Radio Paradigm Research Articles

Artificial intelligence driven cognitive optimization and predictive analysis using blockchain privacy-based machine learning model

According to the cognitive radio paradigm, spectrum sensing, decision-making, sharing, and mobility phases can be integrated to enable both authorised and unauthorised users to coexist in the radio-electric spectrum to the fullest extent possible. Using a blockchain privacy model and ML approaches in a B5G network, this study suggests a new approach to cognitive network optimisation and predictive analysis which stands for blockchain privacy-based transfer encoder neural networks. One further step is to optimise the network using binary swarm optimisation (BSMO). Bandwidth efficiency, throughput, forecast accuracy, and quality of service are the experimentally measured variables for a given number of channels and users. An innovative QoS-based optimisation phase and two separate decision-making procedures are proposed for usage in a proactive approach. One use of artificial neural networks (ANNs) is the prediction of future traffic loads for different radio access technologies (RATs), which employ different bands of the electromagnetic spectrum.

Level Process Station Control Using ALE111 Communication Module

A noteworthy example of the technological evolution is the ALE111, a cutting-edge system equipped with advanced functionalities designed to monitor the status of field wireless devices. One of its key features is the implementation of bumpless output, a capability that ensures seamless transitions and adjustments in the control process. Remarkably, the ALE111 enables wireless process control, a capability traditionally associated with wired control systems utilizing 4-20 mA signal communication. This wireless paradigm not only introduces a new level of flexibility but also contributes to the overall enhancement of process control reliability. The ALE111 goes a step further by incorporating redundant configurations, a strategic approach that adds an extra layer of reliability to the system. By doing so, potential points of failure are mitigated, and the overall robustness of the process control system is substantially improved. Key Word: ALE111 Communication Module, Ethernet, Level Process Station, Vnet, Field Control Station ,HIS, Data Acquisition Card

Soft Delivery: Survey on a New Paradigm for Wireless and Mobile Multimedia Streaming

The increasing demand for video streaming services is the key driver of modern wireless and mobile communications. Although many studies have designed digital-based delivery schemes to send video content over wireless and mobile networks, significant quality degradation, known as cliff and leveling effects, often occurs owing to fluctuating channel characteristics. In this article, we present a comprehensive summary of soft delivery, which is a new paradigm for wireless and mobile video streaming and discuss the future directions of soft delivery. Existing studies found that introducing multi-dimensional cosine transform, human vision system, and graph signal processing can make soft delivery schemes more effective in untethered immersive experiences, including virtual reality and volumetric media, than digital-based delivery schemes. In addition, this study finds that soft delivery has the potential to be a new standard to deliver deep neural network models and tactile information over wireless and mobile networks.

Middleton’s Class A Noise Parameter Estimator

For the development of communication systems that intend to be based on the cognitive radio paradigm, it is of vital importance to obtain the characteristics of the communication channel in a simple and fast way. This article presents a simple method for estimating the parameters of the probability density function, corresponding to Middleton’s Class A noise. The method is presented, justified and compared with different known estimators in terms of precision and simplicity, resulting in a notable advantage in its general performance and its possible implementation.

Some power allocation algorithms for cognitive uplink satellite systems

Cognitive satellite communication (SatCom) is rapidly emerging as a promising technology to overcome the scarcity of the exclusive licensed band model in order to fulfill the increasing demand for high data rate services. The paper addresses power allocation methods for multi-operator multi-beam uplink satellite communication systems co-existing with a Ka-band terrestrial network, using cognitive radio paradigm. Such a scenario is especially challenging because of (i) the coexisting multiple SatCom operators over the cognitive band need to coordinate the use of their resources under limited inter-operator information exchange, and (ii) nonlinear onboard high power amplifier (HPA) which leads to nonlinear interference between users and beams. In order to tackle the first challenge, we propose distributed power allocation algorithms including the standard Alternate Direction Multiplier Method (ADMM); Regarding the HPA nonlinear impairment, we propose nonlinear-aware power allocation based on Signomial Programming. The proposed solutions outperform state-of-the-art in both cases.

