Showing papers on "Channel allocation schemes published in 2011"

A survey on 3GPP heterogeneous networks

Abstract: As the spectral efficiency of a point-to-point link in cellular networks approaches its theoretical limits, with the forecasted explosion of data traffic, there is a need for an increase in the node density to further improve network capacity. However, in already dense deployments in today's networks, cell splitting gains can be severely limited by high inter-cell interference. Moreover, high capital expenditure cost associated with high power macro nodes further limits viability of such an approach. This article discusses the need for an alternative strategy, where low power nodes are overlaid within a macro network, creating what is referred to as a heterogeneous network. We survey current state of the art in heterogeneous deployments and focus on 3GPP LTE air interface to describe future trends. A high-level overview of the 3GPP LTE air interface, network nodes, and spectrum allocation options is provided, along with the enabling mechanisms for heterogeneous deployments. Interference management techniques that are critical for LTE heterogeneous deployments are discussed in greater detail. Cell range expansion, enabled through cell biasing and adaptive resource partitioning, is seen as an effective method to balance the load among the nodes in the network and improve overall trunking efficiency. An interference cancellation receiver plays a crucial role in ensuring acquisition of weak cells and reliability of control and data reception in the presence of legacy signals.

Practical, real-time, full duplex wireless

Abstract: This paper presents a full duplex radio design using signal inversion and adaptive cancellation. Signal inversion uses a simple design based on a balanced/unbalanced (Balun) transformer. This new design, unlike prior work, supports wideband and high power systems. In theory, this new design has no limitation on bandwidth or power. In practice, we find that the signal inversion technique alone can cancel at least 45dB across a 40MHz bandwidth. Further, combining signal inversion cancellation with cancellation in the digital domain can reduce self-interference by up to 73dB for a 10MHz OFDM signal. This paper also presents a full duplex medium access control (MAC) design and evaluates it using a testbed of 5 prototype full duplex nodes. Full duplex reduces packet losses due to hidden terminals by up to 88%. Full duplex also mitigates unfair channel allocation in AP-based networks, increasing fairness from 0.85 to 0.98 while improving downlink throughput by 110% and uplink throughput by 15%. These experimental results show that a re- design of the wireless network stack to exploit full duplex capability can result in significant improvements in network performance.

Vehicular Channel Characterization and Its Implications for Wireless System Design and Performance

Abstract: To make transportation safer, more efficient, and less harmful to the environment, traffic telematics services are currently being intensely investigated and developed. Such services require dependable wireless vehicle-to-infrastructure and vehicle-to-vehicle communications providing robust connectivity at moderate data rates. The development of such dependable vehicular communication systems and standards requires accurate models of the propagation channel in all relevant environments and scenarios. Key characteristics of vehicular channels are shadowing by other vehicles, high Doppler shifts, and inherent nonstationarity. All have major impact on the data packet transmission reliability and latency. This paper provides an overview of the existing vehicular channel measurements in a variety of important environments, and the observed channel characteristics (such as delay spreads and Doppler spreads) therein. We briefly discuss the available vehicular channel models and their respective merits and deficiencies. Finally, we discuss the implications for wireless system design with a strong focus on IEEE 802.11p. On the road towards a dependable vehicular network, room for improvements in coverage, reliability, scalability, and delay are highlighted, calling for evolutionary improvements in the IEEE 802.11p standard. Multiple antennas at the onboard units and roadside units are recommended to exploit spatial diversity for increased diversity and reliability. Evolutionary improvements in the physical (PHY) and medium access control (MAC) layers are required to yield dependable systems. Extensive references are provided.

