Intelligent Massive MIMO Systems for Beyond 5G Networks: An Overview and Future Trends

Machine learning (ML) which is a subset of artificial intelligence is expected to unlock the potential of challenging large-scale problems in conventional massive multiple-input-multiple-output (CM-MIMO) systems. This introduces the concept of intelligent massive MIMO (I-mMIMO) systems. Due to the surge of application of different ML techniques in the enhancement of mMIMO systems for existing and emerging use cases beyond fifth-generation (B5G) networks, this article aims to provide an overview of the different aspects of the I-mMIMO systems. First, the characteristics and challenges of the CM-MIMO have been identified. Secondly, the most recent efforts aimed at applying ML to a different aspect of CM-MIMO systems are presented. Thirdly, the deployment of I-mMIMO and efforts towards standardization are discussed. Lastly, the future trends of I-mMIMO-enabled application systems are presented. The aim of this paper is to assist the readers to understand different ML approaches in CM-MIMO systems, explore some of the advantages and disadvantages, identify some of the open issues, and motivate the readers toward future trends

Analysis and Design of Non-Orthogonal Multiple Access (NOMA) Techniques for Next Generation Wireless Communication Systems

The current surge in wireless connectivity, anticipated to amplify significantly in future wireless technologies, brings a new wave of users. Given the impracticality of an endlessly expanding bandwidth, there’s a pressing need for communication techniques that efficiently serve this burgeoning user base with limited resources. Multiple Access (MA) techniques, notably Orthogonal Multiple Access (OMA), have long addressed bandwidth constraints. However, with escalating user numbers, OMA’s orthogonality becomes limiting for emerging wireless technologies. Non-Orthogonal Multiple Access (NOMA), employing superposition coding, serves more users within the same bandwidth as OMA by allocating different power levels to users whose signals can then be detected using the gap between them, thus offering superior spectral efficiency and massive connectivity. This thesis examines the integration of NOMA techniques with cooperative relaying, EXtrinsic Information Transfer (EXIT) chart analysis, and deep learning for enhancing 6G and beyond communication systems. The adopted methodology aims to optimize the systems’ performance, spanning from bit-error rate (BER) versus signal to noise ratio (SNR) to overall system efficiency and data rates. The primary focus of this thesis is the investigation of the integration of NOMA with cooperative relaying, EXIT chart analysis, and deep learning techniques. In the cooperative relaying context, NOMA notably improved diversity gains, thereby proving the superiority of combining NOMA with cooperative relaying over just NOMA. With EXIT chart analysis, NOMA achieved low BER at mid-range SNR as well as achieved optimal user fairness in the power allocation stage. Additionally, employing a trained neural network enhanced signal detection for NOMA in the deep learning scenario, thereby producing a simpler signal detection for NOMA which addresses NOMAs’ complex receiver problem

6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities

Mobile communications have been undergoing a generational change every ten years or so. However, the time difference between the so-called "G's" is also decreasing. While fifth-generation (5G) systems are becoming a commercial reality, there is already significant interest in systems beyond 5G, which we refer to as the sixth-generation (6G) of wireless systems. In contrast to the already published papers on the topic, we take a top-down approach to 6G. We present a holistic discussion of 6G systems beginning with lifestyle and societal changes driving the need for next generation networks. This is followed by a discussion into the technical requirements needed to enable 6G applications, based on which we dissect key challenges, as well as possibilities for practically realizable system solutions across all layers of the Open Systems Interconnection stack. Since many of the 6G applications will need access to an order-of-magnitude more spectrum, utilization of frequencies between 100 GHz and 1 THz becomes of paramount importance. As such, the 6G eco-system will feature a diverse range of frequency bands, ranging from below 6 GHz up to 1 THz. We comprehensively characterize the limitations that must be overcome to realize working systems in these bands; and provide a unique perspective on the physical, as well as higher layer challenges relating to the design of next generation core networks, new modulation and coding methods, novel multiple access techniques, antenna arrays, wave propagation, radio-frequency transceiver design, as well as real-time signal processing. We rigorously discuss the fundamental changes required in the core networks of the future that serves as a major source of latency for time-sensitive applications. While evaluating the strengths and weaknesses of key 6G technologies, we differentiate what may be achievable over the next decade, relative to what is possible.Comment: Accepted for Publication into the Proceedings of the IEEE; 32 pages, 10 figures, 5 table

