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Optimizing Client Association in 60 GHz Wireless Access Networks Optimizing Client Association in 60 GHz Wireless Access Networks

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Date added: 12/30/2013
Date modified: 12/30/2013
Filesize: 436.53 kB
Downloads: 770

MillimeterWave communications in the 60 GHz band are considered one of the key technologies for enabling multi-gigabit wireless access. However, the high propagation loss in such a band poses major obstacles to the optimal utilization of the wireless resources, where the problem of efficient client association to access points (APs) is of vital importance. In this paper, the client association in 60 GHz wireless access networks is investigated. The AP utilization and the quality of the rapidly vanishing communication links are the control parameters. Because of the tricky non-convex and combinatorial nature of the client association optimization problem, a novel solution method is developed to guarantee balanced and fair resource allocation. A new distributed, lightweight and easy to implement association algorithm, based on Lagrangian duality theory and subgradient methods, was proposed. It is shown that the algorithm is asymptotically optimal, that is, the relative duality gap diminishes to zero as the number of clients increases. Both theoretical and numerical results evince numerous useful properties of the algorithm, such as fast convergence, scalability, time efficiency, and fair execution in comparison to existing approaches. It is concluded that the proposed solution can be applied in the forthcoming 60 GHz wireless access networks.

A Distributed Estimation Method for Sensor Networks Based on Pareto Optimization A Distributed Estimation Method for Sensor Networks Based on Pareto Optimization

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Date added: 12/30/2013
Date modified: 12/30/2013
Filesize: 286 Bytes
Downloads: 1222

A novel distributed estimation method for sensor networks is proposed. The goal is to track a time-varying signal that is jointly measured by a network of sensor nodes despite the presence of noise: each node computes its local estimate as a weighted sum of its own and its neighbors' measurements and estimates and updates its weights to minimize both the variance and the mean of the estimation error by means of a suitable Pareto optimization problem. The estimator does not rely on a central coordination: both parameter optimization and estimation are distributed across the nodes. The performance of the distributed estimator is investigated in terms of estimation bias and estimation error. Moreover, an upper bound of the bias is provided. The effectiveness of the proposed estimator is illustrated via computer simulations and the performances are compared with other distributed schemes previously proposed in the literature. The results show that the estimation quality is comparable to that of one of the best existing distributed estimation algorithms, guaranteeing lower computational cost and time.

Multiple Description Analog Joint Source-Channel Coding to Exploit the Diversity in Parallel Channel Multiple Description Analog Joint Source-Channel Coding to Exploit the Diversity in Parallel Channel

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Date added: 12/28/2013
Date modified: 12/28/2013
Filesize: 286 Bytes
Downloads: 1159

The complexity and delay introduced by efficient digital coding strategies may be a barrier in some real-time communications. In this sense, these last years, joint source-channel coding schemes based on analog mappings have gained prominence precisely for their simplicity and their implicit low delay. In this work, analog mappings originally designed for point-to-point communications are adapted to the case of parallel channels by following the multiple description strategy traditionally used in source coding. In principle, the coding scheme is designed to transmit over parallel AWGN on-off channels, which are characterized by the possibility of having failures. We also show that our scheme performs satisfactorily over slow Rayleigh fading parallel channels.

Weighted Sum-Rate Maximization for MISO Downlink Cellular Networks via Branch and Bound Weighted Sum-Rate Maximization for MISO Downlink Cellular Networks via Branch and Bound

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Date added: 12/24/2013
Date modified: 12/28/2013
Filesize: 286 Bytes
Downloads: 1353

The problem of weighted sum-rate maximization (WSRMax) in multicell downlink multiple-input single-output (MISO) systems is considered. The problem is known to be NP-hard. We propose a method, based on branch and bound technique, which solves globally the nonconvex WSRMax problem with an optimality certificate. Specifically, the algorithm computes a sequence of asymptotically tight upper and lower bounds and it terminates when the difference between them falls below a pre-specified tolerance. Novel bounding techniques via conic optimization are introduced and their efficiency is demonstrated by numerical simulations. The proposed method can be used to provide performance benchmarks by back-substituting it into many existing network design problems which relies on WSRMax problem. The method proposed here can be easily extended to maximize any system performance metric that can be expressed as a Lipschitz continuous and increasing function of signal-to-interference-plus-noise ratio.