Energy-Efficient Design of Sequential Channel Sensing in Cognitive Radio Networks: Optimal Sensing Strategy, Power Allocation, and Sensing Order

Abstract: Energy-efficient design has become increasingly important to battery-powered wireless devices. In this paper, we focus on the energy efficiency of a cognitive radio network, in which a secondary user senses the channels licensed to some primary users sequentially before it decides to transmit. Energy is consumed in both the channel sensing and transmission processes. The energy-efficient design calls for a careful design in the sensing-access strategies and the sensing order, with the sensing strategy specifying when to stop sensing and start transmission, the access strategy specifying the power level to be used upon transmission, and the sensing order specifying the sequence of channel sensing. Hence, the objective of this paper is to identify the sensing-access strategies and the sensing order that achieve the maximum energy efficiency. We first investigate the design when the channel sensing order is given and formulate the above design problem as a stochastic sequential decision-making problem. To solve it, we study another parametric formulation of the original problem, which rewards transmission throughput and penalizes energy consumption. Dynamic programming can be applied to identify the optimal strategy for the parametric problem. Then, by exploring the relationship between the two formulations and making use of the monotonicity property of the parametric formulation, we develop an algorithm to find the optimal sensing-access strategies for the original problem. Furthermore, we study the joint design of the channel sensing order and the sensing-access strategies. Lastly, the performance of the proposed designs is evaluated through numerical results.

Power Allocation Strategies for Target Localization in Distributed Multiple-Radar Architectures

Abstract: Widely distributed multiple radar architectures offer parameter estimation improvement for target localization. For a large number of radars, the achievable localization minimum estimation mean-square error (MSE), with full resource allocation, may extend beyond the predetermined system performance goals. In this paper, performance driven resource allocation schemes for multiple radar systems are proposed. All available antennas are used in the localization process. For a predefined estimation MSE threshold, the total transmitted energy is minimized such that the performance objective is met, while keeping the transmitted power at each station within an acceptable range. For a given total power budget, the attainable localization MSE is minimized by optimizing power allocation among the transmit radars. The Cramer-Rao bound (CRB) is used as an optimization metric for the estimation MSE. The resulting nonconvex optimization problems are solved through relaxation and domain decomposition methods, supporting both central processing at the fusion center and distributed processing. It is shown that uniform or equal power allocation is not necessarily optimal and that the proposed power allocation algorithms result in local optima that provide either better localization MSE for the same power budget, or require less power to establish the same performance in terms of estimation MSE. A physical interpretation of these conclusions is offered.

Optimal Power Allocation Strategies for Fading Cognitive Radio Channels with Primary User Outage Constraint

Abstract: In this paper, we consider a cognitive radio (CR) network where a secondary (cognitive) user shares the spectrum for transmission with a primary (non-cognitive) user over block-fading (BF) channels. It is assumed that the primary user has a constant-rate, constant-power transmission, while the secondary user is able to adapt transmit power and rate allocation over different fading states based on the channel state information (CSI) of the CR network. We study a new type of constraint imposed over the secondary transmission to protect the primary user by limiting the maximum transmission outage probability of the primary user to be below a desired target. We derive the optimal power allocation strategies for the secondary user to maximize its ergodic/outage capacity, under the average/peak transmit power constraint along with the proposed primary user outage probability constraint. It is shown by simulations that the derived new power allocation strategies can achieve substantial capacity gains for the secondary user over the conventional methods based on the interference temperature (IT) constraint to protect the primary transmission, with the same resultant primary user outage probability.

IEEE 802.11ac: Dynamic Bandwidth Channel Access

Abstract: IEEE 802.11ac is enhancing the throughput beyond IEEE 802.11n using the 80 MHz channel bonding technique. In this paper, we first overview the static 40 MHz and the dynamic 20/40 MHz bandwidth channel access schemes defined in 802.11n. We then extend the schemes to the IEEE 802.11ac for the 80 MHz wide channel and study the static and dynamic channel access schemes. The simulation results show that dynamically switching between 20, 40, and 80 MHz bandwidths based on the clear channel assessment (CCA) result of each 20 MHz channel outperforms the static 80 MHz scheme by 85 % in terms throughput when the secondary channels are occupied by the 802.11a stations with moderate traffic loads. The paper also investigates the effects of the secondary channel CCA sensitivity and the primary channel selection on the 802.11ac throughput.