Transmissive Metasurfaces Assisted Wireless Communications on Railways: Channel Strength Evaluation and Performance Analysis

We propose a new wireless paradigm for railways – transmissive metasurface (TMS) assisted communications. It compensates for the Doppler shift brought by high mobility and reduces signal degradation due to train carriages. Specifically, the elements of the TMS panel attached to train windows manipulate the links between the base station (BS) and the onboard users. One fundamental problem with it is: does the channel introduced by TMS outperform the traditional direct channel? To answer this, we compare the gains of direct and cascaded channels and introduce the cascaded-outperform-direct probability (CODP), which is the probability that the latter exceeds the former. We then derive two simplified closed-form CODP expressions by approximating the cascaded channel gain as mixed Gaussian and Gamma distributions. Moreover, BS-related parameters impact the CODP; we show that the CODP has (i) global maximum points concerning the azimuth angle of the path from the BS to the TMS, the distance from the BS to the railway, and the BS height, respectively, and (ii) a minimum point in terms of the azimuth angle of the path from the BS to the TMS. Finally, we provide numerical results to verify our analysis and derivations.

The Millennial Medium: The Interpretive Community of Early Podcast Professionals

Through evidence gathered from sixteen interviews with producers and businesspeople in the podcast industry, this paper argues that the professionals that populated the early phase of the formalizing podcasting scene made up an interpretive community defined, in part, by their appreciation for, and experiences with, public radio. I chart how this interpretive community cast themselves against dominant public radio paradigms when they moved into podcasting, while also retaining much of public radio’s ethos, and I discuss what the central preoccupations of this interpretive community were. I assert that audio broadcasting as understood and practiced within the interpretive community is a particularly millennial medium, influenced by the norms of digital communication. And I make claims about how this is foundational to understanding podcasting’s political and aesthetic predispositions. Ultimately, this argument advances and nuances one connection between public radio and podcasting using qualitative interview data.

Drivers’ Warning Application Through Personalized DSSS-CDMA Data Transmission by Using the FM Radio Broadcasting Infrastructure

In this paper, a new drivers’ warning application through personalized Direct-Sequence Spread Spectrum Code-Division Multiple Access (DSSS-CDMA) transmissions, performed using the FM radio broadcasting infrastructure is presented. The proposed application is designed to simultaneously transmit a maximum of 15 low-resolution image notifications together with standard FM radio broadcasting in different geographical areas. The application is intended to warn drivers of significant driving events in major traffic areas of a country. The proposed solution is low-cost and rapid to put into practice because the modifications, both on the transmission infrastructure and on the receiver’s side, are relatively easy to implement. The transmission of image notifications is performed in subsidiary bands of commercial FM radio systems. The receiver is implemented using the Software-Defined Radio (SDR) paradigm and is able to extract the audio signal (corresponding to the usual FM transmission) and the data component, depending on the geographical area in which the vehicle is located. The receiver is based on a novel implementation of a modified Costas loop using two new nonlinear limiters. Appropriate image notification is selected using a specific decoding key, generated according to the geographical position of the vehicle. The performance of the data transmission system is analyzed by plotting the Bit Error Rate (BER) versus the signal-to-noise ratio of the data signal for different numbers of image notifications simultaneously transmitted. The proposed radio communication system was validated through an experimental setup based on Universal Software Radio Peripheral (USRP) devices driven by MATLAB/Simulink software.

Reconfigurable Intelligent Surface-Assisted Backscatter Communication: A New Frontier for Enabling 6G IoT Networks

Backscatter Communication (BackCom), which is based on passive reflection and modulation of an incident radio-frequency (RF) wave, has emerged as a cutting-edge technological paradigm for self-sustainable Internet-of-things (IoT). Nevertheless, contemporary BackCom systems are limited to short-range and low data rate applications only, rendering them insufficient on their own to support pervasive connectivity among the massive number of IoT devices. Meanwhile, wireless networks are rapidly evolving toward the smart radio paradigm. In this regard, reconfigurable intelligent surfaces (RISs) have come to the forefront to transform the wireless propagation environment into a fully controllable and customizable space in a cost-effective and energy-efficient manner. Targeting the sixth-generation (6G) horizon, we anticipate the integration of RISs into BackCom systems as a new frontier for enabling 6G IoT networks. In this article, for the first time in the open literature, we provide a tutorial overview of RIS-assisted BackCom (RIS-BackCom) systems. Specifically, we introduce the three different variants of RIS-BackCom and identify the potential improvements that can be achieved by incorporating RISs into BackCom systems. In addition, owing to the unrivaled effectiveness of non-orthogonal multiple access (NOMA), we present a case study on a RIS-assisted NOMA-enhanced BackCom system. Finally, we outline the way forward for translating this disruptive concept into real-world applications.

