Artificial Intelligence for 5G Wireless Systems: Opportunities, Challenges, and Future Research Direction

Summary form only given. Emerging demands for high data rate multimedia based services and high spectral efficiency are the key drives for the continued technology evolution in wireless communications. Recently, several advancements have been introduced for 3G wireless communication systems to further enhance the data rate and the system performance. However, due to the proliferation of wireless multimedia applications and services such as video teleconferencing, network gaming, and high-quality audio/video streaming, it is apparent that 3G wireless systems will be unable to comply with this ever increasing demand for broadband wireless services. The next generation wireless communication systems (namely, fourth generation (4G) or beyond 3G (B3G) systems) are expected to support much higher data rate services compared to evolving 3G systems (up to 100 Mbit/s in outdoor environments and up to 1 Gbit/s in indoor environments). The major technical challenges will be achieving high spectral efficiency and handling high frequency-selectivity due to the use of large bandwidth. Hence, it has become crucial to incorporate the recent technical advances in the physical layer into the future wireless systems. In this keynote speech, an overview of leading technological advances and future trends in the physical layer that enable truly ubiquitous broadband wireless capabilities will be presented. The topics include multiple-input multiple-output (MIMO) technologies, adaptive modulation, cooperative diversity, multicarrier CDMA, ultra wideband (UWB) transmission, and cognitive radio.

The Long Term Evolution (LTE) standards are generated by the Third Generation Partnership Project (3GPP) for the Fourth Generation (4G) wireless communication systems. The Fourth Generation (4G) wireless communication standards use new physical layer signaling techniques in their physical layer. Single Carrier Frequency Division Multiple Access (SC-FDMA) and Orthogonal Frequency Division Multiple Access (OFDMA) are the two major signaling techniques used in LTE. OFDMA is used in the downlink of the Fourth Generation (4G) wireless communication systems for its high spectral efficiency and SC-FDMA is used in the uplink of the Fourth Generation (4G) wireless communication systems for its high power efficiency. The main objective of this paper is to design and implement the reliable and energy efficient architecture for LTE uplink system using FPGA. IFDMA is the most energy efficient subcarrier mapping scheme of SC-FDMA multiple access scheme. In IFDMA, the data symbols subcarrier mapping is not one to one instead each subcarrier carries a part from each data symbol transmitted at that time instant. The reason for the selection of IFDMA subcarrier mapping along with SC-FDMA multiple access scheme for LTE uplink comes mainly from its advantage to provide a low peak to average power ratio (PAPR) for the transmitted waveform. This results in less power consumption in the mobile station during uplink transmission. The reliability of the system is improved using interleaving process by avoiding packet loss. Convolution codes are less complex and are used to provide error free transmission. The enhancement of energy efficiency is done using the convolution coded IFDMA. The chosen energy efficient architecture must be more power efficient and support high data rates, which is the main requirement for the mobile user. The proposed reliable and energy efficient architecture for LTE uplink system is implemented using Xilinx system generator tool.

SummaryThis paper introduces the concept of spatial and media‐based modulated (SMBM) orthogonal frequency division multiplexing (OFDM) as a potential candidate for highly mobile next generation beyond 5G (B5G) wireless communications. The proposed SMBM‐OFDM technique utilizes not only the transmit antenna and channel state indices but also OFDM subcarriers to improve the system performance under high mobility. In addition, this study sheds light on challenging fast time‐varying channel estimation problem of MBM‐based systems by using the linear minimum mean square error (LMMSE) approach due to its optimality to investigate the achievable system performance with the aid of basis expansion modeling. The minimum lower bound on the channel estimation error (Bayesian Cramer–Rao bound) is derived theoretically and shown to be attainable by the considered LMMSE estimator. Moreover, symbol detection performance is provided for different modulation types and higher mobile velocities. Simulation results demonstrate that SMBM‐OFDM system under high mobility is able to provide around 12‐dB performance gains in terms of both channel estimation and symbol detection error compared to conventional spatial modulation (SM)‐OFDM systems without MBM. The presented framework is important due to addressing the high mobility support of SMBM‐OFDM systems for B5G wireless communications in terms of achievable channel estimation and data detection performance.

