Full-Duplex Wireless for 6G: Progress Brings New Opportunities and Challenges

The use of in-band full-duplex (FD) enables nodes to simultaneously transmit and receive on the same frequency band, which challenges the traditional assumption in wireless network design. The full-duplex capability enhances spectral efficiency and decreases latency, which are two key drivers pushing the performance expectations of next-generation mobile networks. In less than ten years, in-band FD has advanced from being demonstrated in research labs to being implemented in standards and products, presenting new opportunities to utilize its foundational concepts. Some of the most significant opportunities include using FD to enable wireless networks to sense the physical environment, integrate sensing and communication applications, develop integrated access and backhaul solutions, and work with smart signal propagation environments powered by reconfigurable intelligent surfaces. However, these new opportunities also come with new challenges for large-scale commercial deployment of FD technology, such as managing self-interference, combating cross-link interference in multi-cell networks, and coexistence of dynamic time division duplex, subband FD and FD networks.Comment: 21 pages, 15 figures, accepted to an IEEE Journa

Ultra-Wideband Secure Communications and Direct RF Sampling Transceivers

Larger wireless device bandwidth results in new capabilities in terms of higher data rates and security. The 5G evolution is focus on exploiting larger bandwidths for higher though-puts. Interference and co-existence issues can also be addressed by the larger bandwidth in the 5G and 6G evolution. This dissertation introduces of a novel Ultra-wideband (UWB) Code Division Multiple Access (CDMA) technique to exploit the largest bandwidth available in the upcoming wireless connectivity scenarios. The dissertation addresses interference immunity, secure communication at the physical layer and longer distance communication due to increased receiver sensitivity. The dissertation presents the design, workflow, simulations, hardware prototypes and experimental measurements to demonstrate the benefits of wideband Code-Division-Multiple-Access. Specifically, a description of each of the hardware and software stages is presented along with simulations of different scenarios using a test-bench and open-field measurements. The measurements provided experimental validation carried out to demonstrate the interference mitigation capabilities. In addition, Direct RF sampling techniques are employed to handle the larger bandwidth and avoid analog components. Additionally, a transmit and receive chain is designed and implemented at 28 GHz to provide a proof-of-concept for future 5G applications. The proposed wideband transceiver is also used to demonstrate higher accuracy direction finding, as much as 10 times improvement

Cooperative spectrum sensing using adaptive quantization mapping for mobile cognitive radio networks

Sparsity in spectrum is the result of spectrum underutilization. Cognitive radio (CR) technology has been proposed to address inefficiency of spectrum utilisation through dynamic spectrum access technique. CR in general allows secondary node (SN) users to access the licensed or primary users’ (PU) band without disrupting their activities. In CR cooperative spectrum sensing (CSS), a group of SNs share their spectrum sensing information to provide a better picture of the spectrum usage over the area where the SNs are located. In centralised CCS approach, all the SNs report their sensing information to a master node (MN) through a control reporting channel before the MN decides the spectrum bands that can be used by the SNs. To reduce unnecessary reporting information by the cooperating nodes, orthogonal frequency division multiplexing (OFDM) Subcarrier Mapping (SCM) spectrum exchange information was proposed. In this technique, the detection power level from each secondary SN user is quantized and mapped into a single OFDM subcarrier number before delivering it to the MN. Most researches in cooperative spectrum sensing often stated that the SNs are absolutely in stationary condition. So far, the mobility effect on OFDM based SCM spectrum exchange information has not been addressed before. In this thesis, the benchmarking of SCM in mobility environment is carried out. The results showed that during mobility, the performance of OFDM-based SCM spectrum exchange information degraded significantly. To alleviate the degradation, OFDM-based spectrum exchange information using adaptive quantization is proposed, which is known as Dynamic Subcarrier Mapping (DSM). The method is proposed to adapt to changes in detected power level during mobility. This new nonuniform subcarrier mapping considers the range of received power, threshold level and dynamic subcarrier width. The range of received power is first compressed or expanded depending on the intensity of the received power against a pre-determined threshold level before the OFDM subcarrier number is computed. The results showed that OFDM-based DSM spectrum exchange information is able to enhance the probability of detection for cooperative sensing by up to 43% and reduce false alarm by up to 28%. The DSM spectrum exchange information method has the potential to improve cooperative spectrum sensing for future CR mobile wireless networks