Wireless Sensor Network for Spectrum Cartography Based on Kriging Interpolation Wireless Sensor Network for Spectrum Cartography Based on Kriging Interpolation

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Date added: 08/30/2013
Date modified: 08/30/2013
Filesize: 286 Bytes
Downloads: 1476

Dynamic spectrum access with Cognitive Radio (CR) network is a promising approach to increase the efficiency of spectrum usage. To allow the optimization of resource allocation and transmission adaptation techniques, each CR terminal needs to acquire awareness of the state of the time-frequency-location varying radio spectrum. In this paper we present a Spectrum Cartography (SC) approach where CR terminals are supported by a fixed wireless sensor network (WSN) to estimate and update the Power Spectral Density (PSD) over the area of interest. The wireless sensors collaborate to estimate the spatial distribution of the received power at a given frequency using either a centralized or a distributed Kriging (DK) algorithm. We present an analysis of the semivariogram models used to estimate the spatial statistics of wireless PSD distributions. The performance of the centralized and DK algorithms are evaluated by simulating different realizations of the PSD and the results are compared with classical interpolating schemes varying the density of nodes in the area and the number of nodes used for local estimation.

Modeling and Optimization of the IEEE 802.15.4 Protocol for Reliable and Timely Communications Modeling and Optimization of the IEEE 802.15.4 Protocol for Reliable and Timely Communications

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Date added: 08/16/2013
Date modified: 08/16/2013
Filesize: 286 Bytes
Downloads: 1378

Distributed processing through ad hoc and sensor networks is having a major impact on scale and applications of computing. The creation of new cyber-physical services based on wireless sensor devices relies heavily on how well communication protocols can be adapted and optimized to meet quality constraints under limited energy resources. The IEEE 802.15.4 medium access control protocol for wireless sensor networks can support energy efficient, reliable, and timely packet transmission by a parallel and distributed tuning of the medium access control parameters. Such a tuning is difficult, because simple and accurate models of the influence of these parameters on the probability of successful packet transmission, packet delay, and energy consumption are not available. Moreover, it is not clear how to adapt the parameters to the changes of the network and traffic regimes by algorithms that can run on resource-constrained devices. In this paper, a Markov chain is proposed to model these relations by simple expressions without giving up the accuracy. In contrast to previous work, the presence of limited number of retransmissions, acknowledgments, unsaturated traffic, packet size, and packet copying delay due to hardware limitations is accounted for. The model is then used to derive a distributed adaptive algorithm for minimizing the power consumption while guaranteeing a given successful packet reception probability and delay constraints in the packet transmission. The algorithm does not require any modification of the IEEE 802.15.4 medium access control and can be easily implemented on network devices. The algorithm has been experimentally implemented and evaluated on a testbed with off-the-shelf wireless sensor devices. Experimental results show that the analysis is accurate, that the proposed algorithm satisfies reliability and delay constraints, and that the approach reduces the energy consumption of the network under both stationary and transient conditions. Specifically, even if the number of devices and traffic configuration change sharply, the proposed parallel and distributed algorithm allows the system to operate close to its optimal state by estimating the busy channel and channel access probabilities. Furthermore, results indicate that the protocol reacts promptly to errors in the estimation of the number of devices and in the traffic load that can appear due to device mobility. It is also shown that the effect of imperfect channel and carrier sensing on system performance heavily depends on the traffic load and limited range of the protocol parameters.

Modeling and stability analysis of hybrid multiple access in the IEEE 802.15.4 protocol Modeling and stability analysis of hybrid multiple access in the IEEE 802.15.4 protocol

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Date added: 08/16/2013
Date modified: 08/16/2013
Filesize: 286 Bytes
Downloads: 1348

