Transmit power control and data rate enhancement in cognitive radio network using computational intelligence

Underutilized radio frequencies are the chief apprehension in advance radio communication. The radio recourses are sparse and costly and their efficient allocation has become a challenge. Cognitive radio networks are the ray of hope. Cognitive radio networks use dynamic spectrum access technique to opportunistically retrieve and share the licensed spectrum. The licensed users are called primary users and the users that opportunistically access the licensed spectrum all called secondary users. The proposed system is a feedback system that work on demand and supply concept, in which secondary receivers senses the vacant spectrum and shares the information with the secondary transmitters. The secondary transmitters adjust their transmission parameters of transmit power and data rate in such a way that date rate is maximized. Two methods of spectrum access using frequency division multiple access (FDMA) and Time division multiple access (TDMA) are discussed. Interference temperature limit and maximum achievable capacity are the constraints that regulate the entire technique. The aim of the technique is to control the transmitter power according to the data requirements of each secondary user and optimizing the resources like bandwidth, transmit power using machine learning and feed forward back propagation deep neural networks making full use of the network capacity without hampering the operation of primary network.

Unification of Broadband and Broadcast Mobile Services using Cognitive Radio

The networks in future generation uses the confluence of multi-media, broadband, and broadcast services, Cognitive Radio (CR) networks are located as a preferred paradigm to bring up with spectrum functionality traumatic conditions. CRS addresses the ones troubles via dynamic spectrum access. However, the precept traumatic conditions faced through manner of manner of the CR pertain to accomplishing spectrum overall performance. At the end, spectrum overall performance improvement models based on spectrum sensing and sharing models have attracted quite a few research hobby in modern-day years, which incorporates CR mastering models, network densification architectures, and Massive Multiple Input Multiple Output (MIMO), and beamforming techniques. This paper deals with a survey of modern CR spectrum overall improvement performance models and techniques which helps ultra-high reliability with low latency communications which might be resilient to surges in web page site visitors and competition for spectrum. These models and techniques, mainly speaks about permit a big form of functionality beginning from extra superb mobiliary broadband to large-scale Internet of Things (IoT) type communications. It also provides a research correlation for many of the regular periods of a spectrum block, as well as the realistic statistics rate, the models which are used in this paper are applicable in an ultra-high frequency band. This study provides a super compare of CRs and direction for future investigations into newly identified 5G research areas, such as in business enterprise and academia.

Enhanced Dynamic Spectrum Access in UAV Wireless Networks for Post-Disaster Area Surveillance System: A Multi-Player Multi-Armed Bandit Approach

Modern wireless networks are notorious for being very dense, uncoordinated, and selfish, especially with greedy user needs. This leads to a critical scarcity problem in spectrum resources. The Dynamic Spectrum Access system (DSA) is considered a promising solution for this scarcity problem. With the aid of Unmanned Aerial Vehicles (UAVs), a post-disaster surveillance system is implemented using Cognitive Radio Network (CRN). UAVs are distributed in the disaster area to capture live images of the damaged area and send them to the disaster management center. CRN enables UAVs to utilize a portion of the spectrum of the Electronic Toll Collection (ETC) gates operating in the same area. In this paper, a joint transmission power selection, data-rate maximization, and interference mitigation problem is addressed. Considering all these conflicting parameters, this problem is investigated as a budget-constrained multi-player multi-armed bandit (MAB) problem. The whole process is done in a decentralized manner, where no information is exchanged between UAVs. To achieve this, two power-budget-aware PBA-MAB) algorithms, namely upper confidence bound (PBA-UCB (MAB) algorithm and Thompson sampling (PBA-TS) algorithm, were proposed to realize the selection of the transmission power value efficiently. The proposed PBA-MAB algorithms show outstanding performance over random power value selection in terms of achievable data rate.

