arXiv subjects

Alfredo Garcia

Publications and source records attributed to Alfredo Garcia.

43 records · Page 3Linked to original sources

arXiv2012

An Adaptive Online Ad Auction Scoring Algorithm for Revenue Maximization

Sponsored search becomes an easy platform to match potential consumers' intent with merchants' advertising. Advertisers express their willingness to pay for each keyword in terms of bids to the search engine. When a user's query matches the keyword, the search engine evaluates the bids and allocates slots to the advertisers that are displayed along side the unpaid algorithmic search results. The advertiser only pays the search engine when its ad is clicked by the user and the price-per-click is determined by the bids of other competing advertisers.

cs.GT↗

arXiv2012

Joint Access Point Selection and Power Allocation for Uplink Wireless Networks

We consider the distributed uplink resource allocation problem in a multi-carrier wireless network with multiple access points (APs). Each mobile user can optimize its own transmission rate by selecting a suitable AP and by controlling its transmit power. Our objective is to devise suitable algorithms by which mobile users can jointly perform these tasks in a distributed manner. Our approach relies on a game theoretic formulation of the joint power control and AP selection problem. In the proposed game, each user is a player with an associated strategy containing a discrete variable (the AP selection decision) and a continuous vector (the power allocation among multiple channels). We provide characterizations of the Nash Equilibrium of the proposed game, and present a set of novel algorithms that allow the users to efficiently optimize their rates. Finally, we study the properties of the proposed algorithms as well as their performance via extensive simulations.

cs.IT↗

arXiv2011

Lower Bounds Optimization for Coordinated Linear Transmission Beamformer Design in Multicell Network Downlink

We consider the coordinated downlink beamforming problem in a cellular network with the base stations (BSs) equipped with multiple antennas, and with each user equipped with a single antenna. The BSs cooperate in sharing their local interference information, and they aim at maximizing the sum rate of the users in the network. A set of new lower bounds (one bound for each BS) of the non-convex sum rate is identified. These bounds facilitate the development of a set of algorithms that allow the BSs to update their beams by optimizing their respective lower bounds. We show that when there is a single user per-BS, the lower bound maximization problem can be solved exactly with rank-1 solutions. In this case, the overall sum rate maximization problem can be solved to a KKT point. Numerical results show that the proposed algorithms achieve high system throughput with reduced backhaul information exchange among the BSs.

cs.IT↗

arXiv2011

Distributed Uplink Resource Allocation in Cognitive Radio Networks -- Part I: Equilibria and Algorithms for Power Allocation

Spectrum management has been identified as a crucial step towards enabling the technology of a cognitive radio network (CRN). Most of the current works dealing with spectrum management in the CRN focus on a single task of the problem, e.g., spectrum sensing, spectrum decision, spectrum sharing or spectrum mobility. In this two-part paper, we argue that for certain network configurations, jointly performing several tasks of the spectrum management improves the spectrum efficiency. Specifically, our aim is to study the uplink resource management problem in a CRN where there exist multiple cognitive users (CUs) and access points (APs). The CUs, in order to maximize their uplink transmission rates, have to associate to a suitable AP (spectrum decision), and to share the channels used by this AP with other CUs (spectrum sharing). These tasks are clearly interdependent, and the problem of how they should be carried out efficiently and in a distributed manner is still open in the literature.

cs.IT↗

arXiv2011

Distributed Uplink Resource Allocation in Cognitive Radio Networks -- Part II: Equilibria and Algorithms for Joint Access Point Selection and Power Allocation

In the first part of this paper, we have studied solely the spectrum sharing aspect of the above problem, and proposed algorithms for the CUs in the single AP network to efficiently share the spectrum. In this second part of the paper, we build upon our previous understanding of the single AP network, and formulate the joint spectrum decision and spectrum sharing problem in a multiple AP network into a non-cooperative game, in which the feasible strategy of a player contains a discrete variable (the AP/spectrum decision) and a continuous vector (the power allocation among multiple channels). The structure of the game is hence very different from most non-cooperative spectrum management game proposed in the literature. We provide characterization of the Nash Equilibrium (NE) of this game, and present a set of novel algorithms that allow the CUs to distributively and efficiently select the suitable AP and share the channels with other CUs. Finally, we study the properties of the proposed algorithms as well as their performance via extensive simulations.

cs.IT↗

arXiv2011

Joint Distributed Access Point Selection and Power Allocation in Cognitive Radio Networks

Spectrum management has been identified as a crucial step towards enabling the technology of the cognitive radio network (CRN). Most of the current works dealing with spectrum management in the CRN focus on a single task of the problem, e.g., spectrum sensing, spectrum decision, spectrum sharing or spectrum mobility. In this work, we argue that for certain network configurations, jointly performing several tasks of the spectrum management improves the spectrum efficiency. Specifically, we study the uplink resource management problem in a CRN where there exist multiple cognitive users (CUs) and access points (APs), with each AP operates on a set of non-overlapping channels. The CUs, in order to maximize their uplink transmission rates, have to associate to a suitable AP (spectrum decision), and to share the channels belong to this AP with other CUs (spectrum sharing). These tasks are clearly interdependent, and the problem of how they should be carried out efficiently and distributedly is still open in the literature. In this work we formulate this joint spectrum decision and spectrum sharing problem into a non-cooperative game, in which the feasible strategy of a player contains a discrete variable and a continuous vector. The structure of the game is hence very different from most non-cooperative spectrum management game proposed in the literature. We provide characterization of the Nash Equilibrium (NE) of this game, and present a set of novel algorithms that allow the CUs to distributively and efficiently select the suitable AP and share the channels with other CUs. Finally, we study the properties of the proposed algorithms as well as their performance via extensive simulations.

cs.IT↗

arXiv2011

Averaged Iterative Water-Filling Algorithm: Robustness and Convergence

The convergence properties of the Iterative water-filling (IWF) based algorithms have been derived in the ideal situation where the transmitters in the network are able to obtain the exact value of the interference plus noise (IPN) experienced at the corresponding receivers in each iteration of the algorithm. However, these algorithms are not robust because they diverge when there is it time-varying estimation error of the IPN, a situation that arises in real communication system. In this correspondence, we propose an algorithm that possesses convergence guarantees in the presence of various forms of such time-varying error. Moreover, we also show by simulation that in scenarios where the interference is strong, the conventional IWF diverges while our proposed algorithm still converges.

cs.IT↗