Spectrum sensing is a key component of the cognitive radio paradigm. Primary signals are typically detected with uncalibrated receivers at signal-to-noise ratios (SNRs) well below decodability levels. Multiantenna detectors exploit spatial independence receiver thermal noise to boost detection performance and robustness. We study problem detecting Gaussian signal rank- <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</i> unknown covariance matrix...

We recently proposed the dynamic spectrum leasing (DSL) paradigm for access in cognitive radio networks. In this paper, we formalize concept by developing a general game-theoretic framework DSL and carefully identifying requirements coexistence of primary secondary systems via leasing. contrast to hierarchical access, owners networks, which are denoted as users, dynamically adjust amount interference that they willing tolerate response demand from transmitters. The transmitters, turn,...

Spectrum sensing is a key ingredient of the dynamic spectrum access paradigm, but it needs powerful detectors operating at SNRs well below decodability levels primary signals. Noise uncertainty poses significant challenge to development such schemes, requiring some degree diversity (spatial, temporal, or in distribution) for identifiability noise level. Multiantenna exploit spatial independence receiver thermal noise. We review this class schemes and propose novel detector trading off...

Since multi-antenna (MIMO) systems are becoming more popular thanks to their inherent potential for capacity improvement, interference from MIMO transceivers is an increasingly serious concern. Spatial multiplexing schemes particularly vulnerable multi-user interference. Fortunately, this can be mitigated, when the channel matrices show a sufficient spatial separation. In paper, we quantify separability of channels using actual measurements in scenario where single outdoor base station...

Dynamic Spectrum Access (DSA) is receiving considerable interest as a means to improve spectral usage in licensed bands. In order avoid interference users, spectrum sensing has emerged an enabling technology for DSA. The requirements sensors are stringent, user detection must be performed reliably at low signal-to-noise ratios (SNR). Sensing performance can improved by exploiting signal features not present the background noise. These approaches result tradeoffs among and robustness...

Saddlepoint approximations of the meta-converse and random-coding union bounds are derived. These accurately characterize channel coding minimum error probability for symmetric memoryless channels in a wide range system parameters. The proposed simple to compute yield unified analysis both hypothesis-testing lower upper bounds.

Two alternative exact characterizations of the minimum error probability Bayesian M-ary hypothesis testing are derived. The first expression corresponds to an induced binary test and implies tightness meta-converse bound by Polyanskiy et al.; second is a function information-spectrum measure generalized Verdú-Han lower bound. formulas characterize several problems in information theory help identify steps where existing converse bounds loose.

In recent years, the derivation of nonasymptotic converse and achievability bounds on maximum coding rate as a function error probability blocklength has gained attention in information theory literature. While these are accurate for many scenarios interest, they need to be evaluated numerically most wireless channels practical their evaluation is computationally demanding. This paper presents saddlepoint approximations state-of-the-art noncoherent, single-antenna, Rayleigh block-fading...

Many problems in digital communications involve wideband radio signals. As the most recent example, impressive advances Cognitive Radio systems make even more necessary development of sampling schemes for signals with spectral holes. This is equivalent to considering a sparse multiband signal framework Compressive Sampling theory. Starting from previous results on multicoset and compressive sampling, we analyze matrix involved corresponding reconstruction equation define new method design...

Multiple-antenna detection of a Gaussian signal with spatial rank one in temporally white noise arbitrary and unknown covariance is considered. This motivated by spectrum sensing problems the context dynamic access which several secondary networks coexist but do not cooperate, creating background spatially correlated broadband interference. When temporal correlation interest assumed known up to scale factor, corresponding Generalized Likelihood Ratio Test shown yield scalar optimization...

We propose a saddlepoint approximation of the error probability binary hypothesis test between two i.i.d. distributions. The is accurate, simple to compute, and yields unified analysis in different asymptotic regimes. proposed formulation used efficiently compute meta-converse lower bound for moderate block-lengths several cases interest.

Dynamic spectrum leasing (DSL) is one of the schemes proposed for dynamic sharing (DSS) in cognitive radio networks. In DSL, owners, denoted as primary users, dynamically adjust amount secondary interference they are willing to tolerate response demand from transmitters. this correspondence we investigate how much can be gained by users if limited interaction with system allowed, compared a scheme which cap allowed fixed {a priori} regulatory authority. To that end, define performance...

