Enhancing 6G wireless performance through advanced MIMO techniques

In this chapter, we present advanced schemes for the evolution of multiple access and MIMO. In particular, non‐orthogonal multiple access (NOMA) and smart vertical MIMO (SV‐MIMO) are introduced as new advanced interference management and MIMO schemes to enable future enhancements of spectrum efficiency. Both schemes aim to improve spectrum utilization efficiency without the need to install new antenna equipment. NOMA superposes multiple users in the power domain and exploits the channel‐gain differences among multiplexed users, while SV‐MIMO performs 3D MIMO transmission using antenna elements that are adaptively grouped vertically according to the type of signal or channel quality at the receiving mobile terminal. Regarding NOMA, we present our design concept and its performance gains over traditional OFDMA. Regarding SV‐MIMO, we describe the characteristics of adaptive mode selection, system‐level simulation results, and our experimental results, and compare its performance gains over conventional systems without adaptive antenna grouping.

For the application of advanced smart antenna and MIMO techniques as joint transmission, channel inversion and Tomlinson-Harashima pre-coding in future radio systems, channel side information is required at the transmitter. In the time-division duplex mode, the reciprocal channel coefficients estimated in the uplink may in principle be reused in the downlink. In practice, the reciprocity must not be limited to the radio frequency channel between the antennas but it should be available also at the transceiver interfaces to the baseband signal processing. Here we propose a new transceiver design suitable for the application of these advanced techniques.

This article proposes criteria and mechanisms that achieve seamless inter-working between the multi-radio access technologies that will compose the fourth-generation (4G) wireless mobile environment. We address the problem of incorporating system interoperability in order to provide the user with seamless mobility across different radio access technologiess namely we focus on inter-working UMTS-High Speed Downlink Packet Access (HSDPA) and WLAN networks, as these two networks are believed to be major components of the 4G wireless network. Interoperability results in providing the user with a rich range of services across a wide range of propagation environment and mobility conditions, using a single terminal. Specifically, the article aims at defining the criteria and mechanisms for interoperability between the two networks. Our approach considers the use of Cost functions to monitor the essential parameters at the system level in order to trigger an interoperability procedure. Initial user assignment and inter-system handover are considered the incidents that initiate the interoperability algorithm execution. The overall objective of this work is to assess the performance of our developed interoperability platform and to optimize system performance by guarantying a minimum QoS requirement and maximizing network capacity.

Compared to the preceding generations networks to attain fast data transfer and high data rates, the 5G wireless communication has deployed in many countries. The access point's raising level and number of wireless devices will increase the level of EMF radiation and exposure. Several researchers have voiced their concerns about 5G that it raised on adverse health impacts by high expose of Electromagnetic Fields (EMF). This paper presents the human EMF exposure on human body and mitigation techniques which are used to reduce the risks and also it investigates the impacts of 5G downlinks. The adverse health impacts related to EMF is still on debate in science. Several health organizations already provided the safety guidelines about 5G and suggest minimum distance between User Equipment (UE) and the Base Station (BS) or transmitter. Nevertheless, it is still under in consideration that is not safe to human while we are using the high frequencies. i.e., above 6 GHz. In this article I analyze the alleged health effects, impact and challenges of 5G and also accurate estimation of the EMF distribution by using Specific Absorption Rate, Massive MIMO and Power Density techniques.

The sixth generation (6G) wireless networks are required to provide the massive ultra-reliable low-latency communication (mURLLC) services for massive subscribers, and thus, need to be supported by new techniques. Since the massive multiple-input multiple-output (massive MIMO) technique with massive antennas is able to substantially improve the channel performance, it has been widely applied to achieve the goal of mURLLC networks. Moreover, based on the inherent advantages of high mobility and dynamically deployment, the emerging unmanned aerial vehicle (UAV) technique has also been considered as one of the promising candidate techniques in the 6G wireless networks. However, how to integrate the massive MIMO and UAV techniques has never been thoroughly studied. In this paper, we first establish the massive MIMO channel model between a set of UAVs and a ground station, equipped with uniform rectangular antenna array. Then, we derive the expression of channel capacity for this channel model, which is a function of the distance between each UAV and each antenna. To support the mURLLC traffics in the 6G wireless networks, we employ the effective capacity theory to measure the maximum packet arrival rate, and we also derive the upper-bound on the effective capacity, which is a function of our obtained channel capacity. Finally, we validate and evaluate our derived results of the UAV communication with massive MIMO channel over 6G wireless networks through numerical analyses.

