Signal estimation for cognitive wireless networks

Project leaders

Roberto Tempo, Boris Polyak

Agreement

RUSSIA - RAS old - Russian Academy of Sciences old

Call

CNR/RAS 2011-2013

Department

ICT

Thematic area

Engineering, ICT and technologies for energy and transportation

Status of the project

Extended

Report for renewal

joint-report.doc

Research proposal

A) Prerequisites for a successful collaboration
The research teams of IEIIT-CNR and IPU-RAS share a long history of continuous collaborations. In the past six years they were involved in two subsequent joint collaboration projects funded by CNR and RAS.
In particular this proposal is a continuation of a three-year project, titled "New Monte-Carlo like methods in control, and applications within information-technology", held during the period 2008-2010 and involving the same research groups. The project has been very successful and the main results that have been obtained are:
- several joint papers published in top-level international journals and conferences
- development of the Matlab-based Toolbox RACT (Randomized Algorithms Control Toolbox)
The Laboratory of Adaptive and Robust Systems of the Institute for Control Science includes a research group involved in theoretical developments of iterative methods for adaptation; some relevant results have been summarized in the series of monographs by the founder of the Laboratory, Academician Ya. Z. Tsypkin. The collaboration with the Italian IEIIT-CNR group started more than 10 years ago in the framework of NATO-CNR fellowships and continued thanks to two CNR-RAS bilateral projects and several visits of B. Polyak and P. Shcherbakov to IEIIT-CNR in Torino.
Another feature of these projects has been the active involvement of young Russian scientists (E. Gryazina and A. Tremba), who demonstrated their abilities and skills during visits to IEIIT-CNR.
The Italian IEIIT-CNR group has profound expertise on the study of complex systems, communications, control theory, signal processing and identification. In the past, intensive exchange of ideas with the IPU-RAS group took place during two visits of R. Tempo and F. Dabbene to RAS in Moscow.
B) Research proposal
The aim of this joint research proposal is to extend the fruitful collaborations between IEIIT-CNR and IPU-RAS to the field of wireless networks and related technologies.
The idea steams from the consideration that wireless technologies have experienced a dramatic rise in popularity in recent years. This phenomenon has ultimately led to soaring numbers of users overcrowding the spectrum portion allocated for unlicensed use, commonly employed by these technologies.
This spectrum scarcity has become a new challenge for the development of wireless technologies. However, it has been shown that it only occurs in those portions of spectrum allocated for unlicensed use, while the rest of the spectrum, which is usually lent for use by the governments via licenses, is being heavily underutilized. For this reason, many see the cognitive radio technology as a viable solution for the problem of spectrum scarcity.
Cognitive radio basically enables wireless devices to use licensed portions of the spectrum, when they are not being used by their legal owners (primary users). To make this possible, cognitive radio devices scan the licensed frequencies at all times, to detect transmissions from the licensed user and only transmit when they are sure that the channel is free. However, if a transmission from a primary user is detected, the cognitive-enabled devices immediately vacate the channel, to avoid causing interference.
Besides detecting transmissions from primary users, establishing a cognitive radio network, where many cognitive-enabled devices communicate with each other in a cognitive radio environment, poses a range of challenges.
In this research proposal, we investigate a cooperative approach able to identify transmissions coming from other cognitive-enabled devices in the area.
In particular, we focus our attention on cooperative signal-estimation in a cognitive radio environment, to verify whether there is a valid transmission from other unlicensed users or unlicensed access points (AP) employing the same technology, and to differentiate such transmissions from those coming from primary users.
More specifically we focus on the idea of applying subspace-based methods, developed for dynamical system identification, to detect transmissions coming from unlicensed APs in the network.
The approach we propose will evolve along the following directions:
1) We consider a scenario where several devices are cooperating to detect the same transmission. By employing subspace-based methods, originally developed by the control system community for identifying dynamical systems, one can extract the common signal, if present, among those transmitted by the participating devices.
The outcome of this approach is twofold: i) establishing if a common signal exists ii) separating such a signal from other interfering signals whenever possible
2) In the case the signals involved are generated by devices employing OFDM (Othogonal Frequency Division Multiplexing) modulation, a further step will be to identify the OFDM signal structure and its specific parameters such as, subcarrier modulation, cyclic prefix length, number of carriers, subcarrier spacing, etc.

Research goals

The following key problems are the main objectives of this project:
1) Finding techniques based on subspace methods able to reliably extract the common portion of a signal, from a set of signals received by cooperating network nodes.
2) Identifying the structure of the common signal, once it has been extracted. In particular, if the common signal is OFDM the goal will be to reliably estimate OFDM parameters such as, the constellation used for modulating the subcarriers, the number of subcarriers, the subcarrier spacing and the OFDM cyclic prefix length.
3) Investigating the performance of the proposed estimation and parameter identification techniques in the presence of multipath fading and fast time varying wireless channels.

Last update: 25/04/2024