347 research outputs found
Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks
Cognitive radio has been widely considered as one of the prominent solutions
to tackle the spectrum scarcity. While the majority of existing research has
focused on single-band cognitive radio, multiband cognitive radio represents
great promises towards implementing efficient cognitive networks compared to
single-based networks. Multiband cognitive radio networks (MB-CRNs) are
expected to significantly enhance the network's throughput and provide better
channel maintenance by reducing handoff frequency. Nevertheless, the wideband
front-end and the multiband spectrum access impose a number of challenges yet
to overcome. This paper provides an in-depth analysis on the recent
advancements in multiband spectrum sensing techniques, their limitations, and
possible future directions to improve them. We study cooperative communications
for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also
investigate several limits and tradeoffs of various design parameters for
MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that
differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE
Journal, Special Issue on Future Radio Spectrum Access, March 201
Enhanced Compressive Wideband Frequency Spectrum Sensing for Dynamic Spectrum Access
Wideband spectrum sensing detects the unused spectrum holes for dynamic
spectrum access (DSA). Too high sampling rate is the main problem. Compressive
sensing (CS) can reconstruct sparse signal with much fewer randomized samples
than Nyquist sampling with high probability. Since survey shows that the
monitored signal is sparse in frequency domain, CS can deal with the sampling
burden. Random samples can be obtained by the analog-to-information converter.
Signal recovery can be formulated as an L0 norm minimization and a linear
measurement fitting constraint. In DSA, the static spectrum allocation of
primary radios means the bounds between different types of primary radios are
known in advance. To incorporate this a priori information, we divide the whole
spectrum into subsections according to the spectrum allocation policy. In the
new optimization model, the minimization of the L2 norm of each subsection is
used to encourage the cluster distribution locally, while the L0 norm of the L2
norms is minimized to give sparse distribution globally. Because the L0/L2
optimization is not convex, an iteratively re-weighted L1/L2 optimization is
proposed to approximate it. Simulations demonstrate the proposed method
outperforms others in accuracy, denoising ability, etc.Comment: 23 pages, 6 figures, 4 table. arXiv admin note: substantial text
overlap with arXiv:1005.180
Compressive Identification of Active OFDM Subcarriers in Presence of Timing Offset
In this paper we study the problem of identifying active subcarriers in an
OFDM signal from compressive measurements sampled at sub-Nyquist rate. The
problem is of importance in Cognitive Radio systems when secondary users (SUs)
are looking for available spectrum opportunities to communicate over them while
sensing at Nyquist rate sampling can be costly or even impractical in case of
very wide bandwidth. We first study the effect of timing offset and derive the
necessary and sufficient conditions for signal recovery in the oracle-assisted
case when the true active sub-carriers are assumed known. Then we propose an
Orthogonal Matching Pursuit (OMP)-based joint sparse recovery method for
identifying active subcarriers when the timing offset is known. Finally we
extend the problem to the case of unknown timing offset and develop a joint
dictionary learning and sparse approximation algorithm, where in the dictionary
learning phase the timing offset is estimated and in the sparse approximation
phase active subcarriers are identified. The obtained results demonstrate that
active subcarrier identification can be carried out reliably, by using the
developed framework.Comment: To appear in the proceedings of the IEEE Global Communications
Conference (GLOBECOM) 201
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