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe

CELLULAR-ENABLED MACHINE TYPE COMMUNICATIONS: RECENT TECHNOLOGIES AND COGNITIVE RADIO APPROACHES

The scarcity of bandwidth has always been the main obstacle for providing reliable high data-rate wireless links, which are in great demand to accommodate nowadays and immediate future wireless applications. In addition, recent reports have showed inefficient usage and under-utilization of the available bandwidth. Cognitive radio (CR) has recently emerged as a promising solution to enhance the spectrum utilization, where it offers the ability for unlicensed users to access the licensed spectrum opportunistically. By allowing opportunistic spectrum access which is the main concept for the interweave network model, the overall spectrum utilization can be improved. This requires cognitive radio networks (CRNs) to consider the spectrum sensing and monitoring as an essential enabling process for the interweave network model. Machine-to-machine (M2M) communication, which is the basic enabler for the Internet-of-Things (IoT), has emerged to be a key element in future networks. Machines are expected to communicate with each other exchanging information and data without human intervention. The ultimate objective of M2M communications is to construct comprehensive connections among all machines distributed over an extensive coverage area. Due to the radical change in the number of users, the network has to carefully utilize the available resources in order to maintain reasonable quality-of-service (QoS). Generally, one of the most important resources in wireless communications is the frequency spectrum. To utilize the frequency spectrum in IoT environment, it can be argued that cognitive radio concept is a possible solution from the cost and performance perspectives. Thus, supporting numerous number of machines is possible by employing dual-mode base stations which can apply cognitive radio concept in addition to the legacy licensed frequency assignment. In this thesis, a detailed review of the state of the art related to the application of spectrum sensing in CR communications is considered. We present the latest advances related to the implementation of the legacy spectrum sensing approaches. We also address the implementation challenges for cognitive radios in the direction of spectrum sensing and monitoring. We propose a novel algorithm to solve the reduced throughput issue due to the scheduled spectrum sensing and monitoring. Further, two new architectures are considered to significantly reduce the power consumption required by the CR to enable wideband sensing. Both systems rely on the 1-bit quantization at the receiver side. The system performance is analytically investigated and simulated. Also, complexity and power consumption are investigated and studied. Furthermore, we address the challenges that are expected from the next generation M2M network as an integral part of the future IoT. This mainly includes the design of low-power low-cost machine with reduced bandwidth. The trade-off between cost, feasibility, and performance are also discussed. Because of the relaxation of the frequency and spatial diversities, in addition, to enabling the extended coverage mode, initial synchronization and cell search have new challenges for cellular-enabled M2M systems. We study conventional solutions with their pros and cons including timing acquisition, cell detection, and frequency offset estimation algorithms. We provide a technique to enhance the performance in the presence of the harsh detection environment for LTE-based machines. Furthermore, we present a frequency tracking algorithm for cellular M2M systems that utilizes the new repetitive feature of the broadcast channel symbols in next generation Long Term Evolution (LTE) systems. In the direction of narrowband IoT support, we propose a cell search and initial synchronization algorithm that utilizes the new set of narrowband synchronization signals. The proposed algorithms have been simulated at very low signal to noise ratios and in different fading environments

Contribution à la conception d'un système de radio impulsionnelle ultra large bande intelligent

