Showing papers in "IEEE Journal on Selected Areas in Communications in 2010"

Multi-Cell MIMO Cooperative Networks: A New Look at Interference

Abstract: This paper presents an overview of the theory and currently known techniques for multi-cell MIMO (multiple input multiple output) cooperation in wireless networks. In dense networks where interference emerges as the key capacity-limiting factor, multi-cell cooperation can dramatically improve the system performance. Remarkably, such techniques literally exploit inter-cell interference by allowing the user data to be jointly processed by several interfering base stations, thus mimicking the benefits of a large virtual MIMO array. Multi-cell MIMO cooperation concepts are examined from different perspectives, including an examination of the fundamental information-theoretic limits, a review of the coding and signal processing algorithmic developments, and, going beyond that, consideration of very practical issues related to scalability and system-level integration. A few promising and quite fundamental research avenues are also suggested.

A physical end-to-end model for molecular communication in nanonetworks

Abstract: Molecular communication is a promising paradigm for nanoscale networks. The end-to-end (including the channel) models developed for classical wireless communication networks need to undergo a profound revision so that they can be applied for nanonetworks. Consequently, there is a need to develop new end-to-end (including the channel) models which can give new insights into the design of these nanoscale networks. The objective of this paper is to introduce a new physical end-to-end (including the channel) model for molecular communication. The new model is investigated by means of three modules, i.e., the transmitter, the signal propagation and the receiver. Each module is related to a specific process involving particle exchanges, namely, particle emission, particle diffusion and particle reception. The particle emission process involves the increase or decrease of the particle concentration rate in the environment according to a modulating input signal. The particle diffusion provides the propagation of particles from the transmitter to the receiver by means of the physics laws underlying particle diffusion in the space. The particle reception process is identified by the sensing of the particle concentration value at the receiver location. Numerical results are provided for three modules, as well as for the overall end-to-end model, in terms of normalized gain and delay as functions of the input frequency and of the transmission range.

NLOS identification and mitigation for localization based on UWB experimental data

Abstract: Sensor networks can benefit greatly from location-awareness, since it allows information gathered by the sensors to be tied to their physical locations. Ultra-wide bandwidth (UWB) transmission is a promising technology for location-aware sensor networks, due to its power efficiency, fine delay resolution, and robust operation in harsh environments. However, the presence of walls and other obstacles presents a significant challenge in terms of localization, as they can result in positively biased distance estimates. We have performed an extensive indoor measurement campaign with FCC-compliant UWB radios to quantify the effect of non-line-of-sight (NLOS) propagation. From these channel pulse responses, we extract features that are representative of the propagation conditions. We then develop classification and regression algorithms based on machine learning techniques, which are capable of: (i) assessing whether a signal was transmitted in LOS or NLOS conditions; and (ii) reducing ranging error caused by NLOS conditions. We evaluate the resulting performance through Monte Carlo simulations and compare with existing techniques. In contrast to common probabilistic approaches that require statistical models of the features, the proposed optimization-based approach is more robust against modeling errors.

Cell Association and Interference Coordination in Heterogeneous LTE-A Cellular Networks

Abstract: Embedding pico/femto base-stations and relay nodes in a macro-cellular network is a promising method for achieving substantial gains in coverage and capacity compared to macro-only networks. These new types of base-stations can operate on the same wireless channel as the macro-cellular network, providing higher spatial reuse via cell splitting. However, these base-stations are deployed in an unplanned manner, can have very different transmit powers, and may not have traffic aggregation among many users. This could potentially result in much higher interference magnitude and variability. Hence, such deployments require the use of innovative cell association and inter-cell interference coordination techniques in order to realize the promised capacity and coverage gains. In this paper, we describe new paradigms for design and operation of such heterogeneous cellular networks. Specifically, we focus on cell splitting, range expansion, semi-static resource negotiation on third-party backhaul connections, and fast dynamic interference management for QoS via over-the-air signaling. Notably, our methodologies and algorithms are simple, lightweight, and incur extremely low overhead. Numerical studies show that they provide large gains over currently used methods for cellular networks.

