arXiv subjects

Carlo Fischione

Publications and source records attributed to Carlo Fischione.

At least 109 records · Page 6Linked to original sources

arXiv2016

On the Relay-Fallback Tradeoff in Millimeter Wave Wireless System

Millimeter wave (mmWave) communications systems are promising candidate to support extremely high data rate services in future wireless networks. MmWave communications exhibit high penetration loss (blockage) and require directional transmissions to compensate for severe channel attenuations and for high noise powers. When blockage occurs, there are at least two simple prominent options: 1) switching to the conventional microwave frequencies (fallback option) and 2) using an alternative non-blocked path (relay option). However, currently it is not clear under which conditions and network parameters one option is better than the other. To investigate the performance of the two options, this paper proposes a novel blockage model that allows deriving maximum achievable throughput and delay performance of both options. A simple criterion to decide which option should be taken under which network condition is provided. By a comprehensive performance analysis, it is shown that the right option depends on the payload size, beam training overhead, and blockage probability. For a network with light traffic and low probability of blockage in the direct link, the fallback option is throughput- and delay-optimal. For a network with heavy traffic demands and semi-static topology (low beam-training overhead), the relay option is preferable.

cs.IT↗

arXiv2016

Distributed Resource Allocation Using One-Way Communication with Applications to Power Networks

Typical coordination schemes for future power grids require two-way communications. Since the number of end power-consuming devices is large, the bandwidth requirements for such two-way communication schemes may be prohibitive. Motivated by this observation, we study distributed coordination schemes that require only one-way limited communications. In particular, we investigate how dual descent distributed optimization algorithm can be employed in power networks using one-way communication. In this iterative algorithm, system coordinators broadcast coordinating (or pricing) signals to the users/devices who update power consumption based on the received signal. Then system coordinators update the coordinating signals based on the physical measurement of the aggregate power usage. We provide conditions to guarantee the feasibility of the aggregated power usage at each iteration so as to avoid blackout. Furthermore, we prove the convergence of algorithms under these conditions, and establish its rate of convergence. We illustrate the performance of our algorithms using numerical simulations. These results show that one-way limited communication may be viable for coordinating/operating the future smart grids.

eess.SY↗

arXiv2016

Robustness Analysis for an Online Decentralized Descent Power allocation algorithm

As independent service providers shift from conventional energy to renewable energy sources, the power distribution system will likely experience increasingly significant fluctuation in supply, given the uncertain and intermittent nature of renewable sources like wind and solar energy. These fluctuations in power generation, coupled with time-varying consumer demands of electricity and the massive scale of power distribution networks present the need to not only design real-time decentralized power allocation algorithms, but also characterize how effective they are given fast-changing consumer demands and power generation capacities. In this paper, we present an Online Decentralized Dual Descent (OD3) power allocation algorithm and determine (in the worst case) how much of observed social welfare and price volatility can be explained by fluctuations in generation capacity and consumer demand. Convergence properties and performance guarantees of the OD3 algorithm are analyzed by characterizing the difference between the online decision and the optimal decision. The theoretical results in the paper are validated and illustrated by numerical experiments using real data.

eess.SY↗

arXiv2015

The Transitional Behavior of Interference in Millimeter Wave Networks and Its Impact on Medium Access Control

Millimeter wave (mmWave) communication systems use large number of antenna elements that can potentially overcome severe channel attenuation by narrow beamforming. Narrow-beam operation in mmWave networks also reduces multiuser interference, introducing the concept of noise-limited wireless networks as opposed to interference-limited ones. The noise-limited or interference-limited regime heavily reflects on the medium access control (MAC) layer throughput and on proper resource allocation and interference management strategies. Yet, these regimes are ignored in current approaches to mmWave MAC layer design, with the potential disastrous consequences on the communication performance. In this paper, we investigate these regimes in terms of collision probability and throughput. We derive tractable closed-form expressions for the collision probability and MAC layer throughput of mmWave ad hoc networks, operating under slotted ALOHA. The new analysis reveals that mmWave networks may exhibit a non-negligible transitional behavior from a noise-limited regime to an interference-limited one, depending on the density of the transmitters, density and size of obstacles, transmission probability, operating beamwidth, and transmission power. Such transitional behavior necessitates a new framework of adaptive hybrid resource allocation procedure, containing both contention-based and contention-free phases with on-demand realization of the contention-free phase. Moreover, the conventional collision avoidance procedure in the contention-based phase should be revisited, due to the transitional behavior of interference, to maximize throughput/delay performance of mmWave networks. We conclude that, unless proper hybrid schemes are investigated, the severity of the transitional behavior may significantly reduce throughput/delay performance of mmWave networks.

cs.IT↗

arXiv2015

Millimeter Wave Ad Hoc Networks: Noise-limited or Interference-limited?

