کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
466362 697831 2012 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Group sparse Lasso for cognitive network sensing robust to model uncertainties and outliers
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
پیش نمایش صفحه اول مقاله
Group sparse Lasso for cognitive network sensing robust to model uncertainties and outliers
چکیده انگلیسی

To account for variations in the frequency, time, and space dimensions, dynamic re-use of licensed bands under the cognitive radio (CR) paradigm calls for innovative network-level sensing algorithms for multi-dimensional spectrum opportunity awareness. Toward this direction, the present paper develops a collaborative scheme whereby CRs cooperate to localize active primary user (PU) transmitters and reconstruct a power spectral density (PSD) map portraying the spatial distribution of power across the monitored area per frequency band and channel coherence interval. The sensing scheme is based on a parsimonious model that accounts for two forms of sparsity: one due to the narrow-band nature of transmit-PSDs compared to the large portion of spectrum that a CR can sense, and another one emerging when adopting a spatial grid of candidate PU locations. Capitalizing on this dual sparsity, an estimator of the model coefficients is obtained based on the group sparse least-absolute-shrinkage-and-selection operator (GS-Lasso). A novel reduced-complexity GS-Lasso solver is developed by resorting to the alternating direction method of multipliers (ADMoM). Robust versions of this GS-Lasso estimator are also introduced using a GS total least-squares (TLS) approach to cope with both uncertainty in the regression matrices, arising due to inaccurate channel estimation and grid-mismatch effects, and unexpected model outliers. In spite of the non-convexity of the GS-TLS criterion, the novel robust algorithm has guaranteed convergence to (at least) a local optimum. The analytical findings are corroborated by numerical tests.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physical Communication - Volume 5, Issue 2, June 2012, Pages 161–172
نویسندگان
, , ,