Reliability Optimization for Channel Resource Allocation in Multihop Wireless Network: A Multigranularity Deep Reinforcement Learning Approach

This article investigates the high-reliable data transmission for multihop and multichannel wireless sensor networks (WSNs), which jointly optimizes the channel allocation and channel access mechanisms. We propose a novel wireless paradigm empowered by mobile-edge computing (MEC) and deep reinforcement learning (DRL) to improve the data process ability of WSNs and formulate the joint resource allocation problem for reliability maximization as a partially observable Markov decision process (POMDP). Meanwhile, we introduce the distributed decision-making (DDM) framework to decouple channel optimization into two subproblems: 1) channel allocation and 2) channel access. Correspondingly, we present an asynchronous channel allocation algorithm for multiagent scenario and enable the neighbor cooperation to tackle the nonstationary problem, which can significantly improve the network convergence speed. Besides, we present a collision-free channel access algorithm including three submodules that can simultaneously eliminate vanishing nodes, hidden terminal, and exposed terminal problems in large-scale WSNs. Simulation results demonstrate that the proposed algorithm significantly improves network performance in terms of convergence, throughput, collision, and packet delivery ratio (PDR).

Performance Comparison of Energy Detection Based non – Cooperative Spectrum Sensing Techniques in Cognitive Radio

Cognitive radio is a ground-breaking software-defined radio paradigm that offers Dynamic spectrum access, allowing secondary users to use the frequency band allotted to the principal user when it is not in use and vacate when the prime application returns. The ability to sense the spectrum is critical to cognitive radio's efficiency. Energy detection sensing is the simplest and most often used spectrum sensing approach, owing to its ease of implementation in cognitive radio applications. The three-energy detection-based algorithms adopted for different scenarios have been compared in this study. The algorithms include the double-threshold energy detection, adaptive single threshold energy detection, and the adaptive double threshold spectrum sensing algorithm. Since the noise prediction in the practical situation is difficult, the necessity is to find the best algorithm in this condition. The other equally important parameters for efficiently sensing the spectrum are spectrum efficiency and less interference to the primary user. Simulation findings show that the adaptive double threshold approach outperforms the other two algorithms in all respect. The detection probability of the method is typically found to be substantially greater as compared to other two techniques. In addition, the likelihood of a false alarm is significantly reduced. Furthermore, when the signal-to-noise ratio value is low, often below -5dB, the performance of this approach is poor. MATLAB is used to run all of the simulations.

Extensive review on IoT security challenges and LWC implementation on tiny hardware for node level security evaluation

Internet-of-Things (IoT) offers a novel intelligent ecosystem that consists of various physical objects interconnected via the internet, which draws the attention of researchers, academicians, and industrialists. Various physical objects are embedded systems that perform dedicated operations that include sensing, monitoring, and controls. Such connectivity of embedded system devices over the internet creates an intelligent mesh worldwide and makes city, industry, and human life entirely automated and intelligent. However, the existing embedded system with radio modules is battery operated, referred to as a low-resourced device. Further, it is expected that the device should consume less operational power. Tiny size devices are offering less memory which creates a resource-constrained environment. An efficient hardware implementation of security algorithms is challenging in a constrained environment that satisfies all performance metrics. Standard internet connectivity of all devices with new wireless paradigms (e.g. ZigBee, LoRa, Wi-Fi, SigFox, etc.) essentially needs to be scrutinized for secured data communication and other security flaws. The universal connection allows an adversary to access secured technology via vulnerable systems. Many researchers are analyzing IoT technologies in every possible aspect to provide an economically secured solution. Importing software-tested encryption standards on hardware with efficient results can produce reliable IoT nodes. In this paper, we present the overview of IoT infrastructure with supporting data communication protocols. Also, we discussed essential cryptographic design rationale to minimize overall structure with the importance of metrics. Environmental and implementation based challenges, trade-off, and importance of cryptography towards the development of secured IoT node with Light-Weight Cipher (LWC) ANU and PRESENT proof-of-concept for generic application is provided in this research.

