A tree-structured DFT filter bank based spectrum detector for estimation of radio channel edge frequencies in cognitive radios

AbstractCognitive radio (CR) technology with dynamic spectrum management capabilities is widely advocated for utilizing effectively the unused spectrum resources. The main idea behind CR technology is to trigger secondary communications to utilize the unused spectral resources. However, CR technology heavily relies on spectrum sensing techniques which are applied to estimate the presence of primary user (PU) signals. This paper firstly focuses on novel analysis filter bank (AFB) and FFT-based cooperative spectrum sensing (CSS) techniques as conceptually and computationally simplified CSS methods based on subband energies to detect the spectral holes in the interesting part of the radio spectrum. To counteract the practical wireless channel effects, collaborative subband-based approaches of PU signal sensing are studied. CSS has the capability to relax the problems of both hidden nodes and fading multipath channels. FFT- and AFB-based receiver side sensing methods are applied for OFDM waveform and filter bank-based multicarrier (FBMC) waveform, respectively, the latter one as a candidate beyond-OFDM/beyond-5G scheme. Subband energies are then applied for enhanced energy detection (ED)-based CSS methods that are proposed in the context of wideband, multimode sensing. Our first case study focuses on sensing potential spectral gaps close to relatively strong primary users, considering also the effects of spectral regrowth due to power amplifier nonlinearities. The study shows that AFB-based CSS with FBMC waveform is able to improve the performance significantly. Our second case study considers a novel maximum–minimum energy detector (Max–Min ED)-based CSS. The proposed method is expected to effectively overcome the issue of noise uncertainty (NU) with remarkably lower implementation complexity compared to the existing methods. The developed algorithm with reduced complexity, enhanced detection performance, and improved reliability is presented as an attractive solution to counteract the practical wireless channel effects under low SNR. Closed-form analytic expressions are derived for the threshold and false alarm and detection probabilities considering frequency selective scenarios under NU. The validity of the novel expressions is justified through comparisons with respective results from computer simulations.

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Filter Bank Spectrum Sensing for Cognitive Radios

IEEE Transactions on Signal Processing ◽

10.1109/tsp.2007.911490 ◽

2008 ◽

Vol 56 (5) ◽

pp. 1801-1811 ◽

Cited By ~ 241

Author(s):

B. Farhang-Boroujeny

Keyword(s):

Spectrum Sensing ◽

Filter Bank ◽

Cognitive Radios

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A Low Complexity Reconfigurable Filter Bank Architecture for Spectrum Sensing in Cognitive Radios

2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008) ◽

10.1109/crowncom.2008.4562506 ◽

2008 ◽

Cited By ~ 11

Author(s):

R. Mahesh ◽

A. P. Vinod ◽

Christophe Moy ◽

Jacques Palicot

Keyword(s):

Spectrum Sensing ◽

Filter Bank ◽

Cognitive Radios ◽

Low Complexity

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Design of a Power-Efficient Low Complexity Non Maximally Coefficient Symmetry Multi Rate Filter Bank for Wideband Channelization

International Journal of Circuits, Systems and Signal Processing ◽

10.46300/9106.2021.15.95 ◽

2021 ◽

Vol 15 ◽

pp. 883-894

Author(s):

Kirti Samir Vaidya ◽

C. G. Dethe ◽

S. G. Akojwar

Keyword(s):

Wireless Communication ◽

Software Defined Radio ◽

Filter Bank ◽

Radio Channel ◽

Software Radio ◽

Low Complexity ◽

Power Efficient ◽

Complex Part ◽

Computing Complexity ◽

Hardware Efficiency

A solution for existing and upcoming wireless communication standards is a software-defined radio (SDR) that extracts the desired radio channel. Channelizer is supposed to be the computationally complex part of SDR. In multi-standard wireless communication, the Software Radio Channelizer is often used to extract individual channels from a wideband input signal. Despite the effective channelizer design that reduces computing complexity, delay and power consumption remain a problem. Thus, to promote the effectiveness of the channelizer, we have provided the Non-Maximally Coefficient Symmetry Multirate Filter Bank. In this paper, to improve the hardware efficiency and functionality of the proposed schemes, we propose a polyphase decomposition and coefficient symmetry incorporated into the Non-Maximally Coefficient Symmetry Multirate Filter Bank. For sharp wideband channelizers, the proposed methods are suitable. Furthermore, polyphase decomposition filter and coefficient symmetry is incorporated into the Non-Maximally Coefficient Symmetry Multirate Filter Bank to improve the hardware efficiency, power efficient, flexibility, reduce hardware size and functionality of the proposed methods. To prove the complexity enhancement of the proposed system, the design to be the communication standard for complexity comparison.

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Leveraging on the Cognitive Radio Channel Aggregation Strategy for Next Generation Utility Networks

Energies ◽

10.3390/en12142753 ◽

2019 ◽

Vol 12 (14) ◽

pp. 2753

Author(s):

Esenogho Ebenezer ◽

Theo. Swart ◽

Thokozani Shongwe

Keyword(s):

Cognitive Radio ◽

Radio Channel ◽

Cognitive Radios ◽

Self Awareness ◽

Power Network ◽

Next Generation ◽

Power Utility ◽

Proposed Model ◽

Utility Network ◽

The Cost

Integrating cognitive radio into the current power grid is designed to enable smart communication and decisions within the grid. Communication within the grid is not feasible without channel(s) and most studies have emphasized the use of cellular spectrum. This study proposes a strategy that enables the use of television white space (TVWS) within the grid. To be specific, we propose using a next-generation utility network (Next-GUN), which leverages on the cognitive radio (CR) channel aggregation capability. This strategy enables the aggregation of idle TVWS into a usable channel, thus making the Next-GUN different from the traditional power network. Next-GUN differs in terms of security, reliability, self-awareness, and cross-layer compatibility to the interface, and conveys different traffic classes, thereby making it a hybrid system. It has no dedicated channel assigned to it, and hence, utilizes the idle TVWS opportunistically to transmit data. The proposed scheme was modelled as a Markovian process and analyzed using a continuous time Markov chain (CTMC). Extensive system simulations were performed to evaluate this proposed model and the corresponding comparison with the literature was done to see the improvement. The result of our comparisons shows that when channels are aggregated, more data/information are transmitted. In addition, the use of cognitive radios on a power network enables smart transaction because idle TVWS is utilized instead of congesting the GSM spectrum. Lastly, the power utility establishment can save the cost of paying for a licensed spectrum.

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