Performance Analyses of Energy Detection Based on Square-Law Combining in MIMO-OFDM Cognitive Radio Networks

Cognitive radio (CR) technology has the potential to detect and share the unutilized spectrum by enabling dynamic spectrum access. To detect the primary users’ (PUs) activity, energy detection (ED) is widely exploited due to its applicability when it comes to sensing a large range of PU signals, low computation complexity, and implementation costs. As orthogonal frequency-division multiplexing (OFDM) transmission has been proven to have a high resistance to interference, the ED of OFDM signals has become an important local spectrum-sensing (SS) concept in cognitive radio networks (CRNs). In combination with multiple-input multiple-output (MIMO) transmissions, MIMO-OFDM-based transmissions have started to become a widely accepted air interface, which ensures a significant improvement in spectral efficiency. Taking into account the future massive implementation of MIMO-OFDM systems in the fifth and sixth generation of mobile networks, this work introduces a mathematical formulation of expressions that enable the analysis of ED performance based on the square-law combining (SLC) method in MIMO-OFDM systems. The analysis of the ED performance was done through simulations performed using the developed algorithms that enable the performance analysis of the ED process based on the SLC in the MIMO-OFDM systems having a different number of transmit (Tx) and receive (Rx) communication branches. The impact of the distinct factors including the PU Tx power, the false alarm probability, the number of Tx and Rx MIMO branches, the number of samples in the ED process, and the different modulation techniques on the ED performance in environments with different levels of signal-to-noise ratios are presented. A comprehensive analysis of the obtained results indicated how the appropriate selection of the analyzed factors can be used to enhance the ED performance of MIMO-OFDM-based CRNs.

Investigation of Radio Frequency Licensed Spectrum Utilization in Nigeria: A Study of Rumuokwuta, Port Harcourt, Nigeria

This study was carried out to investigate the spectrum utilization of the licensed Radio Frequency (RF) spectrum in Rumuokwuta, Port Harcourt. An outdoor measurement of spectrum occupancy was carried out in a high-rise building situated at Rumuokwuta urban area in Port Harcourt, Nigeria using RF explorer spectrum analyzer and a personal computer laptop system. Spectrum activities in the band of 240-960 MHz were monitored for 24 hours. The frequency band was subdivided into 24 sub bands each with a span size of 30 MHz. Scanning of bands was made efficient using a python script that scans a range, analyzed the frequencies and signal strengths for 112 data points, saves data in CSV file format, scans the next range until the 24 ranges were scanned. The process was repeated to achieve 15 iterations. With a noise floor of - 110dBm, a threshold of -95dBm was used to determine the presence of signal, hence the spectrum occupancy of measured bands. Results showed that out of the 24 investigated sub bands; only one band was completely occupied with spectrum occupancy of 100%. 12 bands were partially occupied while 11 were completely free. The average spectrum occupancy for the whole band was obtained as 11.64%. This showed good location for dynamic spectrum access and cognitive radio deployment, especially in Television White Space (TVWS).

Three Dimensional Measuring Points Locating Algorithm Based Texture-Patched Matrix Completion Algorithm for Indoor 3D REM Design

In this paper, a novel texture-patch transformed (TPT) three dimensional (3D) matrix completion (MC) method has been proposed with the support of novel 3D measuring points (MPs) locating algorithm to generate practical received signal strength (RSS) database assisted indoor 3D radio environment map (REM) of ultra-high frequency (UHF) television (TV)-band. The exploration of TV-band results in TV white and grey space (TV-WS and TV-GS), which are competent resolution to recoup excess data traffic through cognitive radio networks (CRNs) by dynamic spectrum access (DSA) by secondary user (SU). Maximum wireless data traffic generates in indoor and altitude considered exploration of REM achieves high data rate, so selecting interpolation algorithm is important for getting accurate and timely generated REM. Many MC algorithm shows better results than standard interpolation methods. Instead of using layer-by-layer MC algorithm, TPT-MC algorithm could be used through 3D↔2D conversion. Patch size has been considered through symmetric dataset profile. MC criteria based analysis shows TPT-MC algorithm takes lesser no. of MPs than layer-by-layer MC algorithm. Singular value thresholding (SVT) algorithm is used MC algorithm. TPT-SVT shows advantage over layer-by-layer SVT algorithm on RMSE, correlation, best-fit-line and simulation time on same no. of dataset. The result analysis shows that TPT-SVT algorithm is better in RMSE, closest best-fit-line and correlation coefficient than 2D IDW2, 2D K-NN, 2D kriging, TPT-IDW2, TPT-K-NN, TPT-kriging, 3D IDW2 and layer-by-layer SVT algorithm. Computation time of TPT-SVT is better than 3D IDW2 and SVT. TPT-SVT algorithm takes lesser no. of dataset than SVT algorithm for faithful MC.