Cooperative Multi-Cell Block Diagonalization with Per-Base-Station Power Constraints

Abstract: Block diagonalization (BD) is a practical linear precoding technique that eliminates the inter-user interference in downlink multiuser multiple-input multiple-output (MIMO) systems. In this paper, we apply BD to the downlink transmission in a cooperative multi-cell MIMO system, where the signals from different base stations (BSs) to all the mobile stations (MSs) are jointly designed with the perfect knowledge of the downlink channels and transmit messages. Specifically, we study the optimal BD precoder design to maximize the weighted sum-rate of all the MSs subject to a set of per-BS power constraints. This design problem is formulated in an auxiliary MIMO broadcast channel (BC) with a set of transmit power constraints corresponding to those for individual BSs in the multi-cell system. By applying convex optimization techniques, this paper develops an efficient algorithm to solve this problem, and derives the closed-form expression for the optimal BD precoding matrix. It is revealed that the optimal BD precoding vectors for each MS in the per-BS power constraint case are in general non-orthogonal, which differs from the conventional orthogonal BD precoder design for the MIMO-BC under one single sum-power constraint. Moreover, for the special case of single-antenna BSs and MSs, the proposed solution reduces to the optimal zero-forcing beamforming (ZF-BF) precoder design for the weighted sum-rate maximization in the multiple-input single-output (MISO) BC with per-antenna power constraints. Suboptimal and low-complexity BD/ZF-BF precoding schemes are also presented, and their achievable rates are compared against those with the optimal schemes.

Distributed scheduling scheme for video streaming over multi-channel multi-radio multi-hop wireless networks

Abstract: An important issue of supporting multi-user video streaming over wireless networks is how to optimize the systematic scheduling by intelligently utilizing the available network resources while, at the same time, to meet each video's Quality of Service (QoS) requirement. In this work, we study the problem of video streaming over multi-channel multi-radio multihop wireless networks, and develop fully distributed scheduling schemes with the goals of minimizing the video distortion and achieving certain fairness. We first construct a general distortion model according to the network?s transmission mechanism, as well as the rate distortion characteristics of the video. Then, we formulate the scheduling as a convex optimization problem, and propose a distributed solution by jointly considering channel assignment, rate allocation, and routing. Specifically, each stream strikes a balance between the selfish motivation of minimizing video distortion and the global performance of minimizing network congestions. Furthermore, we extend the proposed scheduling scheme by addressing the fairness problem. Unlike prior works that target at users' bandwidth or demand fairness, we propose a media-aware distortion-fairness strategy which is aware of the characteristics of video frames and ensures max-min distortion-fairness sharing among multiple video streams. We provide extensive simulation results which demonstrate the effectiveness of our proposed schemes.

Adaptive Spatial Intercell Interference Cancellation in Multicell Wireless Networks

Abstract: Downlink spatial intercell interference cancellation (ICIC) is considered for mitigating other-cell interference using multiple transmit antennas. A principle question we explore is whether it is better to do ICIC or simply standard single-cell beamforming. We explore this question analytically and show that beamforming is preferred for all users when the edge SNR (signal-to-noise ratio) is low ( 10 dB), for example in an urban setting. At medium SNR, a proposed adaptive strategy, where multiple base stations jointly select transmission strategies based on the user location, outperforms both while requiring a lower feedback rate than the pure ICIC approach. The employed metric is sum rate, which is normally a dubious metric for cellular systems, but surprisingly we show that even with this reward function the adaptive strategy also improves fairness. When the channel information is provided by limited feedback, the impact of the induced quantization error is also investigated. The analysis provides insights on the feedback design, and it is shown that ICIC with well-designed feedback strategies still provides significant throughput gain.