Macro-femto heterogeneous network deployment and management: from business models to technical solutions

Abstract: The femtocell technique can address the poor in-building coverage problem and increase net work capacity cost efficiently. At present, some wireless service providers have launched their femtocell services, although there are still plenty of challenges unsettled. In this article we discuss the business mode in macro-femto heterogeneous networks. We propose three frameworks according to the deployment types of femtocells, which are joint deployment, WSP deployment, and user deployment frameworks. Their unique characteristics, corresponding challenges, and potential solutions are further investigated to provide deeper insight systematically. We also present two schemes for WSP revenue maximization under the WSP deployment framework. The first scheme jointly handles the interference and users' demand satisfaction via cross-tier channel allocation, and the second scheme further considers the optimal pricing selection for accessing different networks.

Joint Subcarrier Pairing and Power Allocation for OFDM Transmission With Decode-and-Forward Relaying

Abstract: In this paper, a point-to-point orthogonal-frequency- division multiplexing (OFDM) system with a decode-and- forward (DF) relay is considered. The transmission consists of two hops. The source transmits in the first hop, and the relay transmits in the second hop. Each hop occupies one time slot. The relay is half-duplex, and capable of decoding the message on a particular subcarrier in one time slot, and re-encoding and forwarding it on a different subcarrier in the next time slot. Thus, each message is transmitted on a pair of subcarriers in two hops. It is assumed that the destination is capable of combining the signals from the source and the relay pertaining to the same message. The goal is to maximize the weighted sum rate of the system by jointly optimizing subcarrier pairing and power allocation on each subcarrier in each hop. The weighting of the rates is to take into account the fact that different subcarriers may carry signals for different services. Both total and individual power constraints for the source and the relay are investigated. For the situations where the relay does not transmit on some subcarriers because doing so does not improve the weighted sum rate, we further allow the source to transmit new messages on these idle subcarriers. To the best of our knowledge, such a joint optimization inclusive of the destination combining has not been discussed in the literature. The problem is first formulated as a mixed integer programming problem. It is then transformed to a convex optimization problem by continuous relaxation, and solved in the dual domain. Based on the optimization results, algorithms to achieve feasible solutions are also proposed. Simulation results show that the proposed algorithms almost achieve the optimal weighted sum rate and outperform the existing methods in various channel conditions.

Power and Channel Allocation for Cooperative Relay in Cognitive Radio Networks

Abstract: In this paper, we investigate power and channel allocation for cooperative relay in a three-node cognitive radio network. Different from conventional cooperative relay channels, cognitive radio relay channels can be divided into three categories: direct, dual-hop, and relay channels, which provide three types of parallel end-to-end transmission. In the context, those spectrum bands available at all three nodes may either perform relay diversity transmission or assist the transmission in direct or dual-hop channels. On the other hand, the relay node involves both dual-hop and relay diversity transmission. In this paper, we develop power and channel allocation approaches for cooperative relay in cognitive radio networks that can significantly improve the overall end-to-end throughput. We further develop a low complexity approach that can obtain most of the benefits from power and channel allocation with minor performance loss.

The impact of channel bonding on 802.11n network management

Abstract: The IEEE 802.11n standard allows wireless devices to operate on 40MHz-width channels by doubling their channel width from standard 20MHz channels, a concept called channel bonding. Increasing channel width should increase bandwidth, but it comes at the cost of decreased transmission range and greater susceptibility to interference. However, with the incorporation of MIMO (Multiple-Input Multiple-Output) technology in 802.11n, devices can now exploit the increased transmission rates from wider channels at a reduced sacrifice to signal quality and range. The goal of our work is to understand the characteristics of channel bonding in 802.11n networks and the factors that influence that behavior to ultimately be able to predict behavior so that network performance is maximized. We discuss the impact of channel bonding choices as well as the effects of both co-channel and adjacent channel interference on network performance. We discover that intelligent channel bonding decisions rely not only on a link's signal quality, but also on the strength of neighboring links and their physical rates.

