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

Analysis of Wireless Networks With Massive Connectivity

Recent years have witnessed unprecedented growth in wireless networks in terms of both data traffic and number of connected devices. How to support this fast increasing demand for high data traffic and connectivity is a key consideration in the design of future wireless communication systems. With this motivation, in this thesis, we focus on the analysis of wireless networks with massive connectivity. In the first part of the thesis, we seek to improve the energy efficiency (EE) of single-cell massive multiple-input multiple-output (MIMO) networks with joint antenna selection and user scheduling. We propose a two-step iterative procedure to maximize the EE. In each iteration, bisection search and random selection are used first to determine a subset of antennas with the users selected before, and then identify the EE-optimal subset of users with the selected antennas via cross entropy algorithm. Subsequently, we focus on the joint uplink and downlink EE maximization, under a limitation on the number of available radio frequency (RF) chains. With the Jensen\u27s inequality and the power consumption model, the original problem is converted into a combinatorial optimization problem. Utilizing the learning-based stochastic gradient descent framework and the rare event simulation method, we propose an efficient learning-based stochastic gradient descent algorithm to solve the corresponding combinatorial optimization problem. In the second part of the thesis, we focus on the joint activity detection and channel estimation in cell-free massive MIMO systems with massive connectivity. At first, we conduct an asymptotic analysis of single measurement vector (SMV) based minimum mean square error (MMSE) estimation in cell-free massive MIMO systems with massive connectivity. We establish a decoupling principle of SMV based MMSE estimation for sparse signal vectors with independent and non-identically distributed (i.n.i.d.) non-zero components. Subsequently, using the decoupling principle, likelihood ratio test and the optimal fusion rule, we obtain detection rules for the activity of users based on the received pilot signals at only one access point (AP), and also based on the cooperation of the received pilot signals from the entire set of APs for centralized and distributed detection. Moreover, we study the achievable uplink rates with zero-forcing (ZF) detector at the central processing unit (CPU) of the cell-free massive MIMO systems. In the third part, we focus on the performance analysis of intelligent reflecting surface (IRS) assisted wireless networks. Initially, we investigate the MMSE channel estimation for IRS assisted wireless communication systems. Then, we study the sparse activity detection problem in IRS assisted wireless networks. Specifically, employing the generalized approximate message passing (GAMP) algorithm, we obtain the MMSE estimates of the equivalent effective channel coefficients from the base station (BS) to all users, and transform the received pilot signals into additive Gaussian noise corrupted versions of the equivalent effective channel coefficients. Likelihood ratio test is used to acquire decisions on the activity of each user based on the Gaussian noise corrupted equivalent effective channel coefficients, and the optimal fusion rule is used to obtain the final decisions on the activity of all users based on the previous decisions on the activity of each user and the corresponding reliabilities. Finally, we conduct an asymptotic analysis of maximizing the weighted sum rate by joint beamforming and power allocation under transmit power and quality-of-service (QoS) constraints in IRS assisted wireless networks

On Enabling Concurrent Communications in Wireless Networks

Today innumerable devices use the wireless spectrum for communication, including cell-phones, WiFi devices, military radios, public safety radios, satellite phones etc. This crowding is limiting the experience of each device either through interference or by waiting fortheir turn to communicate. So, how do we allow a limited spectral resource to reliably scale to many more devices? This is possible through concurrent communication where multiple links share the spectrum and communicate simultaneously using multi-antenna techniques. One promising technique is Interference Alignment (IA), that has been shown to be Degrees-of-Freedom optimal under some conditions. Still, IA requires accurate channel knowledge to be effective and its ability to achieve high throughput under time varying wireless conditions is yet unproven. We make progress towards understanding these limitations and provide viable solutions.We study an IA system under different models of the time varying channel and derive expressions for the achieved rate over time and the system throughput. Using these, we can arrive at the optimal duration of the data phase that maximizes throughput. We proposetwo strategies that help to counter the effects of a time varying channel. First, data aided receiver beam-tracking along with link adaptation provides a sizable improvement in the received signal to interference and noise ratio. Second, updating the transmit beams during data transmission using short feedback pilots improves alignment at the receivers. In faster varying channels, we get a more stable achieved rate whereas in slower varying channels, we see additional throughput gains. The conclusion from this work is that an IA system must be trained more frequently than the channel coherence time to ensure high throughput and beam adaptation during the data phase gives significant robustness to the system.Lastly, we present an IA based medium access control (MAC) protocol that outperforms traditional protocols. Our concurrent carrier sense multiple access (CSMA) protocol based on beam-nulling is compatible with CSMA and increases the sum throughput by 2 to 3x.We also show that IA outperforms optimal time division multiple access under time varying conditions. Hence a well-designed IA system can enable reliable concurrent communications in a wireless network