Anti-jamming broadcast communication using uncoordinated spread spectrum techniques

Abstract: Jamming-resistant communication is crucial for safety-critical applications such as emergency alert broadcasts or the dissemination of navigation signals in adversarial settings. In such applications, mission-critical messages are broadcast to a large and unknown number of (potentially untrusted) receivers that rely on the availability, integrity, and authenticity of the messages; here, availability primarily refers to the ability to communicate in the presence of jamming. Common techniques to counter jamming-based denial-of-service attacks such as Frequency Hopping (FH) and Direct Sequence Spread Spectrum (DSSS) cannot be applied in such settings because they depend on secret pairwise or group keys shared between the sender and the receivers before the communication. This dependency entails serious or unsolvable scalability and keysetup problems or weak jamming-resistance (a single malicious receiver can compromise the whole system). As a solution, in this work, we propose uncoordinated spread spectrum techniques that enable anti-jamming broadcast communication without shared secrets. Uncoordinated spread spectrum techniques can handle an unlimited amount of (malicious) receivers. We present two instances (Uncoordinated FH and Uncoordinated DSSS) and analyze differences in their performance as well as their combination. We further discuss the applications of these techniques to anti-jamming navigation broadcast, bootstrapping of coordinated spread spectrum communication, and anti-jamming emergency alerts.

Linear Precoding in Cooperative MIMO Cellular Networks with Limited Coordination Clusters

Abstract: In a cooperative multiple-antenna downlink cellular network, maximization of a concave function of user rates is considered. A new linear precoding technique called soft interference nulling (SIN) is proposed, which performs at least as well as zero-forcing (ZF) beamforming. All base stations share channel state information, but each user's message is only routed to those that participate in the user's coordination cluster. SIN precoding is particularly useful when clusters of limited sizes overlap in the network, in which case traditional techniques such as dirty paper coding or ZF do not directly apply. The SIN precoder is computed by solving a sequence of convex optimization problems. SIN under partial network coordination can outperform ZF under full network coordination at moderate SNRs. Under overlapping coordination clusters, SIN precoding achieves considerably higher throughput compared to myopic ZF, especially when the clusters are large.

Cooperative Recovery of Distributed Storage Systems from Multiple Losses with Network Coding

Abstract: This paper studies the recovery from multiple node failures in distributed storage systems. We design a mutually cooperative recovery (MCR) mechanism for multiple node failures. Via a cut-based analysis of the information flow graph, we obtain a lower bound of maintenance bandwidth based on MCR. For MCR, we also propose a transmission scheme and design a linear network coding scheme based on (?, ?) strong-MDS code, which is a generalization of (?, ?) MDS code. We prove that the maintenance bandwidth based on our transmission and coding schemes matches the lower bound, so the lower bound is tight and the transmission scheme and coding scheme for MCR are optimal. We also give numerical comparisons of MCR with other redundancy recovery mechanisms in storage cost and maintenance bandwidth to show the advantage of MCR.

A new nanonetwork architecture using flagellated bacteria and catalytic nanomotors

Abstract: Molecular communication has been recently proposed for interconnected nano-scale devices as an alternative to classical communication paradigms such as electromagnetic waves, acoustic or optical communication. In this novel approach, the information is encoded as molecules that are transported between nano-scale devices within different distances. For short distances (nm-mm ranges) there exist molecular motors and calcium signaling techniques to realize the communication. For long distances (mm-m ranges), pheromones are used to transport information. In this work, the medium-range is explored to cover distances from ?m to mm and a molecular network architecture is proposed to realize the communication between nano-machines that can be deployed over different (short, medium and long) distances. In addition, two new communication techniques, flagellated bacteria and catalytic nanomotors, are proposed to cover the medium-range. Both techniques are based on the transport of DNA encoded information between emitters and receivers by means of a physical carrier. Finally, a qualitative comparison of both communication techniques is carried out and some future research topics are pointed out.