QoS Provisioning for Heterogeneous Services in Cooperative Cognitive Radio Networks

Abstract: In this paper, we propose a spectrum allocation framework that jointly considers the Quality-of-Service (QoS) provisioning for heterogeneous secondary Real-Time (RT) and Non-Real Time (NRT) users, the spectrum sensing, spectrum access decision, channel allocation, and call admission control in distributed cooperative Cognitive Radio Networks (CRNs). Giving priority to the RT users with QoS requirements in terms of the dropping and blocking probabilities, a number of the identified available channels are allocated to the optimum number of the RT users that can be admitted into the network, while the remaining identified available channels are allocated adaptively to the optimum number of the NRT users considering the spectrum sensing and utilization indispensability. Extensive analytical and simulation results are provided to demonstrate the effectiveness of the proposed QoS-based spectrum resource allocation framework.

Optimal Bandwidth and Power Allocation for Sum Ergodic Capacity Under Fading Channels in Cognitive Radio Networks

Abstract: This paper studies optimal bandwidth and power allocation in a cognitive radio network where multiple secondary users (SUs) share the licensed spectrum of a primary user (PU) under fading channels using the frequency division multiple access scheme. The sum ergodic capacity of all the SUs is taken as the performance metric of the network. Besides the peak/average transmit power constraints at the SUs and the peak/average interference power constraint imposed by the PU, total bandwidth constraint of the licensed spectrum is also taken into account. Optimal bandwidth allocation is derived in closed-form for any given power allocation. The structures of optimal power allocations are also derived under all possible combinations of the aforementioned power constraints. These structures indicate the possible numbers of users that transmit at nonzero power but below their corresponding peak powers, and show that other users do not transmit or transmit at their corresponding peak powers. Based on these structures, efficient algorithms are developed for finding the optimal power allocations.

Optimal Channel Access Management with QoS Support for Cognitive Vehicular Networks

Abstract: We consider the problem of optimal channel access to provide quality of service (QoS) for data transmission in cognitive vehicular networks. In such a network, the vehicular nodes can opportunistically access the radio channels (referred to as shared-use channels) which are allocated to licensed users. Also, they are able to reserve a channel for dedicated access (referred to as exclusive-use channel) for data transmission. A channel access management framework is developed for cluster-based communication among vehicular nodes. This framework has three components: opportunistic access to shared-use channels, reservation of exclusive-use channel, and cluster size control. A hierarchical optimization model is then developed for this framework to obtain the optimal policy. The objective of the optimization model is to maximize the utility of the vehicular nodes in a cluster and to minimize the cost of reserving exclusive-use channel while the QoS requirements of data transmission (for vehicle-to-vehicle and vehicle-to-roadside communications) are met, and also the constraint on probability of collision with licensed users is satisfied. This hierarchical optimization model comprises of two constrained Markov decision process (CMDP) formulations - one for opportunistic channel access, and the other for joint exclusive-use channel reservation and cluster size control. An algorithm is presented to solve this hierarchical optimization model. Performance evaluation results show the effectiveness of the optimal channel access management policy. The proposed optimal channel access management framework will be useful to support mobile computing and intelligent transportation system (ITS) applications in vehicular networks.

Asymmetric Cooperative Communications Based Spectrum Leasing via Auctions in Cognitive Radio Networks

Abstract: Dynamic spectrum leasing (DSL) was proposed recently as a new paradigm for dynamic spectrum sharing (DSS) in cognitive radio networks (CRN's). In this paper, we propose a new way to encourage primary users to lease their spectrum: The secondary users (SU's) place bids indicating how much power they are willing to spend for relaying the primary signals to their destinations. In this formulation, the primary users achieve power savings due to asymmetric cooperation. We propose and analyze both a centralized and a distributed decision-making architecture for the secondary CRN. In the centralized architecture, a Secondary System Decision Center (SSDC) selects a bid for each primary channel based on optimal channel assignment for SU's. In the decentralized cognitive network architecture, we formulate an auction game-based protocol in which each SU independently places bids for each primary channel and receivers of each primary link pick the bid that will lead to the most power savings. A simple and robust distributed reinforcement learning mechanism is developed to allow the users to revise their bids and to increase their rewards. The performance results show the significant impact of reinforcement learning in both improving spectrum utilization and meeting individual SU performance requirements.