IRS-aided UAV for Future Wireless Communications: A Survey and Research Opportunities

Both unmanned aerial vehicles (UAVs) and intelligent reflecting surfaces (IRS) are gaining traction as transformative technologies for upcoming wireless networks. The IRS-aided UAV communication, which introduces IRSs into UAV communications, has emerged in an effort to improve the system performance while also overcoming UAV communication constraints and issues. The purpose of this paper is to provide a comprehensive overview of IRSassisted UAV communications. First, we provide five examples of how IRSs and UAVs can be combined to achieve unrivaled potential in difficult situations. The technological features of the most recent relevant researches on IRS-aided UAV communications from the perspective of the main performance criteria, i.e., energy efficiency, security, spectral efficiency, etc. Additionally, previous research studies on technology adoption as machine learning algorithms. Lastly, some promising research directions and open challenges for IRS-aided UAV communication are presented

Cell-Free Massive MIMO: Challenges and Promising Solutions

Along with its primary mission in fulfilling the communication needs of humans as well as intelligent machines, fifth generation (5G) and beyond networks will be a virtual fundamental component for all parts of life, society, and industries. These networks will pave the way towards realizing the individuals’ technological aspirations including holographic telepresence, e-Health, pervasive connectivity in smart environments, massive robotics, three-dimensional unmanned mobility, augmented reality, virtual reality, and internet of everything. This new era of applications brings unprecedented challenging demands to wireless network, such as high spectral efficiency, low-latency, high-reliable communication, and high energy efficiency. One of the major technological breakthroughs that has recently drawn the attention of researchers from academia and industry to cope with these unprecedented demands of wireless networks is the cell-free (CF) massive multiple-input multiple-output (mMIMO) systems. In CF mMIMO, a large number of spatially distributed access points are connected to a central processing unit (CPU). The CPU operates all APs as a single mMIMO network with no cell boundaries to serve a smaller number of users coherently on the same time-frequency resources. The system has shown substantial gains in improving the network performance from different perspectives, especially for cell-edge users, compared it other candidate technologies for 5G networks, \ie co-located mMIMO and small-cell (SC) systems. Nevertheless, the full picture of a practical scalable deployment of the system is not clear yet. In this thesis, we provide more in-depth investigations on the CF mMIMO performance under various practical system considerations. Also, we provide promising solutions to fully realize the potential of CF mMIMO in practical scenarios. In this regard, we focus on three vital practical challenges, namely hardware and channel impairments, malicious attacks, and limited-capacity fronthaul network. Regarding the hardware and channel impairments, we analyze the CF mMIMO performance under such practical considerations and compare its performance with SC systems. In doing so, we consider that both APs and user equipment (UE)s are equipped with non-ideal hardware components. Also, we consider the Doppler shift effect as a source of channel impairments in dynamic environments with moving users. Then, we derive novel closed-form expressions for the downlink (DL) spectral efficiency of both systems under hardware distortions and Doppler shift effect. We reveal that the effect of non-ideal UEs is more prominent than the non-ideal APs. Also, while increasing the number of deployed non-ideal APs can limit the hardware distortion effect in CF mMIMO systems, this leads to an extra performance loss in SC systems. Besides, we show that the Doppler shift effect is more harsh in SC systems. In addition, the SC system operation is more suitable for low-velocity users, however, it is more beneficial to adopt CF mMIMO system for network operation under high-mobility conditions. Capitalizing on the latter, we propose a hybrid CF mMIMO/SC system that can significantly outperforms both CF mMIMO and SC systems by providing different mobility conditions with high data rates simultaneously. Towards a further improvement in the CF mMIMO performance under high mobility scenarios, we propose a novel framework to limit the performance degradation due to the Doppler shift effect. To this end, we derive novel expressions for tight lower bound of the average DL and uplink (UL) data rates. Capitalizing on the derived analytical results, we provide an analytical framework that optimizes the frame length to minimize the Doppler shift effect on DL and UL data rates according to some criterion. Our results reveal that the optimal frame lengths for maximizing the DL and UL data rates are different and depend mainly on the users' velocities. Besides, adapting the frame length according to the velocity conditions significantly limits the Doppler shift effect, compared to applying a fixed frame length. To empower the CF mMIMO systems with secure transmission against malicious attacks, we propose two different approaches that significantly increases the achievable secrecy rates. In the first approach, we introduce a novel secure DL transmission technique that efficiently limits the eavesdropper (Eve) capability in decoding the transmitted signals to legitimate users. Differently, in the second approach, we adopt the distinctive features of Reconfigurable intelligent surfaces (RIS)s to limit the information leakage towards the Eve. Regarding the impact of limited capacity of wired-based fronthaul links, we drive the achievable DL data rates assuming two different CF mMIMO system operations, namely, distributed and centralized system operations. APs and CPU are the responsible entities for carrying out the signal processing functionalities in the distributed and centralized system operations, respectively. We show that the impact of limited capacity fronthaul links is more prominent on the centralized system operation. In addition, while the distributed system operation is more preferable under low capacities of fronthaul links, the centralized counterpart attains superior performance at high capacities of fronthaul links. Furthermore, considering the distributed and centralized system operations, and towards a practical and scalable operation of CF mMIMO systems, we propose a wireless-based fronthaul network for CF mMIMO systems under three different operations, namely, microwave-based, mmWave-based, and hybrid mmWave/microwave. Our results show that the integration between the centralized operation and the hybrid-based fronthaul network provides the highest DL data rates when APs are empowered with signal decoding capabilities. However, integrating the distributed operation with the microwave-based fronthaul network achieves ultimate performance when APs are not supported with decoding capabilities