Utility-based asynchronous flow control algorithm for wireless sensor networks

Abstract: In this paper, we formulate a flow control optimization problem for wireless sensor networks with lifetime constraint and link interference in an asynchronous setting. Our formulation is based on the network utility maximization framework, in which a general utility function is used to characterize the network performance such as throughput. To solve the problem, we propose a fully asynchronous distributed algorithm based on dual decomposition, and theoretically prove its convergence. The proposed algorithm can achieve the maximum utility. Extensive simulations are conducted to demonstrate the efficiency of our algorithm and validate the analytical results.

Random-walk based approach to detect clone attacks in wireless sensor networks

Abstract: Wireless sensor networks (WSNs) deployed in hostile environments are vulnerable to clone attacks. In such attack, an adversary compromises a few nodes, replicates them, and inserts arbitrary number of replicas into the network. Consequently, the adversary can carry out many internal attacks. Previous solutions on detecting clone attacks have several drawbacks. First, some of them require a central control, which introduces several inherent limits. Second, some of them are deterministic and vulnerable to simple witness compromising attacks. Third, in some solutions the adversary can easily learn the critical witness nodes to start smart attacks and protect replicas from being detected. In this paper, we first show that in order to avoid existing drawbacks, replica-detection protocols must be non-deterministic and fully distributed (NDFD), and fulfill three security requirements on witness selection. To our knowledge, only one existing protocol, Randomized Multicast, is NDFD and fulfills the requirements, but it has very high communication overhead. Then, based on random walk, we propose two new NDFD protocols, RAndom WaLk (RAWL) and Table-assisted RAndom WaLk (TRAWL), which fulfill the requirements while having only moderate communication and memory overheads. The random walk strategy outperforms previous strategies because it distributes a core step, the witness selection, to every passed node of random walks, and then the adversary cannot easily find out the critical witness nodes. We theoretically analyze the required number of walk steps for ensuring detection. Our simulation results show that our protocols outperform an existing NDFD protocol with the lowest overheads in witness selection, and TRAWL even has lower memory overhead than that protocol. The communication overheads of our protocols are higher but are affordable considering their security benefits.

Existence and Construction of Capacity-Achieving Network Codes for Distributed Storage

Abstract: In a distributed storage system based on erasure coding, when a storage node fails, repairing the erasure code incurs some network traffic. Previous work has characterized the fundamental tradeoff between storage efficiency and repair network bandwidth. This was done via a cut-based analysis on a graph that models the evolution of information flow in the storage system subject to arbitrary sequences of node failures/repairs. This paper presents techniques for constructing network codes that achieve the optimal tradeoff between storage efficiency and repair network bandwidth. The challenge here is that network coding is applied over an unbounded graph with an unbounded number of receivers. It is shown in this paper that optimal codes can be constructed over a finite field whose size depends only on the maximum number of nodes at any instant, but independent of how many failures/repairs can happen. Key to the code construction is a "path-weaving" procedure that leads to inductive existence proof and code construction.

Autonomic traffic engineering for network robustness

Abstract: The continuously increasing complexity of communication networks and the increasing diversity and unpredictability of traffic demand has led to a consensus view that the automation of the management process is inevitable. Currently, network and service management techniques are mostly manual, requiring human intervention, and leading to slow response times, high costs, and customer dissatisfaction. In this paper we present AutoNet, a self-organizing management system for core networks where robustness to environmental changes, namely traffic shifts, topology changes, and community of interest is viewed as critical. A framework to design robust control strategies for autonomic networks is proposed. The requirements of the network are translated to graph-theoretic metrics and the management system attempts to automatically evolve to a stable and robust control point by optimizing these metrics. The management approach is inspired by ideas from evolutionary science where a metric, network criticality, measures the survival value or robustness of a particular network configuration. In our system, network criticality is a measure of the robustness of the network to environmental changes. The control system is designed to direct the evolution of the system state in the direction of increasing robustness. As an application of our framework, we propose a traffic engineering method in which different paths are ranked based on their robustness measure, and the best path is selected to route the flow. The choice of the path is in the direction of preserving the robustness of the network to the unforeseen changes in topology and traffic demands. Furthermore, we develop a method for capacity assignment to optimize the robustness of the network.