The ever-growing number of interconnected devices and the emergence of high-bandwidth technologies such as holographic communications in mixed reality are driving an exponential growth in the demand for terabits-per-second (Tbps) data rates with sub-milliseconds latency. For this reason, the sixth-generation (6G) wireless communications are moving towards the terahertz (THz) frequency band because of its wider spectral bandwidth availability to enable higher channel capacity and data rates according to the Shannon-Hartley theorem. However, the efficiency of wireless THz signal transmission is reduced by the increased path loss and atmospheric attenuation due to water vapor absorption at THz frequencies, which significantly decreases the signal-to-noise ratio and the spectral efficiency of THz wireless communications. The realization of THz band communications is further impeded by the limited power output of existing compact THz sources due to the extremely low conversion efficiencies. Therefore, it is crucial to develop broadband THz integrated circuits with waveguiding and beamforming functionalities for supporting high data-rate on-chip communications and to provide sufficient gains to counteract the path loss and limited power of THz wireless transmissions. This thesis aims to improve the spectral efficiency of 6G wireless communications via the spatiotemporal shaping of THz waves using silicon photonics. Spatiotemporal light shaping is the basis of nearly all THz photonic devices, ranging from THz wavefront manipulation using metasurfaces to THz planar waveguiding using photonic crystal waveguides. Silicon photonics is a promising material platform for THz wave shaping due to the low-loss propagation of THz waves in high-resistivity silicon and the prospect of a monolithic integrated circuit due to the complementary metal-oxide semiconductor (CMOS) fabrication process compatibility. Silicon metasurfaces allow the wavefront modulation of incident THz radiation by exploiting the generalized Snell’s law of refraction and reflection to beamform highly directional THz waves in a dynamic multi-user communication environment for enhancing the spectral efficiency. Likewise, broadband silicon photonic crystal waveguides allow the in-plane and lossless transport of THz waves to support on-chip high data-rate THz communications that can also seamlessly integrate multiple THz photonic devices in a THz integrated circuit. In addition, silicon electron emitters and silicon gratings potentially allow the on-chip generation of highly intense and broadband THz radiation to counteract the significant THz attenuation. In this thesis, spatiotemporal wave shaping techniques using silicon photonics for enhancing the spectral efficiency of THz band communications is presented. First, a self-adaptive and deep reinforcement learning model for THz beamforming is proposed, which can beamform multiple highly directional THz radiation beam in real-time to serve a dynamically changing multi-user communication environment and improve the signal-to-noise ratio of THz wireless transmission while potentially reducing the communication latency. Second, a broadband THz topological silicon waveguide designed based on valley photonic crystals is proposed for the robust and lossless transport of broadband THz waves for the construction of THz integrated circuits with broadband channel capacity for enabling higher data-rate on-chip communication. Last, the versatility of free-electron radiation from silicon gratings is investigated for the generation of highly intense spatiotemporal wave packets with user-designed group velocities and tunable intensity profile, with the potential to realize integrated high-power THz sources. The deep learning beamforming model, the broadband topological waveguide designs, and the free-electron radiation intensity shaping techniques presented in this thesis extends beyond the THz regime and are scalable across the entire electromagnetic spectrum. The CMOS process compatibility of silicon metasurfaces, silicon planar waveguides, along with silicon electron emitters and silicon gratings offers the opportunity to realize a broadband THz photonic integrated circuit with waveguiding, wave generation and beamforming functionalities for enhancing the spectral efficiency of THz communications in 6G wireless networks.

The main objective of the roundtable is to bring together computer scientists and wireless communications experts from industry, academia, and government to explore the electromagnetic spectrum in the Terahertz (THz) bands for ultra-high-speed short-distance wireless communications in extreme environments. This new generation of THz wireless communications is the key to future machine-to-machine communications critical for the mass deployment of an intelligent Internet of Things (IoT). The roundtable discussion explores THz and 6G wireless technologies along with Visible Light Communications (VLC), intelligent reflection surfaces, free-space quantum and optical communications, and nano communications. The roundtable considers the suitability of these technologies for extreme environments from the nanoscale to the mesoscale for the following: scientific facilities and associated instruments, as well as industry, and manufacturing. Such use cases are not traditionally the primary customer of commercial wireless networks which are focused on personal broadband voice and data communications. Finally, the discussion identifies high-level opportunities and challenges for leveraging THz and 6G wireless communications and related Artificial Intelligence (AI) that can catalyze the advancement of the development of hyperconnected smart scientific instruments and facilities