The high cost of cellular spectrum has motivated network providers to seek advanced MIMO techniques to improve spectral efficiency [2, 1]. Yet, only point-to-point MIMO multiplexing can be performed efficiently in current networks [3]. More advanced MIMO solutions, such as massive MIMO, coordinated multi-point, distributed MIMO, and multi-user MIMO, all require the base station to know the downlink channels prior to transmission. In the absence of this information, the base station cannot beamform its signal to its users

Modern evaluation methodologies for system level simulations of mobile radio networks (e.g., [1]) support modeling systems with multiple simultaneously operating base stations and mobile devices where accurate simulation of multi-user MIMO and other space-time signal processing techniques should be provided. To be able to predict realistic performance, such models introduce a number of channel parameters with complex auto- and cross-correlation properties. Particularly, such models include a set of large-scale parameters (tap delay spread, angular spreads of rays at the base station and mobile station sides, shadow fading, etc.) being cross-correlated as well as auto-correlated in the spatial domain (across the deployment area) with different correlation functions. This paper is devoted to a method for accurate generation of correlated channel parameters during a simulation based on filtering of the parameters defined in the nodes of a spatial grid. The proposed method combines formal mathematical exactness at least in the asymptotic case and a much lower computational complexity in comparison with existing solutions [2]. Method description, analytical derivation, implementation details and verification by numerical simulations for an exemplary deployment scenario are provided in the paper. The described method may be recommended for application in system level simulators for 3G and 4G mobile radio access networks such as WCDMA HSPA, IEEE 802.16m, LTE-A.

This paper proposes an advanced OFDM-MIMO reconfigurable architecture that uses an adaptive switching algorithm between diversity and spatial multiplexing. The transmitter blocs' specifications such as the MIMO technique and the modulation scheme are adjusted according to the channel state, which gives a practical cognitive radio strategy. The system cost- efficiency is performed by the application of the Software Defined Radio (SDR) technology. Based on the Demmel condition number criterion, an indicator bit exchange between the transmitter and the receiver allows selecting the adapted MIMO configuration and improving the whole system performances.

Long Term Evolution (LTE) is an emerging 4G wireless access technology. It is showing a lot of promise in field trials and gaining acceptance among the major wireless vendors. The Long Term Evolution (LTE) standard for mobile broadband employs this MIMO technique in its transmission modes which were defined in release 8. The advantage of using MIMO is the improved performance in terms of coverage, spectral efficiency, reduced power consumption and peak throughput in LTE downlink, PDSCH channel can use several MIMO techniques which includes transmit diversity, spatial multiplexing and beamforming. The antenna configuration in transmitting and receiving side may be 212, 214 or 414. However the performance of transmission modes varies with the variation of multipath channel, UE speed and UE location within a cell. So, it is necessary to analyze their performance by considering the above facts. In this paper, the throughput conditions are investigated by changing the UE speed and also changing multipath channel in order to find out which transmission mode is best for which condition.

IEEE 802.16m and 3GPP LTE-Advanced are the two evolving standards targeting 4G wireless systems. In both standards, multiple-input multiple-output antenna technologies play an essential role in meeting the 4G requirements. The application of MIMO technologies is one of the most crucial distinctions between 3G and 4G. It not only enhances the conventional point-to-point link, but also enables new types of links such as downlink multiuser MIMO. A large family of MIMO techniques has been developed for various links and with various amounts of available channel state information in both IEEE 802.16e/m and 3GPP LTE/LTE-Advanced. In this article we provide a survey of the MIMO techniques in the two standards. The MIMO features of the two are compared, and the engineering considerations are depicted.

MIMO or multiple-input multiple-output technology is the use of multiple antennas in wireless networks to increase the throughput of such a network to solve the current limitations of the electromagnetic spectrum and is the only viable approach for substantial improvement of spectral efficiency. MIMO technology is classified into one of three categories whose development occurred at different non-overlapping time intervals: point-to-point MIMO, multiuser MIMO, and massive MIMO. In this book, engineering principles of massive MIMO are examined and explained, which arguably will be the ultimate embodiment of MIMO technology. The book explains different technologies of MIMO and their important differences through key topics in multi-cell systems, such as propagation modeling, multiplexing and demultiplexing, channel estimation, power control, performance evaluation, and analyses, and development of advanced massive MIMO techniques and algorithms to design complex wireless communication systems. The book covers a lot of technologies related to MIMO and their design. It offers a detailed picture of wireless networks that implement multiple inputs and multiple outputs, and it offers a great deal of knowledge in how to design and implement such networks and how to measure their performance and efficiency. This book also has plenty of examples and offers discussions at the end of each chapter related to the subject.