Orthogonal frequency division multiple access PON (OFDMA-PON) for colorless upstream transmission beyond 10 Gb/s

Abstract: In this paper, we overview the fundamental principles of next-generation optical Orthogonal Frequency Division Multiple Access (OFDMA)-PON systems, with a particular focus on upstream architectures capable of achieving 10+ Gb/s colorless upstream transmission. We also propose a novel OFDMA-PON architecture that satisfies these requirements and is capable of exceeding 10 Gb/s upstream transmission over a single wavelength. It is first analytically shown that optical carrier suppression at the optical network units (ONUs) combined with coherent detection at the optical line terminal (OLT) successfully eliminates both in- and cross-polarization beating noise that would otherwise be generated at the OLT and would fundamentally limit upstream transmission performance. A centralized light source OFDM-based PON architecture with source-free ONUs and OLTside coherent detection is then presented and experimentally verified to achieve 20 Gb/s/λ transmission over a class B+ optical distribution network (20 km SSMF with an additional 1:32 optical split.) By thus providing very high-speed, flexible, colorless upstream transmission, the proposed architecture is an attractive candidate for next-generation PON systems capable of cost-efficiently delivering heterogeneous services.

Network lifetime optimization in wireless sensor networks

Abstract: Network lifetime (NL) is a critical metric in the design of energy-constrained wireless sensor networks (WSNs). In this paper, we investigate a joint optimal design of the physical, medium access control (MAC) and routing layers to maximize NL of a multiple-sources and single-sink (MSSS) WSN with energy constraints. The problem of NL maximization (NLM) can be formulated as a mixed integer-convex optimization problem with adoption of time division multiple access (TDMA) technique. When the integer constraints are relaxed to take real values, the problem can be transformed into a convex problem and the solution achieves the upper bounds. We provide an analytical framework for the relaxed NLM problem of a WSN in general planar topology. We first restrict the topologies to the planar networks on a small scale, including triangle and regular quadrangle topologies. In this special case, we employ the Karush-Kuhn-Tucker (KKT) optimality conditions to derive analytical expressions of the globally optimal NL, which take the influence of data rate, link access and routing into account. To handle larger scale planar networks, an iterative algorithm is proposed using the D&C approach. Numerical results illustrate that the proposed algorithm can be extended to the large planar case and its performance is close to globally optimal performance.

A systematic framework for dynamically optimizing multi-user wireless video transmission

Abstract: In this paper, we systematically formulate the problem of multi-user wireless video transmission as a multi-user Markov decision process (MUMDP) by explicitly considering the users' heterogeneous video traffic characteristics, time-varying network conditions as well as, importantly, the dynamic coupling among the users' resource allocations across time, which are often ignored in existing multi-user video transmission solutions. To comply with the decentralized wireless networks' architecture, we propose to decompose the MUMDP into multiple local MDPs using Lagrangian relaxation. Unlike in conventional multi-user video transmission solutions stemming from the network utility maximization framework, the proposed decomposition enables each wireless user to individually solve its own local MDP (i.e. dynamic single-user cross-layer optimization) and the network coordinator to update the Lagrangian multipliers (i.e. resource prices) based on not only current, but also the future resource needs of all users, such that the long-term video quality of all users is maximized. This MUMDP solution provides us the necessary foundations and structures for solving multiuser video communication problems. However, to implement this framework in practice requires statistical knowledge of the experienced environment dynamics, which is often unavailable before transmission time. To overcome this obstacle, we propose a novel online learning algorithm, which allows the wireless users to simultaneously update their policies at multiple states during each time slot. This is different from conventional learning solutions, which often update the current visited state per time slot. The proposed learning algorithm can significantly improve the learning performance, thereby dramatically improving the video quality experienced by the wireless users over time. Our simulation results demonstrate the efficiency of the proposed MUMDP framework as compared to conventional multi-user video transmission solutions.