Game Theoretical Approach for Channel Allocation in Wireless Sensor and Actuator Networks

Abstract: In this paper, multi-channel allocation in wireless sensor and actuator networks is formulated as an optimization problem which is NP-hard. In order to efficiently solve this problem, a distributed game based channel allocation (GBCA) Algorithm is proposed by taking into account both network topology and routing information. For both tree/forest routing and non-tree/forest routing scenarios, it is proved that there exists at least one Nash Equilibrium for the problem. Furthermore, the sub- optimality of Nash Equilibrium and the convergence of the Best Response dynamics are also analyzed. Simulation results demonstrate that GBCA significantly reduces the interference and dramatically improves the network performance in terms of delivery ratio, throughput, channel access delay, and energy consumption.

SMALL: A Strategy-proof Mechanism for radio spectrum allocation

Abstract: With the growing deployment of wireless communication technologies, radio spectrum is becoming a scarce resource. Thus mechanisms to efficiently allocate the available spectrum are of interest. In this paper, we model the radio spectrum allocation problem as a sealed-bid reserve auction, and propose SMALL, which is a Strategy-proof Mechanism for radio spectrum ALLocation. Furthermore, we extend SMALL to adapt to multi-radio spectrum buyers, which can bid for more than one radio.

A survey on the channel assignment problem in wireless networks

Abstract: Efficient allocation of channels for wireless communication in different network scenarios has become an extremely important topic of recent research. The main challenge lies in the fact that the channel allocation problem is NP-complete. Because of a maximum allowable time limit imposed in practical situations for allocation of channels, sometimes we may need to be satisfied with a near-optimal solution. In this correspondence, we present a discussion on the various challenges and approaches that have been used by different researchers to solve the problem of channel allocation taking into account different interference issues and efficient utilization of available communication channels for cellular mobile (including multimedia communication) environment and cognitive radio based networks. Copyright © 2010 John Wiley & Sons, Ltd.

On Providing Downlink Services in Collocated Spectrum-Sharing Macro and Femto Networks

Abstract: Femtocells have been considered by the wireless industry as a cost-effective solution not only to improve indoor service providing, but also to unload traffic from already overburdened macro networks. Due to spectrum availability and network infrastructure considerations, a macro network may have to share spectrum with overlaid femtocells. In spectrum-sharing macro and femto networks, inter-cell interference caused by different transmission powers of macrocell base stations (MBSs) and femtocell access points (FAPs), in conjunction with potentially densely deployed femtocells, may create dead spots where reliable services cannot be guaranteed to either macro or femto users. In this paper, based on a thorough analysis of downlink (DL) outage probabilities (OPs) of collocated spectrum-sharing orthogonal frequency division multiple access (OFDMA) based macro and femto networks, we devise a decentralized strategy for an FAP to self-regulate its transmission power level and usage of radio resources depending on its distance from the closest MBS. Simulation results show that the derived closed-form lower bounds of DL OPs are tight, and the proposed decentralized femtocell self-regulation strategy is able to guarantee reliable DL services in targeted macro and femto service areas while providing superior spatial reuse, for even a large number of spectrum-sharing femtocells deployed per cell site.

Efficient HetNet implementation using broadband wireless access with fiber-connected massively distributed antennas architecture

Abstract: We introduce a novel HetNet architecture employing fiber-connected distributed antenna systems, named broadband wireless access with fiber-connected massively distributed antennas (BWA-FMDA), which facilitates coordination of resource allocation and interference management. Among various opportunities realized by the proposed approach, our focus in this article is on CoMP for UMTS LTE femto- and picocells, to which we refer as femto-CoMP. Through extensive simulation results we demonstrate the superior performance gain of a femto-CoMP HetNet over independent femto- and picocell operation in traditional HetNet scenarios. We analyze both link- and system-level feasible throughput as well as scheduling delay for round-robin and proportional fair schedulers.