In millimeter wave (mmWave) communication systems, narrow beam operations overcome severe channel attenuations, reduce multiuser interference, and thus introduce the new concept of noise-limited mmWave wireless networks. The regime of the network, whether noise-limited or interference-limited, heavily reflects on the medium access control (MAC) layer throughput and on proper resource allocation and interference management strategies. Yet, alternating presence of these regimes and, more importantly, their dependence on the mmWave design parameters are ignored in the current approaches to mmWave MAC layer design, with the potential disastrous consequences on the throughput/delay performance. In this paper, tractable closed-form expressions for collision probability and MAC layer throughput of mmWave networks, operating under slotted ALOHA and TDMA, are derived. The new analysis reveals that mmWave networks may exhibit a non-negligible transitional behavior from a noise-limited regime to an interference-limited regime, depending on the density of the transmitters, density and size of obstacles, transmission probability, beamwidth, and transmit power. It is concluded that a new framework of adaptive hybrid resource allocation procedure, containing a proactive contention-based phase followed by a reactive contention-free one with dynamic phase durations, is necessary to cope with such transitional behavior.

cs.IT↗

arXiv2015

Design Aspects of Short Range Millimeter Wave Networks: A MAC Layer Perspective

Increased density of wireless devices, ever growing demands for extremely high data rate, and spectrum scarcity at microwave bands make the millimeter wave (mmWave) frequencies an important player in future wireless networks. However, mmWave communication systems exhibit severe attenuation, blockage, deafness, and may need microwave networks for coordination and fall-back support. To compensate for high attenuation, mmWave systems exploit highly directional operation, which in turn substantially reduces the interference footprint. The significant differences between mmWave networks and legacy communication technologies challenge the classical design approaches, especially at the medium access control (MAC) layer, which has received comparatively less attention than PHY and propagation issues in the literature so far. In this paper, the MAC layer design aspects of short range mmWave networks are discussed. In particular, we explain why current mmWave standards fail to fully exploit the potential advantages of short range mmWave technology, and argue for the necessity of new collision-aware hybrid resource allocation frameworks with on-demand control messages, the advantages of a collision notification message, and the potential of multihop communication to provide reliable mmWave connections.

cs.IT↗

arXiv2015

Green Sensing and Access: Energy-Throughput Tradeoffs in Cognitive Networking

Limited spectrum resources and dramatic growth of high data rate applications have motivated opportunistic spectrum access utilizing the promising concept of cognitive networks. Although this concept has emerged primarily to enhance spectrum utilization and to allow the coexistence of heterogeneous network technologies, the importance of energy consumption imposes additional challenges, because energy consumption and communication performance can be at odds. In this paper, the approaches for energy efficient spectrum sensing and spectrum handoff, fundamental building blocks of cognitive networks is investigated. The tradeoff between energy consumption and throughput, under local as well as under cooperative sensing are characterized, and what further aspects need to be investigated to achieve energy efficient cognitive operation under various application requirements are discussed.

cs.IT↗

arXiv2015

Millimeter Wave Cellular Networks: A MAC Layer Perspective

The millimeter wave (mmWave) frequency band is seen as a key enabler of multi-gigabit wireless access in future cellular networks. In order to overcome the propagation challenges, mmWave systems use a large number of antenna elements both at the base station and at the user equipment, which lead to high directivity gains, fully-directional communications, and possible noise-limited operations. The fundamental differences between mmWave networks and traditional ones challenge the classical design constraints, objectives, and available degrees of freedom. This paper addresses the implications that highly directional communication has on the design of an efficient medium access control (MAC) layer. The paper discusses key MAC layer issues, such as synchronization, random access, handover, channelization, interference management, scheduling, and association. The paper provides an integrated view on MAC layer issues for cellular networks, identifies new challenges and tradeoffs, and provides novel insights and solution approaches.