Scalable video multicast in cognitive radio networks

Abstract: We investigate the problem of scalable video multicast in emerging cognitive radio (CR) networks. Although considerable advances have been made in CR research, such important problems have not been well studied. Naturally, 'bandwidth hungry' multimedia applications are excellent candidates for fully capitalizing the potential of CRs. We propose a crosslayer optimization approach to multicast video in CR networks. Specifically, we consider an infrastructure-based CR network collocated with N primary networks and model CR video multicast over the N channels as a mixed integer nonlinear programming (MINLP) problem. The objective is three-fold: to optimize the overall received video quality; to achieve proportional fairness among multicast users; and to keep the interference to primary users below a prescribed threshold. We propose a sequential fixing algorithm and a greedy algorithm to solve the MINLP, while the latter has low complexity and proven optimality gap. Our simulations with MPEG-4 fine grained scalability (FGS) video demonstrate the efficacy and superior performance of the proposed algorithms.

Statistical QoS provisionings for wireless unicast/multicast of multi-layer video streams

Abstract: Due to the time-varying wireless channels, deterministic quality of service (QoS) is usually difficult to guarantee for real-time multi-layer video transmissions in wireless networks. Consequently, statistical QoS guarantees have become an important alternative in supporting real-time video transmissions. In this paper, we propose an efficient framework to model the statistical delay QoS guarantees, in terms of QoS exponent, effective bandwidth/capacity, and delay-bound violation probability, for multi-layer video transmissions over wireless fading channels. In particular, a separate queue is maintained for each video layer, and the same delay bound and corresponding violation probability threshold are set up for all layers. Applying the effective bandwidth/capacity analyses on the incoming video stream, we obtain a set of QoS exponents for all video layers to effectively characterize this delay QoS requirement.We then develop a set of optimal adaptive transmission schemes to minimize the resource consumption while satisfying the diverse QoS requirements under various scenarios, including video unicast/multicast with and/or without loss tolerance. Simulation results are also presented to demonstrate the impact of statistical QoS provisionings on resource allocations of our proposed adaptive transmission schemes.

The autonomic network architecture (ANA)

Abstract: The objective of autonomic networking is to enable the autonomous formation and parametrization of nodes and networks by letting protocols sense and adapt to the networking environment at run time. Besides its dynamic aspects, a core requirement of autonomic networking is to define a structured framework and execution environment that enables algorithms to operate in a continously changing environment. This paper presents the major design principles of the Autonomic Network Architecture (ANA) and reports on a first implementation. The guiding principle of ANA is to strive for flexibility and genericity at all levels of the architecture. In our approach we explicitly avoid to impose a "one-size-fits-all" architecture (where communication protocols and paradigms are fixed by the architecture). To this end, ANA introduces generic abstractions, for example "information dispatch points" instead of addressable endpoints, as well as communication primitives that support network heterogeneity, adaptability, and evolution. These core abstractions allow for the coexistance of multiple and diverse networking styles and protocols. With the public release of the ANA prototype, we aim at federating autonomics related networking projects, enabling different actors to share, compare, and build upon each other?s work. The ANA runtime can host clean slate network designs as well as legacy Internet technology and serves as a platform for demonstrating autonomic communication principles.

Joint synchronization and localization using TOAs: A linearization based WLS solution

Abstract: Joint synchronization and localization using time of arrival (TOA) measurements is a very important research topic for many wireless ad hoc sensor network applications. For such TOA based joint synchronization and localization, the least square (LS) criterion and its corresponding solution have been shown to exhibit optimum estimation performance but generally at a very high computational complexity. Due to its importance and difficulty, in this paper we consider the issue how to approach the estimation performance of such LS solution at low computational complexity: We propose a low-complexity algorithm, which is based on the linearized equations from TOA measurements and applies a weighted least square (WLS) criterion in a computationally efficient way to closely approach the LS solution in estimation performance; Via analyzing and simulating its estimation performance we evidently demonstrate the proposed algorithm of its superior trade-off between estimation performance and computational complexity. The proposed algorithm is also applicable to similar application areas involving TOA base joint timing and positioning.