PU-DetNet: Deep Unfolding Aided Smart Sensing Framework for Cognitive Radio

Spectrum sensing in cognitive radio (CR) paradigm can be broadly categorized as analytical-based and data-driven approaches. The former is sensitive to model inaccuracies in evolving network environment, while the latter (machine learning (ML)/deep learning (DL) based approach) suffers from high computational cost. For devices with low computational abilities, such approaches could be rendered less useful. In this context, we propose a deep unfolding architecture namely the Primary User-Detection Network (PU-DetNet) that harvests the strength of both: analytical and data-driven approaches. In particular, a technique is described that reduces computation in terms of inference time and the number of floating point operations (FLOPs). It involves binding the loss function such that each layer of the proposed architecture possesses its own loss function whose aggregate is optimized during training. Compared to the state-of-the-art, experimental results demonstrate that at SNR= -10 dB, the probability of detection is significantly improved as compared to the long short term memory (LSTM) scheme (between 39% and 56%), convolutional neural network (CNN) scheme (between 45% and 84%), and artificial neural network (ANN) scheme (between 53% and 128%) over empirical, 5G new radio, DeepSig, satellite communications, and radar datasets. The accuracy of proposed scheme also outperforms other existing schemes in terms of the F1-score. Additionally, inference time reduces by 91.69%, 90.90%, and 93.15%, while FLOPs reduces by 62.50%, 56.25%, 64.70% w.r.t. LSTM, CNN and ANN schemes, respectively. Moreover, the proposed scheme also shows improvement in throughput by 56.39%, 51.23%, and 69.52% as compared to LSTM, CNN and ANN schemes respectively, at SNR = -6 dB.

PROMOTION OF UKRAINIAN-LANGUAGE RADIO PROGRAMS IN THE INFORMATION SPACE OF THE USA (EXPERIENCE OF 1930–1932)

<p><strong><em>The research objective </em></strong><em>is to introduce into the scientific discourse and information field of popular-science literature information about the establishing history of the world Ukrainian-language radio broadcasting, in particular in the context of its international sector.</em></p><p><strong><em>The methodological</em></strong><em> basis of the study is grounded on the use of historical method, the method of archival research, and is deepened by the bibliographic-descriptive method, the method of comparison in time, the method of induction and accentuation. The content of 913 issues of the oldest Ukrainian-language newspaper in the USA, </em><em>«</em><em>Svoboda</em><em>»</em><em>, in 1930–1932, was studied using the monitoring method; the use of qualitative content analysis allowed to comprehend the content of 375 materials of various genres, which contain valuable information on the analyzed topics.</em></p><p><strong><em>Results. </em></strong><em>The ways of promoting Ukrainian-language radio hours in the US media space in 1930</em><em>–</em><em>1932 were found out. It was established that the main ways to promote the media business of Ukrainians were personal communication and publication of advertising messages in the press. The tasks, types and efficiency of thematic event attractions, including competitions for the title of the best music groups, radio picnics, radio balls, radio entertainment balls, raffles, and later beauty contests, are studied. The importance of folk art in the context of the accumulation of interest in Ukrainian radio initiatives among the local community is emphasized. The genre diversity of thematic messages in the press was studied, in particular, the use of announcements, reports, advertisements, reviews, publication of listeners' letters. The advertising component of the Ukrainian-language radio space in the USA is evaluated, the first commercial program was analyzed, which consisted exclusively of advertisements. The potential of radio in promoting Ukrainian music groups, individual musicians and announcers is comprehended.</em></p><p><strong><em>Novelty.</em></strong><em> For the first time the methods of promotion of Ukrainian radio hours in the information field of the USA in 1930–1932 were carefully researched and documented, the competitive advantages and semantic potential of such programs in the conditions of rapid formation of the world radio space were comprehended.</em></p><p><strong><em>The practical significance </em></strong><em>of the research results lies in the introduction of the formation history aspects of Ukrainian emigration radio hours into the scientific discourse as a component of the world Ukrainian-language radio paradigm.</em></p><strong><em>Key words:</em></strong><em> archival periodicals, multicultural media space, radio business promotion, radio advertising function, Ukrainian-language radio broadcasting.</em>

A game theoretic power control and spectrum sharing approach using cost dominance in cognitive radio networks.