Certain deterministic interference channels have been shown to accurately model Gaussian in the asymptotic low-noise regime. Motivated by this correspondence, we investigate a K user-pair, cyclically symmetric, channel which each receiver experiences only from its neighboring transmitters (Wyner model). We establish sum capacity for large set of parameters, thus generalizing previous results 2-pair case.

The cognitive radio paradigm is based on the ability to detect presence of primary users in a given frequency band. In this scenario spectrum monitor may estimate signal power levels all channels band interest, together with background noise level. We address Maximum Likelihood estimation for problem, exploiting <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</i> xmlns:xlink="http://www.w3.org/1999/xlink">priori</i> knowledge about network,...

In Cognitive Radio scenarios channelization information from primary network may be available to the spectral monitor. Under this assumption we propose a estimation algorithm compressed measurements of multichannel wideband signal. The analysis Cramer-Rao Lower Bound (CRLB) for problem shows importance detecting underlaying sparsity pattern To end describe Bayesian based iterative that discovers set active signals conforming band and simultaneously reconstructs spectrum. This estimator is...

We address the problem of primary user detection in Cognitive Radio from a wideband signal comprising multiple channels, exploiting priori knowledge about network: channelization and spectral shape transmissions. Using this second-order statistical information, multichannel Gaussian model is formulated. In order to obtain generalized likelihood ratio test, we first maximum (ML) estimation power levels at different as well noise variance. The ML conditions suggest suboptimal closed-form...

This paper studies an almost-lossless source-channel coding scheme in which source messages are assigned to different classes and encoded with a channel code that depends on the class index. The performance is analyzed by means of random-coding error exponents validated simulation low-complexity implementation using existing codes. While each can be seen as concatenation code, overall improves separate approaches joint when number increases.

Random-coding exact characterizations and bounds to the error probability of joint source-channel coding are presented. In particular, upper using maximum-a-posteriori threshold decoding derived as well a lower bound motivated by Verdú-Han's lemma.

This paper studies the random-coding exponent of joint source-channel coding for a scheme where source messages are assigned to disjoint subsets (referred as classes), and codewords independently generated according distribution that depends on class index message. For discrete memoryless systems, two optimally chosen classes product distributions found be sufficient attain sphere-packing in those cases it is tight.

We establish the generalized likelihood ratio (GLR) test for a Gaussian signal of known power spectral shape and unknown rank-one spatial signature in additive white noise with an diagonal correlation matrix. This is motivated by spectrum sensing problems dynamic access, which temporal primary can be assumed up to scaling, where due uncalibrated receive array. For spatially independent identically distributed (i.i.d.) noise, corresponding GLR reduces scalar optimization problem, whereas...

We consider the problem of detecting a primary signal over wireless channel by multiantenna cognitive spectral monitor with knowledge shape transmissions employing multicarrier modulation. As starting point, Locally Most Powerful (LMP) test is derived for single-antenna case. The asymptotic performance improvement LMP detector standard Energy Detector (ED) quantified in terms mask. For case an ideal bandpass mask Uniformly Powerful. With multiple antennas, optimal detectors require and...

Spectrum sensing is a key component of the Cognitive Radio paradigm. Multiantenna detectors can exploit different spatial features primary signals in order to boost detection performance and robustness very low signal-to-noise ratios. However, several cases these require additional information, such as rank covariance matrix received signal. In this work we study problem estimating under Gaussianity assumption using an uncalibrated receiver, i.e. with (unknown) noise levels at each antennas.

We study a source-channel coding scheme in which source messages are assigned to classes and encoded using channel code that depends on the class index. While each can be seen as concatenation of code, overall performance improves separate approaches joint number increases. The this is studied by means random-coding bounds validated simulation low-complexity implementation existing codes.

Based on the hypothesis-testing method, we derive lower bounds average error probability of finite-length joint source-channel coding. The extension meta-converse bound channel coding to depends codebook and decoding rule thus, it is a priori computationally challenging. Weaker versions this general recover known converses in literature provide feasible expressions.

This paper presents saddlepoint approximations of state-of-the-art converse and achievability bounds for noncoherent, single-antenna, Rayleigh block-fading channels. These can be calculated efficiently are shown to accurate SNR values as small 0 dB, blocklengths 168 channel uses or more, when the channel's coherence interval is not smaller than two. It demonstrated that derived recover both normal approximation reliability function channel.