Decentralized Coding Algorithms for Distributed Storage in Wireless Sensor Networks

Abstract: We consider large-scale wireless sensor networks with n nodes, out of which k are in possession, (e.g., have sensed or collected in some other way) k information packets. In the scenarios in which network nodes are vulnerable because of, for example, limited energy or a hostile environment, it is desirable to disseminate the acquired information throughout the network so that each of the n nodes stores one (possibly coded) packet so that the original k source packets can be recovered, locally and in a computationally simple way from any k(1 + ?) nodes for some small ? > 0. We develop decentralized Fountain codes based algorithms to solve this problem. Unlike all previously developed schemes, our algorithms are truly distributed, that is, nodes do not know n, k or connectivity in the network, except in their own neighborhoods, and they do not maintain any routing tables.

Harnessing battery recovery effect in wireless sensor networks: Experiments and analysis

Abstract: Many applications of wireless sensor networks rely on batteries. But most batteries are not simple energy reservoirs, and can exhibit battery recovery effect. That is, the deliverable energy in a battery can be self-replenished, if left idling for sufficient time. As a viable approach for energy optimisation, we made several contributions towards harnessing battery recovery effect in sensor networks. 1) We empirically examine the gain of battery runtime of sensor devices due to battery recovery effect, and affirm its significant benefit in sensor networks. We also observe a saturation threshold, beyond which more idle time will contribute only little to battery recovery. 2) Based on our experiments, we propose a Markov chain model to capture battery recovery considering saturation threshold and random sensing activities, by which we can study the effectiveness of duty cycling and buffering. 3) We devise a simple distributed duty cycle scheme to take advantage of battery recovery using pseudo-random sequences, and analyse its trade-off between the induced latency of data delivery and duty cycle rates.

A hybrid reservation/contention-based MAC for video streaming over wireless networks

Abstract: To reserve or not for bursty video traffic over wireless access networks has been a long-debated issue. For uplink transmissions in infrastructure-based wireless networks and peer-to-peer transmissions in mesh or ad-hoc networks, reservation can ensure the Quality-of-Service (QoS) provisioning at the cost of a lower degree of resource utilization. Contention-based Medium Access Control (MAC) protocols are more flexible and efficient in sharing resources by bursty traffic to achieve a higher multiplexing gain, but the performance may degrade severely when the network is congested and collisions occur frequently. More and more wireless standards adopt a hybrid approach, which allows the coexistence of resource reservation and contention-based MAC protocols. However, how to cost-effectively support video traffic using hybrid MAC protocols is still an open issue. In this paper, we first propose how to use hybrid MAC protocols to support video streaming over wireless networks. Then, we quantify the performance of video traffic over wireless networks with contention-only, reservation-only, and hybrid MAC protocols, respectively. Admission regions for video streams with these three approaches are obtained. Using the standard WiMedia MAC protocols as an example, extensive simulations with a commonly-used network simulator (NS-2) and real video traces are conducted to verify the analysis. The analytical and simulation results reveal the tradeoff between reservation and contention-based medium access strategies, and demonstrate the effectiveness of the hybrid approach.

Cross-layer optimization for streaming scalable video over fading wireless networks

Abstract: We present a cross-layer design of transmitting scalable video streams from a base station to multiple clients over a shared fading wireless network by jointly considering the application layer information and the wireless channel conditions. We first design a long-term resource allocation algorithm that determines the optimal wireless scheduling policy in order to maximize the weighted sum of average video quality of all streams. We prove that our algorithm achieves the global optimum even though the problem is not concave in the parameter space. We then devise two on-line scheduling algorithms that utilize the results obtained by the long-term resource allocation algorithm for user and packet scheduling as well as video frame dropping strategy. We compare our schemes with existing video scheduling and buffer management schemes in the literature and simulation results show our proposed schemes significantly outperform existing ones.

