scholarly journals DSP-based Mitigation of RF Front-end Non-linearity in Cognitive Wideband Receivers

Frequenz ◽  
2012 ◽  
Vol 66 (9-10) ◽  
Author(s):  
Michael Grimm ◽  
Rajesh K. Sharma ◽  
Matthias A. Hein ◽  
Reiner S. Thomä
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Communication Systems ◽  
Measurement Data ◽  
Digital Signal ◽  
Software Defined Radios ◽  
Front End ◽  
Non Linear ◽  
Rf Performance ◽  
Processing Techniques

AbstractSoftware defined radios are increasingly used in modern communication systems, especially in cognitive radio. Since this technology has been commercially available, more and more practical deployments are emerging and its challenges and realistic limitations are being revealed. One of the main problems is the RF performance of the front-end over a wide bandwidth.This paper presents an analysis and mitigation of RF impairments in wideband front-ends for software defined radios, focussing on non-linear distortions in the receiver. We discuss the effects of non-linear distortions upon spectrum sensing in cognitive radio and analyse the performance of a typical wideband software-defined receiver. Digital signal processing techniques are used to alleviate non-linear distortions in the baseband signal. A feed-forward mitigation algorithm with an adaptive filter is implemented and applied to real measurement data. The results obtained show that distortions can be suppressed significantly and thus increasing the reliability of spectrum sensing.

scholarly journals Spectrum Sensing Based on Nonparametric Autocorrelation in Wireless Communication Systems under Alpha Stable Noise

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Riqing Chen ◽  
Jun Wang ◽  
Ruiquan Lin ◽  
Xiangning Zhao
Keyword(s):  
Information Systems ◽  
Cognitive Radio ◽  
Wireless Communication ◽  
Spectrum Sensing ◽  
Communication Systems ◽  
Impulsive Noise ◽  
Wireless Communication Systems ◽  
Core Technology ◽  
Key Steps ◽  
Stable Noise

Cognitive radio is regarded as a core technology to support wireless information systems. Spectrum sensing is one of the key steps to achieve cognitive radio technology. To address this problem in the presence of Alpha stable noise in wireless communication systems, we propose a nonparametric autocorrelation method, which takes advantages of the characteristics of signal autocorrelation and noise nonstationarity. The autocorrelated signal is distinguished from Alpha stable noise. As a result, the proposed method is immune from noise uncertainty. Simulation results show the validity of the proposed method under Alpha stable noise, for example, impulsive noise in wireless information systems.

Highly flexible cognitive radio spectrum sensing front-end

2014 ◽  
Author(s):  
Peter Lohmiller ◽  
Ahmed Elsokary ◽  
Sebastien Chartier ◽  
Hermann Schumacher
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Radio Spectrum ◽  
Front End

A 0.7 – 2.6 GHz high-linearity rf front-end for cognitive radio spectrum sensing

2011 ◽  
Author(s):  
Kari Stadius ◽  
Mikko Kaltiokallio ◽  
Jussi Ollikainen ◽  
Tuomas Parnanen ◽  
Ville Saari ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Radio Spectrum ◽  
High Linearity ◽  
Front End ◽  
Rf Front End

scholarly journals Algorithm for Evaluating Energy Detection Spectrum Sensing Performance of Cognitive Radio MIMO-OFDM Systems

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6881
Author(s):  
Josip Lorincz ◽  
Ivana Ramljak ◽  
Dinko Begusic
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Detection Threshold ◽  
Operating Parameter ◽  
Energy Detection ◽  
Operating Parameters ◽  
Ofdm Systems ◽  
Mimo Ofdm

Cognitive radio technology enables spectrum sensing (SS), which allows the secondary user (SU) to access vacant frequency bands in the periods when the primary user (PU) is not active. Due to its minute implementation complexity, the SS approach based on energy detection (ED) of the PU signal has been analyzed in this paper. Analyses were performed for detecting PU signals by the SU in communication systems exploiting multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) transmission technology. To perform the analyses, a new algorithm for simulating the ED process based on a square-law combining (SLC) technique was developed. The main contribution of the proposed algorithm is enabling comprehensive simulation analyses of ED performance based on the SLC method for versatile combinations of operating parameter characteristics for different working environments of MIMO-OFDM systems. The influence of a false alarm on the detection probability of PU signals impacted by operating parameters such as the signal-to-noise ratios, the number of samples, the PU transmit powers, the modulation types and the number of the PU transmit and SU receive branches of the MIMO-OFDM systems have been analyzed in the paper. Simulation analyses are performed by running the proposed algorithm, which enables precise selection of and variation in the operating parameters, the level of noise uncertainty and the detection threshold in different simulation scenarios. The presented analysis of the obtained simulation results indicates how the considered operating parameters impact the ED efficiency of symmetric and asymmetric MIMO-OFDM systems.

Review

2019 ◽  
pp. 100-122
Author(s):  
Madhushi P. Ranasinghe ◽  
Malka N. Halgamuge
Keyword(s):  
Energy Efficiency ◽  
Cognitive Radio ◽  
Network Management ◽  
Spectrum Sensing ◽  
Communication Systems ◽  
Research Work ◽  
Optimal Solution ◽  
Spectrum Allocation ◽  
Scientific Publications ◽  
Work Related

Cognitive radio technology (CRNs) will be the fundamental driving force behind the next generation (5G) mobile communication systems as it provides the optimal solution for the problem of spectrum scarcity via dynamic spectrum usage. The CRNs, however, pose several key challenges such as network management, spectrum allocation, and access, energy efficiency, interference, cost, spectrum sensing, security, and quality of service (QoS). In this chapter, the authors undertake a comprehensive analysis of 30 peer-reviewed scientific publications collated from 2017 to 2018 April that examine cognitive radio networks to identify practical solutions proposed to overcome critical challenges in this field. Nine distinct challenges were considered: network management, spectrum allocation, and access, energy efficiency, interference, cost, spectrum sensing, security, and QoS. The analysis demonstrates that the majority of research work related to CRN focuses on approaches to improve network management and, specifically, optimization of networks.

Tunable RF Front-Ends and Robust Sensing Algorithms for Cognitive Radio Receivers

2015 ◽  
pp. 68-99
Author(s):  
L. Safatly ◽  
A. H. Ramadan ◽  
M. Al-Husseini ◽  
Y. Nasser ◽  
K. Y. Kabalan ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Learning Mechanisms ◽  
Radio Receivers ◽  
Front End ◽  
Rf Front End ◽  
Rf Impairments ◽  
Cognitive Radio Receivers ◽  
Robust Sensing ◽  
Efficiency Consideration

In this chapter, the concepts of Cognitive Radio (CR) and multi-dimensional spectrum sensing are introduced. Spectrum sensing methodologies, energy efficiency consideration, resources scheduling, and self-management and learning mechanisms in cognitive radio networks are also discussed. The entailed challenges of CR RF front-end architectures are looked into. The synthesis and design performance analysis of a tunable RF front-end sensing receiver for CR applications are presented. The chapter also discusses how sensing performance degradation, which is due to RF impairments, is analytically evaluated. Spectrum sensing algorithms that correct imperfect RF issues by compensating induced error effects through digital baseband processing are also illustrated.

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