Residual energy aware channel assignment in cognitive radio sensor networks

Abstract: We investigate the channel assignment problem in a cluster-based multi-channel cognitive radio sensor network in this paper. Due to the inherent power and resource constraints of sensor networks, energy efficiency is the primary concern for network design. An R-coefficient is developed to estimate the predicted residual energy using sensor information (current residual energy and expected energy consumption) and channel conditions (primary user behavior). We examine three channel assignment approaches: Random pairing, Greedy channel search and Optimization-based channel assignment. The last two exploit R-coefficient to obtain a residual energy aware channel assignment solution. Simulation results show that R-coefficient-based approaches lead to better performance in terms of energy consumption and residual energy balance. Optimization-based channel assignment outperforms the other two approaches with respect to network lifetime.

Throughput Maximizing Multiuser Scheduling with Adjustable Fairness

Abstract: We address the problem of downlink multiuser scheduling in practical wireless networks under a desired fairness constraint. Wireless networks such as LTE, WiMAX and WiFi provide partial channel knowledge at the base station/access point by means of quantized user equipment feedback. Specifically in 3GPP's LTE, the Channel Quality Indicator (CQI) feedback provides time-frequency selective information on achievable rates. This knowledge enables the scheduler to achieve multiuser diversity gains by assigning resources to users with favourable channel conditions. However, only focusing on the possible diversity gains leads to unfair treatment of the individual users. To overcome this situation we propose a method for multiuser scheduling that operates on the boundary of the achievable multiuser rate region while guaranteeing a desired long term average fairness. Our method is based on a sum utility maximization of the alpha-fair utility functions. To obtain a given fairness, quantified with Jain's fairness index, it is necessary to find an appropriate α, which we obtain from the observed CQI probability mass function (pmf).

Dynamic QoS-Based Bandwidth Allocation Framework for Broadband Wireless Networks

Abstract: Broadband wireless communication systems, namely, Worldwide Interoperability for Microwave Access (WiMAX) and Long-Term Evolution (LTE), promise to revolutionize the mobile users wireless experience by offering many of the services and features promised by fourth-generation (4G) wireless systems, such as supporting multimedia services with high data rates and wide coverage area, as well as all-Internet Protocol (IP) with security and quality-of-service (QoS) support. These systems, however, require proficient radio resource management (RRM) schemes to provide the aforementioned features they promise. In this paper, we propose a new framework, which is called dynamic QoS-based bandwidth allocation (DQBA), to support heterogeneous traffic with different QoS requirements in WiMAX networks. The DQBA framework operates as such; it dynamically changes the bandwidth allocation (BA) for ongoing and new arrival connections based on traffic characteristics and service demand. The DQBA aims at maximizing the system capacity by efficiently utilizing its resources and by being fair, practical, and in compliance with the IEEE 802.16 standard specifications. To achieve its objectives, DQBA employs a flexible architecture that combines the following related components: 1) a two-level packet scheduler scheme; 2) an efficient call admission control policy; and 3) a dynamic BA mechanism. Simulation results and comparisons with existing schemes show the effectiveness and strengths of the DQBA framework in delivering promising QoS and being fair to all classes of services in a WiMAX network.

Channel allocation in wireless data center networks

Abstract: Unbalanced traffic demands of different data center applications are an important issue in designing Data center networks (DCNs). In this paper, we present our exploratory investigation of utilizing wireless transmissions in DCNs. Our work aims to solve the congestion problem caused by a few hot nodes to improve the global performance. We model the wireless transmissions in a DCN by considering both the wireless interference and the adaptive transmission rate. Moreover, both throughput and job completion time are taken into account to evaluate the impact of wireless transmissions on the global performance. Based on this model, we formulate the channel allocation in wireless DCNs as an optimization problem and design a genetic algorithm (GA) based approach to address it. To demonstrate the effectiveness of wireless transmissions as well as our GA-based algorithm in a wireless DCN, extensive simulation study is carried out and the results validate our design.

