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Troubleshooting of wireless networks is a challenging network management task. We have developed, in a previous work, a new troubleshooting methodology, which we named Statistical Learning Automated Healing (SLAH). This methodology uses statistical learning, in particular logistic regression, to extract the functional relationships between the noisy Key Performance Indicators (KPIs) and Radio Resource...
Distributed beamforming has the great potential of performance improvement in wireless networks while the carrier synchronization overhead will reduce its performance gain. In this paper the effects of carrier synchronization on link throughput of distributed beamforming is studied. The expressions of the frequency and initial phase used by each cooperative node are derived for the existing round-trip...
We introduce algorithms to optimize wireless networks in the presence of fading. Central to the problem considered is the need to learn the fading's probability distribution while determining optimal operating points. A stochastic subgradient descent algorithm in the dual domain is developed to accomplish this task. Even though the optimization problems considered are not convex, convergence of the...
In this paper we develop a discrete and distributed optimization framework that maximizes the overall spectral efficiency of heterogeneous networks while ensuring a minimum fairness among users. We split the problem into two subproblems: the first one is handled by the users and consists in a transmission by each user of a minimum rate requirement to the base stations and the second is the resource...
This paper establishes a framework for designing fast, robust, and distributed algorithms for solving network utility maximization problems with coupled objective functions. We use two case studies in wireless communications to illustrate the key ideas: reverse-engineering the algorithm based on the KKT conditions of the optimization problem, and proving the properties of the algorithms using monotone...
We consider a random access system of non-cooperative selfish transmitters with the individual objectives of jointly optimizing throughput rewards, energy and delay costs. Our goal is to evaluate the effects of malicious nodes that have the dual objectives of blocking the packet transmissions of the other selfish nodes as well as optimizing their individual performance measures. We assume saturated...
Energy efficient routing is a critical problem in multihop wireless networks due to the severe power constraint of wireless nodes. Despite its importance and many research efforts towards it, a distributed routing algorithm that maximizes network lifetime is still missing. To address this problem, we propose a novel utility-based nonlinear optimization formulation to the maximum lifetime routing problem...
In multi-input multi-output (MIMO) systems, maximum-likelihood (ML) decoding is equivalent to finding the closest lattice point in an N-dimensional complex space. In general, this problem is known to be NP hard. In this paper, we propose a quasi-maximum likelihood algorithm based on semi-definite programming (SDP). We introduce several SDP relaxation models for MIMO systems, with increasing complexity...
In this paper, a bandwidth allocation model is proposed for multi-hop wireless mesh network (WMN) with a goal of achieving high traffic throughput in minimal scheduling time slots. Scheduling scheme based on the optimization model serves the centralized scheduling first and compresses the scheduling time to minimum by enhancing concurrence rate among links, thus more time slots can be saved for distributed...
The popularity of wireless networks has soared in recent years. The wireless channel, along with its many benefits, poses a host of challenges for system designers, due to its time-varying and frequency selective behavior. Orthogonal frequency division multiplexing (OFDM) addresses some of these challenges at the physical layer. In this paper, we discuss various issues in a practical implementation...
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