Advanced Trends in Wireless Communications

Physical limitations on wireless communication channels impose huge challenges to reliable communication. Bandwidth limitations, propagation loss, noise and interference make the wireless channel a narrow pipe that does not readily accommodate rapid flow of data. Thus, researches aim to design systems that are suitable to operate in such channels, in order to have high performance quality of service. Also, the mobility of the communication systems requires further investigations to reduce the complexity and the power consumption of the receiver. This book aims to provide highlights of the current research in the field of wireless communications. The subjects discussed are very valuable to communication researchers rather than researchers in the wireless related areas. The book chapters cover a wide range of wireless communication topics

Journal of Telecommunications and Information Technology, 2022, nr 3

kwartalni

Journal of Telecommunications and Information Technology

kwartalni

Channel Access and Reliability Performance in Cognitive Radio Networks:Modeling and Performance Analysis

Doktorgradsavhandling ved Institutt for Informasjons- og kommunikasjonsteknologi, Universitetet i AgderAccording to the facts and figures published by the international telecommunication union (ITU) regarding information and communication technology (ICT) industry, it is estimated that over 3.2 billion people have access to the Internet in 2015 [1]. Since 2000, this number has been octupled. Meanwhile, by the end of 2015, there were more than 7 billion mobile cellular subscriptions in the world, corresponding to a penetration rate of 97%. As the most dynamic segment in ICT, mobile communication is providing Internet services and consequently the mobile broadband penetration rate has reached 47% globally. Accordingly, capacity, throughput, reliability, service quality and resource availability of wireless services become essential factors for future mobile and wireless communications. Essentially, all these wireless technologies, standards, services and allocation policies rely on one common natural resource, i.e., radio spectrum. Radio spectrum spans over the electromagnetic frequencies between 3 kHz and 300 GHz. Existing radio spectrum access techniques are based on the fixed allocation of radio resources. These methods with fixed assigned bandwidth for exclusive usage of licensed users are often not efficient since most of the spectrum bands are under-utilized, either/both in the space domain or/and in the time domain. In reality, it is observed that many spectrum bands are largely un-occupied in many places [2], [3]. For instance, the spectrum bands which are exclusively allocated for TV broadcasting services in USA remain un-occupied from midnight to early morning according to the real-life measurement performed in [4]. In addition to the wastage of radio resources, spectrum under-utilization constraints spectrum availability for other intended users. Furthermore, legacy fixed spectrum allocation techniques are not capable of adapting to the changes and interactions in the system, leading to degraded network performance. Unlike in the static spectrum allocation, a fraction of the radio spectrum is allocated for open access as license-free bands, e.g., the industrial, scientific and medical (ISM) bands (902-928, 2400-2483.5, 5725-5850 MHz). In 1985, the federal communications commission (FCC) permitted to use the ISM bands for private and unlicensed occupancy, however, under certain restrictions on transmission power [5]. Consequently, standards like IEEE 802.11 for wireless local area networks (WLANs) and IEEE 802.15 for wireless personal area networks (WPAN) have grown rapidly with open access spectrum policies in the 2.4 GHz and 5 GHz ISM bands. With the co-existence of both similar and dissimilar radio technologies, 802.11 networks face challenges for providing satisfactory quality of service (QoS). This and the above mentioned spectrum under-utilization issues motivate the spectrum regulatory bodies to rethink about more flexible spectrum access for licenseexempt users or more efficient radio spectrum management. Cognitive radio (CR) is probably the most promising technology for achieving efficient spectrum utilization in future wireless networks

Antennas and Propagation Aspects for Emerging Wireless Communication Technologies

The increasing demand for high data rate applications and the delivery of zero-latency multimedia content drives technological evolutions towards the design and implementation of next-generation broadband wireless networks. In this context, various novel technologies have been introduced, such as millimeter wave (mmWave) transmission, massive multiple input multiple output (MIMO) systems, and non-orthogonal multiple access (NOMA) schemes in order to support the vision of fifth generation (5G) wireless cellular networks. The introduction of these technologies, however, is inextricably connected with a holistic redesign of the current transceiver structures, as well as the network architecture reconfiguration. To this end, ultra-dense network deployment along with distributed massive MIMO technologies and intermediate relay nodes have been proposed, among others, in order to ensure an improved quality of services to all mobile users. In the same framework, the design and evaluation of novel antenna configurations able to support wideband applications is of utmost importance for 5G context support. Furthermore, in order to design reliable 5G systems, the channel characterization in these frequencies and in the complex propagation environments cannot be ignored because it plays a significant role. In this Special Issue, fourteen papers are published, covering various aspects of novel antenna designs for broadband applications, propagation models at mmWave bands, the deployment of NOMA techniques, radio network planning for 5G networks, and multi-beam antenna technologies for 5G wireless communications