The high-paced development of wireless communication technologies brought about the growing need of smart, autonomous, and ultra-high-performance network structures, and the combination of Artificial Intelligence and Machine Learning in the 6G wireless communication networks is a major research issue. The conventional network management techniques cannot support the new demands that include ultra-low latency communications, intelligent spectrum management, mass connectivity, and real-time dynamic resource provision. This paper is a systematically-conducted literature review on the recent research on AI-driven networks, edge AI, federated learning, intelligent radio access network design, and AI-native architecture in next-generation networks based on PRISMA. The review focuses on the possibilities of self-organizing networks, digital twin networks, and smart connectivity that machine learning, deep learning, and autonomous wireless systems provide to the next generation of wireless networks working in terahertz communication ranges and integrated sensing and communication landscape. The findings indicate that AI based resource allocation, intelligent surfaces of reconfigurability, massive mimo optimization and network automation are all effective towards improving spectral efficiency, reliability and energy efficiency of 6G wireless communication. Moreover, the paper has also noted the increased importance of smart security mechanisms, distributed learning, and edge computing in enabling scalable and secure AI-native architectures. The results also indicate that the next generation wireless networks will be based upon intelligent spectrum management, autonomous control, and real-time data analytics to accommodate the new applications in holographic communication, smart cities, extended reality, and connected autonomous systems.

In recent years, wireless use has exploded. 5G is being implemented globally. The development and implementation of 6G have started, with a target date of the 2030s. Current 3G to 5G technologies have opened the path for high data speeds, low latency, and great dependability in wireless communications. There will be continuous change in the key performance indicators (KPIs) to change, recent trends show that wireless communication system architecture concepts need to go beyond the standard. This paper describes 6G wireless communications and networks vision and needs. Finally, several 6G launch issues are discussed. The design enables migration beyond 5G/6G networks. This study also discusses 6G technology and applications. 6G will include Artificial Intelligence enabled services, reconfigurable intelligent surfaces, tera hertz communication and antenna structure with key applications with the challenges faced at tera hertz communication.

This paper is investigating and comparing three channel models for the fifth generation (5G) wireless communications: the quasi deterministic radio channel generator (QuaDRiGa), the NYUSIM developed by New York University (NYU) and the more general 5G (MG5G) channel model. The three channel models employ different approaches to model the time non-stationary characteristics of the 5G wireless communications, such as the geometry-based drifting modeling and cluster birth-death methodology. Simulations are carried out using the three channel models to analyze the statistical properties including angle power spectrum (APS), power delay profile (PDP), temporal autocorrelation function (ACF), and spatial cross-correlation function (CCF). Simulation results show that the calculation of angular parameters contributes to the performance of APS, generation approaches of path powers and cluster parameters have significant impact on PDP performance, the performance of ACF and CCF varies mainly due to the calculations of path delays and angle spreads for the three channel models in urban macrocell (UMa) mobile NLOS environments.

The wireless mobile communication systems have developed from the second generation (2G) through to the current fourth generation (4G) wireless system, transforming from simply telephony system to a network transporting rich multimedia contents including video conferencing, 3-D gaming and in-flight broadband connectivity (IFBC) where airline crew use augmented reality headsets to address passengers personally. However, there are still many challenges that are beyond the capabilities of the 4G as the demand for higher data rate, lower latency, and mobility requirement by new wireless applications sores leading to mixed content-centric communication service. The fifth generation (5G) wireless system has thus been suggested, and research is ongoing for its deployment beyond 2020. In this article, we investigate the various challenges of 4G and propose an indoor, outdoor segregated cellular architecture with cloud-based Radio Access Network (C-RAN) for 5G, we review some of its key emerging wireless technologies needed in meeting the new demands of users including massive multiple input multiple output (mMIMO) system, Device-to-Device (D2D), Visible Light Communication (VLC), Ultra-dense network, Spatial Modulation and Millimeter wave technology. It is also shown how the benefits of the emerging technologies can be optimized using the Software Defined Networks/Network Functions Virtualization (SDN/NFV) as a tool in C-RAN. We conclude that the new 5G wireless architecture will derive its strength from leveraging on the benefits of the emerging hardware technologies been managed by reconfigurable SDN/NFV via the C-RAN. This work will be of immense help to those who will engage in further research expedition and network operators in the search for a smooth evolution of the current state of the art networks toward 5G networks.

