In this work, energy-efficient protocols for wireless sensor networks (WSN) with applications to prognostics are investigated. Both analytical methods and verification are shown for the proposed methods via either hardware experiments or simulation. This work is presented in five papers. Energy-efficiency methods for WSN include distributed algorithms for i) optimal routing, ii) adaptive scheduling, iii) adaptive transmission power and data-rate control --Abstract, page iv