cs.IT↗

arXiv2015

On the Convergence of Alternating Direction Lagrangian Methods for Nonconvex Structured Optimization Problems

Nonconvex and structured optimization problems arise in many engineering applications that demand scalable and distributed solution methods. The study of the convergence properties of these methods is in general difficult due to the nonconvexity of the problem. In this paper, two distributed solution methods that combine the fast convergence properties of augmented Lagrangian-based methods with the separability properties of alternating optimization are investigated. The first method is adapted from the classic quadratic penalty function method and is called the Alternating Direction Penalty Method (ADPM). Unlike the original quadratic penalty function method, in which single-step optimizations are adopted, ADPM uses an alternating optimization, which in turn makes it scalable. The second method is the well-known Alternating Direction Method of Multipliers (ADMM). It is shown that ADPM for nonconvex problems asymptotically converges to a primal feasible point under mild conditions and an additional condition ensuring that it asymptotically reaches the standard first order necessary conditions for local optimality are introduced. In the case of the ADMM, novel sufficient conditions under which the algorithm asymptotically reaches the standard first order necessary conditions are established. Based on this, complete convergence of ADMM for a class of low dimensional problems are characterized. Finally, the results are illustrated by applying ADPM and ADMM to a nonconvex localization problem in wireless sensor networks.

math.OC↗

arXiv2015

Mobile Node Localization via Pareto Optimization: Algorithm and Fundamental Performance Limitations

Accurate estimation of the position of network nodes is essential, e.g., in localization, geographic routing, and vehicular networks. Unfortunately, typical positioning techniques based on ranging or on velocity and angular measurements are inherently limited. To overcome the limitations of specific positioning techniques, the fusion of multiple and heterogeneous sensor information is an appealing strategy. In this paper, we investigate the fundamental performance of linear fusion of multiple measurements of the position of mobile nodes, and propose a new distributed recursive position estimator. The Cramér-Rao lower bounds for the parametric and a-posteriori cases are investigated. The proposed estimator combines information coming from ranging, speed, and angular measurements, which is jointly fused by a Pareto optimization problem where the mean and the variance of the localization error are simultaneously minimized. A distinguished feature of the method is that it assumes a very simple dynamical model of the mobility and therefore it is applicable to a large number of scenarios providing good performance. The main challenge is the characterization of the statistical information needed to model the Fisher information matrix and the Pareto optimization problem. The proposed analysis is validated by Monte Carlo simulations, and the performance is compared to several Kalman-based filters, commonly employed for localization and sensor fusion. Simulation results show that the proposed estimator outperforms the traditional approaches that are based on the extended Kalman filter when no assumption on the model of motion is used. In such a scenario, better performance is achieved by the proposed method, but at the price of an increased computational complexity.

cs.IT↗

arXiv2015

Beam-searching and Transmission Scheduling in Millimeter Wave Communications

Millimeter wave (mmW) wireless networks are capable to support multi-gigabit data rates, by using directional communications with narrow beams. However, existing mmW communications standards are hindered by two problems: deafness and single link scheduling. The deafness problem, that is, a misalignment between transmitter and receiver beams, demands a time consuming beam-searching operation, which leads to an alignment-throughput tradeoff. Moreover, the existing mmW standards schedule a single link in each time slot and hence do not fully exploit the potential of mmW communications, where directional communications allow multiple concurrent transmissions. These two problems are addressed in this paper, where a joint beamwidth selection and power allocation problem is formulated by an optimization problem for short range mmW networks with the objective of maximizing effective network throughput. This optimization problem allows establishing the fundamental alignment-throughput tradeoff, however it is computationally complex and requires exact knowledge of network topology, which may not be available in practice. Therefore, two standard-compliant approximation solution algorithms are developed, which rely on underestimation and overestimation of interference. The first one exploits directionality to maximize the reuse of available spectrum and thereby increases the network throughput, while imposing almost no computational complexity. The second one is a more conservative approach that protects all active links from harmful interference, yet enhances the network throughput by 100% compared to the existing standards. Extensive performance analysis provides useful insights on the directionality level and the number of concurrent transmissions that should be pursued. Interestingly, extremely narrow beams are in general not optimal.

