Luca Rose

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 - 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, an interference channel with two transmitter-receiver pairs.

Distributed power allocation with SINR constraints using trial and error learning

In this paper, we address the problem of global transmit power minimization in a self-configuring network where radio devices are subject to operate at a minimum signal to interference plus noise ratio (SINR) level. We model the network as a parallel Gaussian interference channel and we introduce a fully decentralized algorithm (based on trial and error) able to statistically achieve a configuration where the performance demands are met. Contrary to existing solutions, our algorithm requires only local information and can learn stable and efficient working points by using only one bit feedback. We model the network under two different game theoretical frameworks: normal form and satisfaction form. We show that the converging points correspond to equilibrium points, namely Nash and satisfaction equilibrium. Similarly, we provide sufficient conditions for the algorithm to converge in both formulations. Moreover, we provide analytical results to estimate the algorithms performance, as a function of the network parameters. Finally, numerical results are provided to validate our theoretical conclusions.

Increasing the Security of Wireless Communication through Relaying and Interference Generation

The exchange of confidential messages is an inherent problem in wireless communication due to the broadcast nature of the radio channel. In this paper, we enhance standard cryptography with information-theoretic techniques by exploiting relays to increase the confidentiality of wireless communication in the presence of one or more eavesdroppers with low-noise receivers. To achieve this, we present a protocol which makes use of relays in two ways. First, the relays re-transmit disjoint encrypted chunks of a message. Second, the relays utilize cooperative jamming techniques to generate pseudo-random signals in order to increase the interference level in the propagation domain. Chunks and interference levels are allocated over relays in such a way that the message can only be decoded within a critical area around the intended receiver. Our simulation results show that this area can be minimized under realistic assumptions on propagation environment and channel knowledge.

Exploiting Geographical Context in D2D Communications

In this paper, we present a framework for including geographical context information within the process of relay selection, where both the relay and destination can be user equipment (UE) hence enabling relaying via device-to-device (D2D) communication. Geographical information, acquired through positioning systems and radio maps, are used to infer pathloss, link budgets and relay generated interference. Thus, this information becomes available at the core network without the aid of extra signaling and channel sounding. Tools from image processing can be exploited to analyze the radio map and determine so called isolated regions. Then, these regions are used by the proposed framework to effectively select the relay. Three different relay selection policies that exploit geographical context via the knowledge of the spatial isolated regions are introduced. Each of these policies is analyzed via simulation and performance is compared with respect to baseline schemes. The pertinence of adopting geographical information is confirmed by the gain in terms of useful power and reduced interference level generated.