Learning-Based Constraint Satisfaction With Sensing Restrictions

In this paper we consider graph-coloring problems, an important subset of general constraint satisfaction problems that arise in wireless resource allocation. We constructively establish the existence of fully decentralized learning-based algorithms that are able to find a proper coloring even in the presence of strong sensing restrictions, in particular sensing asymmetry of the type encountered when hidden terminals are present. Our main analytic contribution is to establish sufficient conditions on the sensing behaviour to ensure that the solvers find satisfying assignments with probability one. These conditions take the form of connectivity requirements on the induced sensing graph. These requirements are mild, and we demonstrate that they are commonly satisfied in wireless allocation tasks. We argue that our results are of considerable practical importance in view of the prevalence of both communication and sensing restrictions in wireless resource allocation problems. The class of algorithms analysed here requires no message-passing whatsoever between wireless devices, and we show that they continue to perform well even when devices are only able to carry out constrained sensing of the surrounding radio environment

Computational Methods for Sparse Solution of Linear Inverse Problems

The goal of the sparse approximation problem is to approximate a target signal using a linear combination of a few elementary signals drawn from a fixed collection. This paper surveys the major practical algorithms for sparse approximation. Specific attention is paid to computational issues, to the circumstances in which individual methods tend to perform well, and to the theoretical guarantees available. Many fundamental questions in electrical engineering, statistics, and applied mathematics can be posed as sparse approximation problems, making these algorithms versatile and relevant to a plethora of applications

Incentive Mechanisms for Participatory Sensing: Survey and Research Challenges

Participatory sensing is a powerful paradigm which takes advantage of smartphones to collect and analyze data beyond the scale of what was previously possible. Given that participatory sensing systems rely completely on the users' willingness to submit up-to-date and accurate information, it is paramount to effectively incentivize users' active and reliable participation. In this paper, we survey existing literature on incentive mechanisms for participatory sensing systems. In particular, we present a taxonomy of existing incentive mechanisms for participatory sensing systems, which are subsequently discussed in depth by comparing and contrasting different approaches. Finally, we discuss an agenda of open research challenges in incentivizing users in participatory sensing.Comment: Updated version, 4/25/201

Future Evolution of CSMA Protocols for the IEEE 802.11 Standard

In this paper a candidate protocol to replace the prevalent CSMA/CA medium access control in Wireless Local Area Networks is presented. The proposed protocol can achieve higher throughput than CSMA/CA, while maintaining fairness, and without additional implementation complexity. Under certain circumstances, it is able to reach and maintain collision-free operation, even when the number of contenders is variable and potentially large. It is backward compatible, allowing for new and legacy stations to coexist without degrading one another's performance, a property that can make the adoption process by future versions of the standard smooth and inexpensive.Comment: This paper has been accepted in the Second IEEE ICC Workshop 2013 on Telecommunication Standards: From Research to Standard

Decentralised Algorithms for Wireless Networks.

Designing and managing wireless networks is challenging for many reasons. Two of the most crucial in 802.11 wireless networks are: (a) variable per-user channel quality and (b) unplanned, ad-hoc deployment of the Access Points (APs). Regarding (a), a typical consequence is the selection, for each user, of a different bit-rate, based on the channel quality. This in turn causes the so-called performance “anomaly”, where the users with lower bit-rate transmit for most of the time, causing the higher bit-rate users to receive less time for transmission (air time). Regarding (b), an important issue is managing interference. This can be mitigated by selecting different channels for neighbouring APs, but needs to be carried out in a decentralised way because often APs belong to different administrative domains, or communication between APs is unfeasible. Tools for managing unplanned deployment are also becoming important for other small cell networks, such as femtocell networks, where decentralised allocation of scrambling codes is a key task