On the Nash Equilibria in Decentralized Parallel Interference Channels

In this paper, the 2-dimensional decentralized parallel interference channel (IC) with 2 transmitter-receiver pairs is modelled as a non-cooperative static game. Each transmitter is assumed to be a fully rational entity with complete information on the game, aiming to maximize its own individual spectral efficiency by tuning its own power allocation (PA) vector. Two scenarios are analysed. First, we consider that transmitters can split their transmit power between both dimensions (PA game). Second, we consider that each transmitter is limited to use only one dimension (channel selection CS game). In the first scenario, the game might have either one or three NE in pure strategies (PS). However, two or infinitely many NE in PS might also be observed with zero probability. In the second scenario, there always exists either one or two NE in PS. We show that in both games there always exists a non-zero probability of observing more than one NE. More interestingly, using Monte-Carlo simulations, we show that the highest and lowest network spectral efficiency at any of the NE in the CS game are always higher than the ones in the PA.Comment: 6 pages, 4 figures, presented in ICCC Kyoto 201

R-DVB: Software Defined Radio implementation of DVB-T signal detection functions for digital terrestrial television

This thesis describes the implementation steps of ETSI DVB-T compliant software defined radio bench receiver, using the GNU Radio framework. It also analyzes its performances and suggest futures optimization tasks in order to achieve the real-time goal

Learning Equilibria with Partial Information in Decentralized Wireless Networks

In this article, a survey of several important equilibrium concepts for decentralized networks is presented. The term decentralized is used here to refer to scenarios where decisions (e.g., choosing a power allocation policy) are taken autonomously by devices interacting with each other (e.g., through mutual interference). The iterative long-term interaction is characterized by stable points of the wireless network called equilibria. The interest in these equilibria stems from the relevance of network stability and the fact that they can be achieved by letting radio devices to repeatedly interact over time. To achieve these equilibria, several learning techniques, namely, the best response dynamics, fictitious play, smoothed fictitious play, reinforcement learning algorithms, and regret matching, are discussed in terms of information requirements and convergence properties. Most of the notions introduced here, for both equilibria and learning schemes, are illustrated by a simple case study, namely, an interference channel with two transmitter-receiver pairs.Comment: 16 pages, 5 figures, 1 table. To appear in IEEE Communication Magazine, special Issue on Game Theor

One loop Standard Model corrections to flavor diagonal fermion-graviton vertices

We extend a previous analysis of flavor-changing fermion-graviton vertices, by adding the one-loop SM corrections to the flavor diagonal fermion-graviton interactions. Explicit analytical expressions taking into account fermion masses for the on-shell form factors are computed and presented. The infrared safety of the fermion-graviton vertices against radiative corrections of soft photons and gluons is proved, by extending the ordinary infrared cancellation mechanism between real and virtual emissions to the gravity case. These results can be easily generalized to fermion couplings with massive gravitons, graviscalar, and dilaton fields, with potential phenomenological implications to new physics scenarios with low gravity scale.Comment: 30 pages, 11 figures, revised final version, to appear on Phys. Rev.

Performance Assessment of MIMO Precoding on Realistic mmWave Channels

In this paper, the performance of multi-user Multiple-Input Multiple-Output (MIMO) systems is evaluated in terms of SINR and capacity. We focus on the case of a downlink single-cell scenario where different precoders have been studied. Among the considered precoders, we range from different Grid of Beams (GoB) optimization approaches to linear precoders (e.g., matched filtering and zero forcing). This performance evaluation includes imperfect channel estimation, and is carried out over two realistic mmWave 5G propagation channels, which are simulated following either the measurement campaign done by New York University (NYU) or the 3GPP channel model. Our evaluation allows grasping knowledge on the precoding performance in mmWave realistic scenarios. The results highlight the good performance of GoB optimization approaches when a realistic channel model with directionality is adopted.Comment: to be published in IEEE ICC Workshop on Millimeter-Wave Communications for 5G and B5G, Shanghai, P.R. China, May, 201

Joint Channel and Power Allocation in Tactical Cognitive Networks: Enhanced Trial and Error

National audienceIn tactical networks the presence of a central controller (e.g., a base station) is made impractical by the unpredictability of the nodes' positions and by the fact that its presence can be exploited by hostile entities. As a consequence, self-configuring networks are sought for military and emergency communication networks. In such networks, the transmission parameters, most notably the transmission channel and the power level, are set by the devices following specific behavioural rules. In this context, an algorithm for self-configuring wireless networks is presented, analysed and enhanced to meet the specific needs of tactical networks. Such an algorithm, based on the concept of trial and error, is tested under static and mobile situations, and different metrics are considered to show its performance. In particular, the stability and performance improvements with respect to previously proposed versions of the algorithm are detailed

Channel and power allocation algorithms for ad hoc clustered networks

978-1-4673-1422-0International audienceIn the context of mobile clustered ad hoc networks, this paper proposes and studies a self-configuring algorithm which is able to jointly set the channel frequency and power level of the transmitting nodes, by exploiting one bit of feedback per receiver. This algorithm is based upon a learning algorithm, namely trial and error, that is cast into a game theoretical framework in order to study its theoretical performance. We consider two different feedback solutions, one based on the SINR level estimation, and one based on the outcome of a CRC check. We analytically prove that this algorithm selects a suitable configuration for the network, and analyse its performance through numerical simulations under various scenarios

Classifying word problems of finitely generated algebras via computable reducibility

We contribute to a recent research program which aims at revisiting the study of the complexity of word problems, a major area of research in combinatorial algebra, through the lens of the theory of computably enumerable equivalence relations (ceers), which has considerably grown in recent times. To pursue our analysis, we rely on the most popular way of assessing the complexity of ceers, that is via computable reducibility on equivalence relations, and its corresponding degree structure (the c-degrees). On the negative side, building on previous work of Kasymov and Khoussainov, we individuate a collection of c-degrees of ceers which cannot be realized by the word problem of any finitely generated algebra of finite type. On the positive side, we show that word problems of finitely generated semigroups realize a collection of c-degrees which embeds rich structures and is large in several reasonable ways