cs.IT↗

arXiv2014

Analysis and Optimization of Random Sensing Order in Cognitive Radio Networks

Developing an efficient spectrum access policy enables cognitive radios to dramatically increase spectrum utilization while ensuring predetermined quality of service levels for primary users. In this paper, modeling, performance analysis, and optimization of a distributed secondary network with random sensing order policy are studied. Specifically, the secondary users create a random order of available channels upon primary users return, and then find optimal transmission and handoff opportunities in a distributed manner. By a Markov chain analysis, the average throughputs of the secondary users and average interference level among the secondary and primary users are investigated. A maximization of the secondary network performance in terms of the throughput while keeping under control the average interference is proposed. It is shown that despite of traditional view, non-zero false alarm in the channel sensing can increase channel utilization, especially in a dense secondary network where the contention is too high. Then, two simple and practical adaptive algorithms are established to optimize the network. The second algorithm follows the variations of the wireless channels in non-stationary conditions and outperforms even static brute force optimization, while demanding few computations. The convergence of the distributed algorithms are theoretically investigated based on the analytical performance indicators established by the Markov chain analysis. Finally, numerical results validate the analytical derivations and demonstrate the efficiency of the proposed schemes. It is concluded that fully distributed sensing order algorithms can lead to substantial performance improvements in cognitive radio networks without the need of centralized management or message passing among the users.

cs.IT↗

arXiv2014

On the Privacy of Optimization Approaches

Ensuring privacy of sensitive data is essential in many contexts, such as healthcare data, banks, e-commerce, wireless sensor networks, and social networks. It is common that different entities coordinate or want to rely on a third party to solve a specific problem. At the same time, no entity wants to publish its problem data during the solution procedure unless there is a privacy guarantee. Unlike cryptography and differential privacy based approaches, the methods based on optimization lack a quantification of the privacy they can provide. The main contribution of this paper is to provide a mechanism to quantify the privacy of a broad class of optimization approaches. In particular, we formally define a one-to-many relation, which relates a given adversarial observed message to an uncertainty set of the problem data. This relation quantifies the potential ambiguity on problem data due to the employed optimization approaches. The privacy definitions are then formalized based on the uncertainty sets. The properties of the proposed privacy measure is analyzed. The key ideas are illustrated with examples, including localization, average consensus, among others.

cs.CR↗

arXiv2014

Repair for Distributed Storage Systems in Packet Erasure Networks

Reliability is essential for storing files in many applications of distributed storage systems. To maintain reliability, when a storage node fails, a new node should be regenerated by a repair process. Most of the previous results on the repair problem assume perfect (error-free) links in the networks. However, in practice, especially in a wireless network, the transmitted packets (for repair) may be lost due to, e.g., link failure or buffer overflow. We study the repair problem of distributed storage systems in packet erasure networks, where a packet loss is modeled as an erasure. The minimum repair-bandwidth, namely the amount of information sent from the surviving nodes to the new node, is established under the ideal assumption of infinite number of packet transmissions. We also study the bandwidth-storage tradeoffs in erasure networks. Then, the use of repairing storage nodes (nodes with smaller storage space) is proposed to reduce the repair-bandwidth. We study the minimal storage of repairing storage nodes. For the case of a finite number of packet transmissions, the probability of successful repairing is investigated. We show that the repair with a finite number of packet transmissions may use much larger bandwidth than the minimum repair-bandwidth. Finally, we propose a combinatorial optimization problem, which results in the optimal repair-bandwidth for the given packet erasure probability and finite packet transmissions.

