600 research outputs found
Cooperative Spectrum Sensing based on 1-bit Quantization in Cognitive Radio Networks
The wireless frequency spectrum is a very valuable resource in the field of communications. Over the years, different bands of the spectrum were licensed to various communications systems and
standards. As a result, most of the easily accessible parts of it ended up being theoretically occupied.
This made it somewhat difficult to accommodate new wireless technologies, especially with the rise of communications concepts such as the Machine to Machine (M2M) communications and the Internet of Things (IoT). It was necessary to find ways to make better use of wireless spectrum.
Cognitive Radio is one concept that came into the light to tackle the problem of spectrum utilization. Various technical reports stated that the spectrum is in fact under-utilized. Many frequency bands are
not heavily used over time, and some bands have low activity. Cognitive Radio (CR) Networks aim to exploit and opportunistically share the already licensed spectrum. The objective is to enable various kinds of communications while preserving the licensed parties' right to access the spectrum without interference.
Cognitive radio networks have more than one approach to spectrum sharing. In interweave spectrum sharing scheme, cognitive radio devices look for opportunities in the spectrum, in frequency and over time. Therefore, and to find these opportunities, they employ what is known as spectrum sensing. In a
spectrum sensing phase, the CR device scans certain parts of the spectrum to find the voids or white spaces in it. After that it exploits these voids to perform its data transmission, thus avoiding any
interference with the licensed users.
Spectrum sensing has various classifications and approaches. In this thesis, we will present a general review of the main spectrum sensing categories. Furthermore, we will discuss some of the techniques employed in each category including their respective advantages and disadvantages, in addition to
some of the research work associated with them.
Our focus will be on cooperative spectrum sensing, which is a popular research topic. In cooperative spectrum sensing, multiple CR devices collaborate in the spectrum sensing operation to enhance the performance in terms of detection accuracy. We will investigate the soft-information decision fusion approach in cooperative sensing. In this approach, the CR devices forward their spectrum sensing data to a central node, commonly known as a Fusion Center. At the fusion center, this data is combined to achieve a higher level of accuracy in determining the occupied parts and the empty parts of the spectrum while considering Rayleigh fading channels. Furthermore, we will address the issue of
high power consumption due to the sampling process of a wide-band of frequencies at the Nyquist rate. We will apply the 1-bit Quantization technique in our work to tackle this issue. The simulation results show that the detection accuracy of a 1-bit quantized system is equivalent to a non-quantized system with only 2 dB less in Signal-to-Noise Ratio (SNR). Finally, we will shed some light on multiple antenna spectrum sensing, and compare its performance to the cooperative sensing
A Framework to Analyze Energy Efficiency of Multi-Band Spectrum Sensing Algorithms
Cognitive radio (CR) is a device which can detect wireless communication channels that are not in use and adapt its parameters intelligently. Networks with CRs use the available frequency bands much more efficiently and hence have higher data rates compare to traditional radios. Spectrum sensing is the class of techniques used by CRs to understand its wireless environment. Recent research on evaluating multi-band spectrum sensing algorithms is limited to only algorithm complexity and optimization; therefore, the primary goal of the study is to devise a novel framework that analyzes a multi-band spectrum sensing algorithm in terms of energy consumption and algorithm efficiency. The proposed structure leads to a comparison and evaluation of a large class of multi-band spectrum sensing algorithms. Multi-band spectrum sensing search methods such as linear, random and binary are evaluated for energy loss and detection performance using the proposed framework
FPGA based Uniform Channelizer Implementation
Channelizers are widely used in modern digital communication systems.
Advanced uniform multirate channelization have been theoretically proved to be
capable of reducing the computational load, with a better performance. Therefore,
in this thesis, we implement these designs on a FPGA board for the sake of the
comprehensive evaluation of resource usage, performance and frequency
response.
The uniform filter-banks are one of the most essential unit in channelization. The
Generalised Discrete Fourier Transform Modulated Filter Bank (GDFT-FB), as an
important variant of basic a DFT-FB, has been implemented in FPGA and
demonstrated with a better computational saving rather than traditional schemes.
Moreover the oversampling version is demonstrated to have a better frequency
response with an acceptable amount of extra resources. On the other hand,
frequency response masking (FRM) techniques is able to reduce the number of
coefficients. Therefore, the full FRM GDFT-FB and alternative narrowband FRM
GDFT-FB are both implemented in FPGA platform, in order to achieve a better
performance and hardware efficiency
Single- versus Multi-Carrier Terahertz-Band Communications: A Comparative Study
The prospects of utilizing single-carrier (SC) and multi-carrier (MC)
waveforms in future terahertz (THz)-band communication systems remain
unresolved. On the one hand, the limited multi-path components at high
frequencies result in frequency-flat channels that favor low-complexity
wideband SC systems. On the other hand, frequency-dependent molecular
absorption and transceiver characteristics and the existence of multi-path
components in indoor sub-THz systems can still result in frequency-selective
channels, favoring off-the-shelf MC schemes such as orthogonal
frequency-division multiplexing (OFDM). Variations of SC/MC designs result in
different THz spectrum utilization, but spectral efficiency is not the primary
concern with substantial available bandwidths; baseband complexity, power
efficiency, and hardware impairment constraints are predominant. This paper
presents a comprehensive study of SC/MC modulations for THz communications,
utilizing an accurate wideband THz channel model and highlighting the various
performance and complexity trade-offs of the candidate schemes. Simulations
demonstrate that discrete-Fourier-transform spread orthogonal time-frequency
space (DFT-s-OTFS) achieves a lower peak-to-average power ratio (PAPR) than
OFDM and OTFS and enhances immunity to THz impairments and Doppler spreads, but
at an increased complexity cost. Moreover, DFT-s-OFDM is a promising candidate
that increases robustness to THz impairments and phase noise (PHN) at a low
PAPR and overall complexity.Comment: 18 pages, 12 figures, journa
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