To offer flexible quality of service to several classes of applications, the medium access control (MAC) protocol of IEEE 802.15.4 wireless sensor networks (WSNs) combines the advantages of a random access with contention with a time division multiple access (TDMA) without contention. Understanding reliability, delay, and throughput is essential to characterizing the fundamental limitations of the MAC and optimizing its parameters. Nevertheless, there is not yet a clear investigation of the achievable performance of hybrid MAC. In this article, an analytical framework for modeling the behavior of the hybrid MAC protocol of the IEEE 802.15.4 standard is proposed. The main challenge for an accurate analysis is the coexistence of the stochastic behavior of the random access and the deterministic behavior of the TDMA scheme. The analysis is done in three steps. First, the contention access scheme of the IEEE 802.15.4 exponential back-off process is modeled through an extended Markov chain that takes into account channel, retry limits, acknowledgements, unsaturated traffic, and superframe period. Second, the behavior of the TDMA access scheme is modeled by another Markov chain. Finally, the two chains are coupled to obtain a complete model of the hybrid MAC. By using this model, the network performance in terms of reliability, average packet delay, average queuing delay, and throughput is evaluated through both theoretical analysis and experiments. The protocol has been implemented and evaluated on a testbed with off-the-shelf wireless sensor devices to demonstrate the utility of the analysis in a practical setup. It is established that the probability density function of the number of received packets per superframe follows a Poisson distribution. It is determined under which conditions the guaranteed time slot allocation mechanism of IEEE 802.15.4 is stable. It is shown that the mutual effect between throughput of the random access and the TDMA scheme for a fixed superframe length is critical to maximizing the overall throughput of the hybrid MAC. In high traffic load, the throughput of the random access mechanism dominates over TDMA due to the constrained use of TDMA in the standard. Furthermore, it is shown that the effect of imperfect channels and carrier sensing on system performance heavily depends on the traffic load and limited range of the protocol parameters. Finally, it is argued that the traffic generation model established in this article may be used to design an activation timer mechanism in a modified version of the CSMA/CA algorithm that guarantees a stable network performance.

Discrete Stochastic Optimization Based Parameter Estimation for Modeling Partially Observed WLAN... Discrete Stochastic Optimization Based Parameter Estimation for Modeling Partially Observed WLAN...

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Date added: 08/16/2013
Date modified: 12/24/2013
Filesize: 286 Bytes
Downloads: 1355

Modeling and parameter estimation of spectrum usage in the ISM band would allow the competing networking technologies to adjust their medium access control accordingly, leading to the more efficient use of the shared spectrum. In this paper we address the problem of WLAN spectrum activity model parameter estimation. We propose a solution based on discrete stochastic optimization, that allows accurate spectrum activity modeling and can be implemented even in wireless sensor nodes with limited computational and energy resources.

Non-cooperative power allocation game with imperfect sensing information for cognitive radio Non-cooperative power allocation game with imperfect sensing information for cognitive radio

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Date added: 07/07/2013
Date modified: 12/28/2013
Filesize: 286 Bytes
Downloads: 1501

In this paper, we consider a sensing-based spectrum sharing scenario and present an efficient decentralized algorithm to maximize the total throughput of the cognitive radio users by optimizing jointly both the detection operation and the power allocation, taking into account the influence of the sensing accuracy. This optimization problem can be formulated as a distributed non-cooperative power allocation game, which can be solved by using an alternating direction optimization method. The transmit power budget of the cognitive radio users and the constraint related to the rate-loss of the primary user due to the interference are considered in the scheme. Finally, we use variational inequality theory in order to find the existence and uniqueness of the Nash equilibrium for our proposed distributed non-cooperative game.

Power-constrained sensor selection and routing for cooperative detection in cognitive radios Power-constrained sensor selection and routing for cooperative detection in cognitive radios

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Date added: 07/07/2013
Date modified: 12/28/2013
Filesize: 286 Bytes
Downloads: 1404

Given a spectrum-sensing network, a set of active nodes jointly aggregate sensed data at a preset frequency-band and simultaneously route this information to an arbitrarily chosen querying node through a power-constrained multi-hop path. Locally, each sensor node is assumed to be an energy-based detector. This work focuses on deriving algorithms that jointly optimize sensor selection and cooperative detection from which a power-efficient route to the querying node can be established, and then, a tree routing structure spanning the chosen nodes is constructed under a power budget constraint. Sensor information is sequentially aggregated along this optimized routing structure up to the querying node. Each parent node combines the information coming from each of its child nodes using either log-likelihood ratios or optimal linear weights. This is done with the goal of maximizing, at the querying node, the overall probability of detection for a given probability of false alarm and a given total power budget spent by the sensor network for routing the sensor information. We propose two algorithms: (1) greedy and (2) select-aggregate-forward that provide a trade-off between the detection quality and the power consumption. We provide experimental results that show the outperformance of our algorithms against traditionally proposed routing structures such as the shortest-path-tree.