Studies of OFDM signal for broadband optical access networks

Abstract: Using orthogonal-frequency-division-multiplexing (OFDM) format for passive optical network (PON) is a subject of great interest for recent research works. OFDM signal has high spectral efficiency, high tolerance to the fiber chromatic dispersion and the high flexibility on both multiple services provisioning and dynamic bandwidth allocation. In this paper we study the use of OFDM signals for optical access networks, including carrier distributed PON, heterogeneous optical wired/wireless network and a 100 Gb/s OFDM-PON. We first quantify the performance of the OFDM signal when subjected to the noise produced by two different Rayleigh backscattering (RB) components that are present in the carrier-distributed PON. Then, based on these results, we also study the possibility of using OFDM for signal remodulation in a long-reach (LR)-PON. We propose carrier-distributed OFDM PONs using a dual-feeder fiber architecture and wavelength-shifting to mitigate the RB noise. Afterwards, we propose heterogeneous optical wired/wireless access networks, combining 10 Gb/s PON and 10 Gb/s OFDM radio-over-fiber (ROF) network. Finally, we propose a 100 Gb/s OFDM-PON using subcarrier multiplexing (SCM).

Distributed target tracking using signal strength measurements by a wireless sensor network

Abstract: Wireless Sensor Networks are well suited for tracking targets carrying RFID tags in indoor environments. Tracking based on the received signal strength indication (RSSI) is by far the cheapest and simplest option, but suffers from secular biases due to effects of multi-path, occlusions and decalibration, as well as large unbiased errors due to measurement noise. We propose a novel algorithm that solves these problems in a distributed, scalable and power-efficient manner. Firstly, our proposal includes a tandem incremental estimator that learns and tracks the radio environment of the network, and provides this knowledge for the use of the tracking algorithm, which eliminates the secular biases due to radio occlusions etc. Secondly, we reduce the unbiased tracking error by exploiting the co-dependencies in the motion of several targets (as in crowds or herds) via a fully distributed and tractable particle filter. We thereby extract a significant 'diversity gain' while still allowing the network to scale seamlessly to a large tracking area. In particular, we avoid the pitfalls of network congestion and severely shortened battery lifetimes that plague procedures based on the joint multi-target probability density.

Improving the efficiency of online upstream scheduling and wavelength assignment in hybrid WDM/TDMA EPON networks

Abstract: Two general approaches have been followed for solving the problem of upstream grant scheduling and wavelength assignment in hybrid WDM/TDMA EPON networks, i.e. the offline and the online one. The latter boasts significantly lower frame delay performance in all cases. Nevertheless, we show that simplistic online schemes do not utilize wavelength resources as efficiently as possible, especially in the case of large differential distances of ONUs from the OLT. We propose and analyze several low- and higher-complexity solutions to overcome those inefficiencies, leading to improved utilization of network capacity and reduced frame delay. All schemes are evaluated and compared using computer simulations.

Constructing low-connectivity and full-coverage three dimensional sensor networks

Abstract: Low-connectivity and full-coverage three dimensional Wireless Sensor Networks (WSNs) have many real-world applications. By low connectivity, we mean there are at least k disjoint paths between any two sensor nodes in a WSN, where k ≤ 4. In this paper, we design a set of patterns to achieve 1-, 2-, 3- and 4-connectivity and full-coverage, and prove their optimality under any value of the ratio of communication range rc over sensing range rs, among regular lattice deployment patterns. We further investigate the evolutions among all the proposed low-connectivity patterns. Finally, we study the proposed patterns under several practical settings.