The wireless networks face challenges in efficient utilization of bandwidth due to paucity of resources and lack of central management, which may result in undesired congestion. The cognitive radio (CR) paradigm can bring efficiency, better utilization of bandwidth, and appropriate management of limited resources. While the CR paradigm is an attractive choice, the CRs selfishly compete to acquire and utilize available bandwidth that may ultimately result in inappropriate power levels, causing degradation in network’s Quality of Service (QoS). A cooperative game theoretic approach can ease the problem of spectrum sharing and power utilization in a hostile and selfish environment. We focus on the challenge of congestion control that results in inadequate and uncontrolled access of channels and utilization of resources. The Nash equilibrium (NE) of a cooperative congestion game is examined by considering the cost basis, which is embedded in the utility function. The proposed algorithm inhibits the utility, which leads to the decrease in aggregate cost and global function maximization. The cost dominance is a pivotal agent for cooperation in CRs that results in efficient power allocation. Simulation results show reduction in power utilization due to improved management in cognitive radio resource allocation.

Transmission State Prediction from MAC in Cognitive Radio via Optimized Deep Learning Architecture

Cognitive Radio (CR) is the hottest network paradigm, which permits the Secondary Users (SUs) like wireless devices/users for intelligent accessing of unallocated radio spectrum. Such accessing happens by enabling interference-free transmission of Primary Users (PUs), who are allotted with some deserved radio spectrum portions. This radio communication paradigm has effective usage in vehicular networks, where communication should be established from vehicles to static stations (vehicle-to-infrastructure) or within vehicles (vehicle-to-vehicle), without allotting dedicated frequencies. Nevertheless, the major issue in designing CR is that it must be built to aid in efficient transmitting and sensing of data through the available radio spectrum channels. This paper proposes a Model Predictive Control (MPC)-based prediction model, via a Deep Learning approach. Here, a Deep Belief Network (DBN) allows in predicting the PU transmission state as idle or busy. Moreover, this paper comes out with a new optimization concept that achieves more accurate and precise prediction. The weight of DBN is optimally selected to pave way for effective performance. Further, a new hybrid algorithm named as Cuckoo Search-Grasshopper Optimization Algorithm (CS-GOA) is proposed. The performance of the proposed model is compared over the other conventional models, in terms of channel utilization and back off, and proved for supremacy. The throughput of the proposed model, even at 50 SUs is better, when compared to other methods. CS-GOA achieved better channel utilization and backoff rate, as compared to ProMAC and NN, when the numbers of SUs and PUs in the architecture are varied with time.

On the Secrecy Performance of NOMA-Based Integrated Satellite Multiple-Terrestrial Relay Networks With Hardware Impairments

Integrated satellite terrestrial networks and non-orthogonal multiple access (NOMA) have been confirmed to be promising and effective approaches to achieve substantial performance gains for future wireless paradigms. This paper studies the effect of hardware impairments (HIs) on the secrecy performance of NOMA-based integrated satellite multiple-terrestrial relay networks (ISMTRNs). Particularly, we consider two important wiretapping cases: Case I, colluding case: all eavesdroppers cooperatively overhear the information; and Case II, non-colluding case: one eavesdropper with the best wiretapping quality is chosen to overhear the main channel information. Specially, the closed-form expressions for the secrecy outage probability (SOP) of the considered NOMA-based ISMTRNs in the presence of the above two eavesdropping cases and partial relay selection scheme are obtained. To obtain further insights in high signal-to-noise ratios (SNRs) regime, the asymptotic analysis of SOP with two considered cases are also derived, which give efficient means to evaluate the benefit of NOMA scheme and the impacts of HIs on the SOP. Moreover, we obtain Monte Carlo (MC) simulations for the secrecy energy efficiency (SEE).