The fifth Generation (5G) of wireless communication standards and Cognitive radio (CR) are believed to be the solution for present day data intensive applications. The 5G wireless networks are expected to provide higher data transfer rates, ubiquitous connectivity, low end-to-end latency, much higher system capacity and improved energy efficiency. Cognitive radio network (CRN) offers dynamic spectrum sharing to achieve higher spectrum efficiencies as required in 5G architecture. Present report encompasses concise information about mobile cellular system, 5G requirements, 5G enabling technologies and cognitive radio paradigm for 5G heterogeneous multi-tier networks.

The increasing demand for higher data rates, better quality of service, fully mobile and connected wireless networks lead the researchers to seek new solutions beyond 4G wireless systems. It is anticipated that 5G wireless networks, which are expected to be introduced around 2020, will achieve ten times higher spectral and energy efficiency than current 4G wireless networks and will support data rates up to 10 Gbps for low mobility users. The ambitious goals set for 5G wireless networks require dramatic changes in the design of different layers for next generation communications systems. Massive multiple-input multiple-output (MIMO) systems, filter bank multi-carrier (FBMC) modulation, relaying technologies, and millimeter-wave communications have been considered as some of the strong candidates for the physical layer design of 5G networks. In this article, we shed light on the potential and implementation of index modulation (IM) techniques for MIMO and multi-carrier communications systems which are expected to be two of the key technologies for 5G systems. Specifically, we focus on two promising applications of IM: spatial modulation (SM) and orthogonal frequency division multiplexing with IM (OFDM-IM), and we discuss the recent advances and future research directions in IM technologies towards spectral and energy-efficient 5G wireless networks.

As the demand for higher speed data transmissions continues to increase exponentially beyond the speed-limit of the fourth generation (4G) wireless networks due to the rapid spectrum depletion of the microwave frequency bands below 6 GHz, it has become quite evident that the existing wireless communication systems will eventually be constrained from meeting the huge throughput requirements for various emerging applications beyond 4G wireless networks. In order to sustain the future market dominance of wireless communications, the narrowness of wireless bandwidths in the existing systems, which has become a key issue for the upcoming wireless systems, needs to be addressed by looking beyond the traditional microwave spectrum domain through the exploitation of the huge bandwidths available in the millimeter wave bands. In this work, we have conducted the review for a series of measurements at various microwave bands, below 6 GHz and above, to study the behavior of ultra-wideband (UWB) channels, typically in different indoor and outdoor environments. These measurements have been used to gain a useful insight into the path loss and time dispersion parametric behaviors of the 5G channel and to investigate the channel characterization of the UWB signals within spatially restricted locations. Moreover, these measurements have been used to evaluate the newest channel model and channel prediction which have proposed for 5G.

The telecommunication industry has changed the way we communicate, work and socialize in a remarkable way since its inception. This change is continuous as new services and applications are being developed and deployed worldwide. In order to confront the requirements of new services, there are still many technical challenges. These include enhanced capacity, high data rate, low latency, spectral and energy efficiency. Therefore, researchers target on 5G wireless communication systems that are scheduled to be rolled out by the year 2020. In this paper, we give an overview of the 5G wireless standard and expected performance characteristics. Promising technologies including Millimeter Wave Technology, Massive MIMO, green Communication, and Cognitive Radio Networks are identified to support the requirements of 5G. Finally, we present numerical results on the path loss characteristics utilizing the SUI model for microwave band and modified SUI model for the mm-wave band.

Enhancing the robustness of object detection via 6G vehicular edge computing

A fully operative and efficient 5G network cannot be complete without the inclusion of artificial intelligence (AI) routines. Existing 4G networks with all-IP (Internet Protocol) broadband connectivity are based on a reactive conception, leading to a poorly efficiency of the spectrum. AI and its subcategories like machine learning and deep learning have been evolving as a discipline, to the point that nowadays this mechanism allows fifth-generation (5G) wireless networks to be predictive and proactive, which is essential in making the 5G vision conceivable. This paper is motivated by the vision of intelligent base stations making decisions by themselves, mobile devices creating dynamically-adaptable clusters based on learned data rather than pre-established and fixed rules, that will take us to a improve in the efficiency, latency, and reliability of the current and real-time network applications in general. An exploration of the potential of AI-based solution approaches in the context of 5G mobile and wireless communications technology is presented, evaluating the different challenges and open issues for future research.