Malicious RIS versus Massive MIMO: Securing Multiple Access against RIS-based Jamming Attacks

In this letter, we study an attack that leverages a reconfigurable intelligent surface (RIS) to induce harmful interference toward multiple users in massive multiple-input multiple-output (mMIMO) systems during the data transmission phase. We propose an efficient and flexible weighted-sum projected gradient-based algorithm for the attacker to optimize the RIS reflection coefficients without knowing legitimate user channels. To counter such a threat, we propose two reception strategies. Simulation results demonstrate that our malicious algorithm outperforms baseline strategies while offering adaptability for targeting specific users. At the same time, our results show that our mitigation strategies are effective even if only an imperfect estimate of the cascade RIS channel is available

LGTBIDS: Layer-wise Graph Theory Based Intrusion Detection System in Beyond 5G

The advancement in wireless communication technologies is becoming more demanding and pervasive. One of the fundamental parameters that limit the efficiency of the network are the security challenges. The communication network is vulnerable to security attacks such as spoofing attacks and signal strength attacks. Intrusion detection signifies a central approach to ensuring the security of the communication network. In this paper, an Intrusion Detection System based on the framework of graph theory is proposed. A Layerwise Graph Theory-Based Intrusion Detection System (LGTBIDS) algorithm is designed to detect the attacked node. The algorithm performs the layer-wise analysis to extract the vulnerable nodes and ultimately the attacked node(s). For each layer, every node is scanned for the possibility of susceptible node(s). The strategy of the IDS is based on the analysis of energy efficiency and secrecy rate. The nodes with the energy efficiency and secrecy rate beyond the range of upper and lower thresholds are detected as the nodes under attack. Further, detected node(s) are transmitted with a random sequence of bits followed by the process of re-authentication. The obtained results validate the better performance, low time computations, and low complexity. Finally, the proposed approach is compared with the conventional solution of intrusion detection.Comment: in IEEE Transactions on Network and Service Management, 202

6G wireless communications networks: a comprehensive survey

The commercial fifth-generation (5G) wireless communications networks have already been deployed with the aim of providing high data rates. However, the rapid growth in the number of smart devices and the emergence of the Internet of Everything (IoE) applications, which require an ultra-reliable and low-latency communication, will result in a substantial burden on the 5G wireless networks. As such, the data rate that could be supplied by 5G networks will unlikely sustain the enormous ongoing data traffic explosion. This has motivated research into continuing to advance the existing wireless networks toward the future generation of cellular systems, known as sixth generation (6G). Therefore, it is essential to provide a prospective vision of the 6G and the key enabling technologies for realizing future networks. To this end, this paper presents a comprehensive review/survey of the future evolution of 6G networks. Specifically, the objective of the paper is to provide a comprehensive review/survey about the key enabling technologies for 6G networks, which include a discussion about the main operation principles of each technology, envisioned potential applications, current state-of-the-art research, and the related technical challenges. Overall, this paper provides useful information for industries and academic researchers and discusses the potentials for opening up new research directions