A Double Auction Framework for Multi-Channel Multi-Winner Heterogeneous Spectrum Allocation in Cognitive Radio Networks

Opportunistic availability of licensed frequency bands enables the secondary users (SUs) to avail the radio spectrum dynamically. Cognitive radio (CR) paradigm extends the dynamic spectrum access techniques to sense for free channels (called spectrum holes) which can be efficiently redistributed amongst SUs. Motivated by the adaptive technology in CR, this paper introduces a sealed-bid double auction mechanism which aims to obtain an effective allocation of the unused radio spectrum. The proposed auction model adopts multi-channel allocation where one SU can access more than one available channel, while imposing the constraints for dynamics in spectrum opportunities and varying channel availability time amongst SUs. Previously designed double auctions miss out the CR constraints which can further degrade the network performance. Also, multi-winner allocation is induced in the model which encourages spectrum reuse by allowing a common channel to be assigned to multiple non-interfering SUs. A preference list of channels is maintained at each SU using which SUs offer their bid values for the heterogeneous channels which the primary owners are competing to lease. To organize channel specific groups of non-interfering SUs, a bidder group formation algorithm is developed such that members of a winner group get access to a common channel. The auctioneer formulates a winner determination strategy and a pricing strategy which achieves truthfulness while assigning the idle spectrum. Effectiveness of the proposed model is studied by comparing it with an existing work which shows that channel allocation gets significantly improved on deploying the proposed model.

Secrecy capacity results for a secure NOMA-based cognitive radio network with an external eavesdropper

In this paper, we investigate a secure cognitive radio network (CRN), which deploys non-orthogonal multiple access (NOMA) to deliver a mixed multicast and unicast traffic to the intended receivers, while keeping them secret from the eavesdroppers. This model represents a cognitive interference channel with an external eavesdropper (CIC-EE). In this model, there are one pair of primary nodes, one pair of secondary nodes, and an external eavesdropper. The primary transmitter multicasts a confidential message to both primary and secondary receivers, while trying to keep it secret from the eavesdropper. The secondary transmitter helps the primary user to deliver its message in exchange of transmission opportunity. The secondary message is unicasted to the secondary receiver, while concealing it from both primary receiver and the eavesdropper. This scenario models a NOMA-based overlay cognitive radio paradigm with an external eavesdropper. For this scenario, the achievable rate-equivocation region is obtained and its optimality is shown for a class of degraded channels. Then, the results obtained for the discrete memoryless channel are extended to the Gaussian channel model. Furthermore, by deploying numerical examples, a comparison is made between the proposed secure NOMA-based scheme, its orthogonal multiple access (OMA) based counterpart, and a cognitive interference channel without an external eavesdropper. It is shown that the NOMA-based method achieves significantly higher rates than its OMA based counterpart.

A framework for multimodal wireless sensor networks

During the last decade, the Wireless Sensor Networks have been considered as a broad solution for Internet of Things (IoT) based systems such as noise and air pollution monitoring systems. These systems should be able to monitor the physical variables regularly and simultaneously, to react immediately upon the occurrence of an emergency, and to report the event and its associated data to an observer, in a reliable and energy-efficient way. Recently, the MultiModal Wireless Sensor Networks (M2WSNs) have been proposed as a solution for monitoring oriented applications with low bandwidth requirements that operate simultaneously under normal circumstances and emergencies. In this paper, we present a reliable and energy-efficiency framework for M2WSNs based on the IoT and the Wake-up Radio paradigms. The framework is implemented in ContikiOS, an open-source operating system for IoT solutions, and its performance is evaluated in hardware in an indoor testbed. The experimental results show that the proposed framework provides better reliability in terms of the event reporting latency and packet delivery ratio. Besides, a significant energy-saving is achieved when considering a broadcast-based wake-up scheme with one communication hop for data transmission and acknowledgment procedures in a multi-hop network, compared to a single-radio approach based on a traditional low-duty-cycling and networking techniques.