Downlink Subchannel and Power Allocation in Multi-Cell OFDMA Cognitive Radio Networks

Abstract: We propose a novel subchannel and transmission power allocation scheme for multi-cell orthogonal frequency-division multiple access (OFDMA) networks with cognitive radio (CR) functionality. The multi-cell CR-OFDMA network not only has to control the interference to the primary users (PUs) but also has to coordinate inter-cell interference in itself. The proposed scheme allocates the subchannels to the cells in a way to maximize the system capacity, while at the same time limiting the transmission power on the subchannels on which the PUs are active. We formulate this joint subchannel and transmission power allocation problem as an optimization problem. To efficiently solve the problem, we divide it into multiple subproblems by using the dual decomposition method, and present the algorithms to solve these subproblems. The resulting scheme efficiently allocates the subchannels and the transmission power in a distributed way. The simulation results show that the proposed scheme provides significant improvement over the traditional fixed subchannel allocation scheme in terms of system throughput.

Partially overlapping channel assignment based on “node orthogonality” for 802.11 wireless networks

Abstract: In this study, we investigate the problem of partially overlapping channel assignment to improve the performance of 802.11 wireless networks. We first derive a novel interference model that takes into account both the adjacent channel separation and the physical distance of the two nodes employing adjacent channels. This model defines “node orthogonality”, which states that two nodes over adjacent channels are orthogonal if they are physically sufficiently separated. We propose an approximate algorithm MICA to minimize the total interference for throughput maximization. Extensive simulation study has been performed to validate our design and to compare the performances of our algorithm with those of the state-of-the-art.

Sequential learning for optimal monitoring of multi-channel wireless networks

Abstract: We consider the problem of optimally assigning p sniffers to K channels to monitor the transmission activities in a multi-channel wireless network. The activity of users is initially unknown to the sniffers and is to be learned along with channel assignment decisions while maximizing the benefits of this assignment, resulting in the fundamental trade-off between exploration versus exploitation. We formulate it as the linear partial monitoring problem, a super-class of multi-armed bandits. As the number of arms (sniffer-channel assignments) is exponential, novel techniques are called for, to allow efficient learning. We use the linear bandit model to capture the dependency amongst the arms and develop two policies that take advantage of this dependency. Both policies enjoy logarithmic regret bound of time-slots with a term that is sub-linear in the number of arms.

Keys Through ARQ: Theory and Practice

Abstract: This paper develops a novel framework for sharing secret keys using the Automatic Repeat reQuest (ARQ) protocol. We first characterize the underlying information theoretic limits, under different assumptions on the channel spatial and temporal correlation function. Our analysis reveals a novel role of “dumb antennas” in overcoming the negative impact of spatial correlation on the achievable secrecy rates. We further develop an adaptive rate allocation policy, which achieves higher secrecy rates in temporally correlated channels, and explicit constructions for ARQ secrecy coding that enjoy low implementation complexity. Building on this theoretical foundation, we propose a unified framework for ARQ-based secrecy in Wi-Fi networks. By exploiting the existing ARQ mechanism in the IEEE 802.11 standard, we develop security overlays that offer strong security guarantees at the expense of only minor modifications in the medium access layer. Our numerical results establish the achievability of nonzero secrecy rates even when the eavesdropper channel is less noisy, on the average, than the legitimate channel, while our Linux-based prototype demonstrates the efficiency of our ARQ overlays in mitigating all known, passive and active, Wi-Fi attacks at the expense of a minimal increase in the link setup time and a small loss in throughput.

Spectrum and Energy Aware Routing Protocol for Cognitive Radio Ad Hoc Networks

Abstract: Throughput maximization is one of the core challenges in cognitive radio ad hoc networks (CRANs), where local spectrum resources are changing over time and locations. This paper proposes a spectrum and energy aware routing (SER) protocol for CRANs, which involves spectrum aware, and energy-efficient route selection, and channel-timeslot assignment. A good routing protocol should be aware of the interference as well as the end-to-end delay. The proposed joint spectrum and energy aware routing with channel-timeslot assignment can balance the energy consumption, eliminates contention between users, and decompose contending traffics over different channels and timeslots. As a result, the proposed scheme leads to significant increases in network throughput and decreases the end-to-end delay. The simulation results show the effectiveness of our proposed approach with good generalization ability.