Distributed ADMM for In-Network Reconstruction of Sparse Signals With Innovations

In this paper, we tackle the in-network recovery of sparse signals with innovations. We assume that the nodes of the network measure a signal composed by a common component and an innovation, both sparse and unknown, according to the joint sparsity model 1 (JSM-1). Acquisition is performed as in compressed sensing, hence the number of measurements is reduced. Our goal is to show that distributed algorithms based on the alternating direction method of multipliers (ADMM) can be efficient in this framework to recover both the common and the individual components. Specifically, we define a suitable functional and we show that ADMM can be implemented to minimize it in a distributed way, leveraging local communication between nodes. Moreover, we develop a second version of the algorithm, which requires only binary messaging, significantly reducing the transmission load

Asynchronous online ADMM for consensus problems

In this paper, we consider the consensus problem where a set of nodes cooperate to minimize a global cost. In particular, we consider an online setting and propose an online algorithm based on the alternating direction method of multipliers. Besides, we take into account the asynchronous operation of the nodes. In this context, we prove that the algorithm attains sublinear regret on the objective. Finally, we assess numerically the performance of the algorithm in a distributed sparse regression problem

Sparse linear regression from perturbed data

The problem of sparse linear regression is relevant in the context of linear system identification from large datasets. When data are collected from real-world experiments, measurements are always affected by perturbations or low-precision representations. However, the problem of sparse linear regression from fully-perturbed data is scarcely studied in the literature, due to its mathematical complexity. In this paper, we show that, by assuming bounded perturbations, this problem can be tackled by solving low-complex l2 and l1 minimization problems. Both theoretical guarantees and numerical results are illustrated in the paper

D13.2 Techniques and performance analysis on energy- and bandwidth-efficient communications and networking

Deliverable D13.2 del projecte europeu NEWCOM#The report presents the status of the research work of the various Joint Research Activities (JRA) in WP1.3 and the results that were developed up to the second year of the project. For each activity there is a description, an illustration of the adherence to and relevance with the identified fundamental open issues, a short presentation of the main results, and a roadmap for the future joint research. In the Annex, for each JRA, the main technical details on specific scientific activities are described in detail.Peer ReviewedPostprint (published version

D13.3 Overall assessment of selected techniques on energy- and bandwidth-efficient communications

Deliverable D13.3 del projecte europeu NEWCOM#The report presents the outcome of the Joint Research Activities (JRA) of WP1.3 in the last year of the Newcom# project. The activities focus on the investigation of bandwidth and energy efficient techniques for current and emerging wireless systems. The JRAs are categorized in three Tasks: (i) the first deals with techniques for power efficiency and minimization at the transceiver and network level; (ii) the second deals with the handling of interference by appropriate low interference transmission techniques; (iii) the third is concentrated on Radio Resource Management (RRM) and Interference Management (IM) in selected scenarios, including HetNets and multi-tier networks.Peer ReviewedPostprint (published version