cs.IT↗

arXiv2014

Optimality of Radio Power Control via Fast-Lipschitz Optimization

Fixed point algorithms play an important role to compute feasible solutions to the radio power control problems in wireless networks. Although these algorithms are shown to converge to the fixed points that give feasible problem solutions, the solutions often lack notion of problem optimality. This paper reconsiders well known fixed point algorithms such as those with standard and type-II standard interference functions, and investigates the conditions under which they give optimal power control solutions by the recently proposed Fast-Lipschitz optimization framework. When the qualifying conditions of Fast-Lipschitz optimization apply, it is established that the fixed points are the optimal solutions of radio power optimization problems. The analysis is performed by a logarithmic transformation of variables that gives problems treatable within the Fast-Lipschitz framework. It is shown how the logarithmic problem constraints are contractive by the standard or type-II standard assumptions on the original power control problem, and how a set of cost functions fulfill the Fast-Lipschitz qualifying conditions. The analysis on non monotonic interference function allows to establish a new qualifying condition for Fast-Lipschitz optimization. The results are illustrated by considering power control problems with standard interference function, problems with type-II standard interference functions, and a case of sub-homogeneous power control problems. It is concluded that Fast-Lipschitz optimization may play an important role in many resource allocation problems in wireless networks.

math.OC↗

arXiv2014

Extensions of Fast-Lipschitz Optimization

The need of fast distributed solvers for optimization problems in networked systems has motivated the recent development of the Fast-Lipschitz optimization framework. In such an optimization, problems satisfying certain qualifying conditions, such as monotonicity of the objective function and contractivity of the constraints, have a unique optimal solution obtained via fast distributed algorithms that compute the fixed point of the constraints. This paper extends the set of problems for which the Fast-Lipschitz framework applies. Existing assumptions on the problem form are relaxed and new and generalized qualifying conditions are established by novel results based on Lagrangian duality. It is shown for which cases of more constraints than decision variables, and less constraints than decision variables Fast-Lipschitz optimization applies. New results are obtained by imposing non strict monotonicity of the objective functions. The extended Fast-Lipschitz framework is illustrated by a number of examples, including a non-linear optimal control problem.

math.OC↗

arXiv2014

Design Challenges of Millimeter Wave Communications: A MAC Layer Perspective

As the spectrum is becoming more scarce due to exponential demand of formidable data quantities, the new millimiterwave (mmW) band is considered as an enabling player of 5G communications to provide multi-gigabits wireless acccess. MmW communications exhibit high attenuation and blockage, directionality due to massive beamforming, deafness, low-interference, and may need micro waves networks for coordination and fallback support. The current mmW standardizations are challenged by the overwhelming complexity given by such heterogeneous communication systems and mmW band characteristics. This demands new substantial protocol developments at all layers. In this paper, the medium access control issues for mmW communications are reviewed. It is discussed that while existing standards address some of these issues for personal and local area networks, little has been done for cellular networks. It is argued that the medium access control layer should be equipped with adaptation mechanisms that are aware of the special mmW characteristics. Recommendations for mmW medium access control design in 5G are provided. It is concluded that the design of efficient access control techniques for mmW is in its infancy and much work still has to be done.

cs.IT↗

arXiv2014

A Semi Distributed Approach for Min-Max Fair Car-Parking Slot Assignment Problem

Designing efficient car parking mechanisms that can be potentially integrated into future intelligent transportation systems is of crucial importance. Usually, the related design problems are combinatorial and the worst-case complexity of optimal solution approaches grows exponentially with the problem sizes. Therefore, such optimal approaches are not scalable and practically undesirable. As a result, almost all existing methods for parking slot assignment are simple and greedy approaches, where each car is assigned a free parking slot, which is closer to its destination. Moreover, no emphasis is placed to optimize the social benefit of the users during the parking slot assignment. In this paper, the fairness as a metric for modeling the aggregate social benefit of the users is considered and a distributed algorithm based on Lagrange duality theory is developed. The proposed algorithm is gracefully scalable compared to the optimal methods. In addition, it is shown that the proposed car parking mechanism preserves privacy in the sense that any car involved in the algorithm will not be able to discover the destination of any other car during the algorithm iterations. Numerical results illustrate the performance of the proposed algorithm compared to the optimal assignment and a greedy method. They show that our algorithm yields a good tradeoff between the implementation-level simplicity and the performance. Even though the main emphasis in this paper resides in the car parking slot assignment problem, our formulation and the algorithms, in general, can also be applied or adopted in fair agent-target assignment problems in other application domains.

math.OC↗