Faced with an ever increasing demand of high data-rates and improved adaptability among existing systems, which inturn is resulting in spectrum scarcity, the development of new radio solutions becomes mandatory in order to answer the requirements of these emergent applications. Among the recent innovations in the field of wireless communications,ultra wideband (UWB) has generated significant interest. Impulse based UWB (IR-UWB) is one attractive way of realizing UWB systems, which is characterized by the transmission of sub nanoseconds UWB pulses, occupying a band width up to 7.5 GHz with extremely low power density. This large band width results in several captivating features such as low-complexity low-cost transceiver, ability to overlay existing narrowband systems, ample multipath diversity, and precise ranging at centimeter level due to extremely fine temporal resolution.In this PhD dissertation, we investigate some of the key elements in the realization of an intelligent time-hopping based IR-UWB system. Due to striking resemblance of IR-UWB inherent features with cognitive radio (CR) requirements, acognitive UWB based system is first studied. A CR in its simplest form can be described as a radio, which is aware ofits surroundings and adapts intelligently. As sensing the environment for the availability of resources and then consequently adapting radio’s internal parameters to exploit them opportunistically constitute the major blocks of any CR, we first focus on robust spectrum sensing algorithms and the design of adaptive UWB waveforms for realizing a cognitive UWB radio. The spectrum sensing module needs to function with minimum a-priori knowledge available about the operating characteristics and detect the primary users as quickly as possible. Keeping this in mind, we develop several spectrum sensing algorithms invoking recent results on the random matrix theory, which can provide efficient performance with a few number of samples. Next, we design the UWB waveform using a linear combination of Bsp lines with weight coefficients being optimized by genetic algorithms. This results in a UWB waveform that is spectrally efficient and at the same time adaptable to incorporate the cognitive radio requirements. In the 2nd part of this thesis, some research challenges related to signal processing in UWB systems, namely synchronization and dense multipath channel estimation are addressed. Several low-complexity non-data-aided (NDA) synchronization algorithms are proposed for BPSK and PSM modulations, exploiting either the orthogonality of UWB waveforms or theinherent cyclostationarity of IR-UWB signaling. Finally, we look into the channel estimation problem in UWB, whichis very demanding due to particular nature of UWB channels and at the same time very critical for the coherent Rake receivers. A method based on a joint maximum-likelihood (ML) and orthogonal subspace (OS) approaches is proposed which exhibits improved performance than both of these methods individually.Face à une demande sans cesse croissante de haut débit et d’adaptabilité des systèmes existants, qui à son tour se traduit par l’encombrement du spectre, le développement de nouvelles solutions dans le domaine des communications sans fil devient nécessaire afin de répondre aux exigences des applications émergentes. Parmi les innovations récentes dans ce domaine, l’ultra large bande (UWB) a suscité un vif intérêt. La radio impulsionnelle UWB (IR-UWB), qui est une solution intéressante pour réaliser des systèmes UWB, est caractérisée par la transmission des impulsions de très courte durée, occupant une largeur de bande allant jusqu’à 7,5 GHz, avec une densité spectrale de puissance extrêmement faible. Cette largeur de bande importante permet de réaliser plusieurs fonctionnalités intéressantes, telles que l’implémentation à faible complexité et à coût réduit, la possibilité de se superposer aux systèmes à bande étroite, la diversité spatiale et la localisation très précise de l’ordre centimétrique, en raison de la résolution temporelle très fine.Dans cette thèse, nous examinons certains éléments clés dans la réalisation d'un système IR-UWB intelligent. Nous avons tout d’abord proposé le concept de radio UWB cognitive à partir des similarités existantes entre l'IR-UWB et la radio cognitive. Dans sa définition la plus simple, un tel système est conscient de son environnement et s'y adapte intelligemment. Ainsi, nous avons tout d’abord focalisé notre recherché sur l’analyse de la disponibilité des ressources spectrales (spectrum sensing) et la conception d’une forme d’onde UWB adaptative, considérées comme deux étapes importantes dans la réalisation d'une radio cognitive UWB. Les algorithmes de spectrum sensing devraient fonctionner avec un minimum de connaissances a priori et détecter rapidement les utilisateurs primaires. Nous avons donc développé de tels algorithmes utilisant des résultats récents sur la théorie des matrices aléatoires, qui sont capables de fournir de bonnes performances, avec un petit nombre d'échantillons. Ensuite, nous avons proposé une méthode de conception de la forme d'onde UWB, vue comme une superposition de fonctions B-splines, dont les coefficients de pondération sont optimisés par des algorithmes génétiques. Il en résulte une forme d'onde UWB qui est spectralement efficace et peut s’adapter pour intégrer les contraintes liées à la radio cognitive. Dans la 2ème partie de cette thèse, nous nous sommes attaqués à deux autres problématiques importantes pour le fonctionnement des systèmes UWB, à savoir la synchronisation et l’estimation du canal UWB, qui est très dense en trajets multiples. Ainsi, nous avons proposé plusieurs algorithmes de synchronisation, de faible complexité et sans séquence d’apprentissage, pour les modulations BPSK et PSM, en exploitant l'orthogonalité des formes d'onde UWB ou la cyclostationnarité inhérente à la signalisation IR-UWB. Enfin, nous avons travaillé sur l'estimation du canal UWB, qui est un élément critique pour les récepteurs Rake cohérents. Ainsi, nous avons proposé une méthode d’estimation du canal basée sur une combinaison de deux approches complémentaires, le maximum de vraisemblance et la décomposition en sous-espaces orthogonaux,d’améliorer globalement les performances

Nonorthogonal Multiple Access for 5G and Beyond

This work was supported in part by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/N029720/1 and Grant EP/N029720/2. The work of L. Hanzo was supported by the ERC Advanced Fellow Grant Beam-me-up