In future 5G wireless networks, inter-cell interference (ICI) is perceived as one of the most critical performance bottlenecks. Traditionally, the interference is treated as an additional source of noise, recent advances in information theory show that interference is not necessarily an opponent, but might be decoded and cancelled to obtain a larger capacity region. In this paper, a sparse code multiple access (SCMA) based uplink ICI cancellation technique is proposed to enhance the performance of the cell-edge users by jointly decoding the desired signal and the interference signal at the base stations. Unlike the orthogonal transmission schemes such as fractional frequency reuse in 4G, the proposed non-orthogonal SCMA-based scheme allows several cell-edge users to share the same time-frequency resource blocks (RBs). The sparse codewords are designed to make each user spread its data on a small set of RBs to achieve frequency and interference diversity, and make the near-optimal detection feasible with moderate complexity through iterative message passing algorithm (MPA). Then an open-loop MIMO transmission scheme which combines SCMA with Alamouti code is proposed to achieve full space-time-frequency diversity. Simulation results show that when there is no correlation among resource blocks and the antenna configuration is 1×1, the proposed SCMA-based scheme has about 2dB gain for uplink cell-edge users in multi-cell scenario compared with the FFR-based ICI coordination scheme in LTE networks. The gain becomes larger when combined with the existing MIMO technique. In addition, the SCMA-based scheme is also proved to be more robust to the burst interference.

This contribution presents the future prospects of radio propagation modelling, with emphasis on deterministic propagation modelling, which is becoming of notable interest in view of future wireless systems adopting mm-wave frequencies and/or advanced MIMO transmission schemes. It is often said that there is not much to further investigate on radio propagation. These rumours often come from the same sources wherefrom criticism is raised about the reliability of propagation models, deterministic ones in particular. This view is actually contradictory: if propagation modelling problems are difficult to solve, and often actually unsolved, then there is place - and need - for further work. The fundamental question is: can a better knowledge of the multi-dimensional characteristics of the radio channel help in the design, deployment and optimization of future wireless systems? The answer is yes, and some motivations for this answer are given here. Quality of Service (QoS) is now a widely used term, and this fact suggests that, in a relatively mature application field such as the mobile radio one, QoS is becoming a strategic performance metric to assess the competitive advantage of different technical solutions or services. Still, not enough attention is being devoted to the actual propagation characteristics, which directly and dramatically impact on the QoS. The same is true for MIMO, Beamforming and UWB transmission techniques where the knowledge of the radio channel and of the real-time Channel State Information (CSI) is of fundamental importance. An increasing number of short-range, high frequency applications is envisioned for the next future, including gigabit wireless applications for indoor connectivity [1], mm-wave back-hauling for urban mobile radio networks [2] [3], etc. Besides the greater spectrum availability, one of the advantages of mm-wave frequencies is the small wavelength, which allows to implement compact, high-order MIMO antenna arrays and therefore to put into action beamforming techniques with narrow beams yielding optimum spatial-spectrum use and high signal-to-interference ratios. In such applications the propagation process takes place in a more limited and well-defined environment with respect to public mobile radio systems making use of large cells and lower frequencies. This represents the ideal field of application of deterministic propagation models such as Ray Tracing (RT). Being based on a sound, albeit approximate, theory such as Ray Optics, ray-based models can be considered very reliable when the wavelength is small compared to the size of the obstacles and when the propagation environment is limited, so that a detailed environment description is possible. RT models have been studied, developed and used for over two decades now. In particular the capability of RT models to predict the spatial and temporal dispersion characteristic of the radio channel, which is very valuable for the design of MIMO and beamforming systems, has been object of several studies [4] [5]. Recent investigations have shown that proper Diffused (or Distributed) Scattering models embedded into the RT engine can increase the prediction performance, especially in terms of the mentioned multi-dimensional dispersion parameters [6] [7]. The increasing availability of low-cost computation power and accurate 3D digital building databases will probably encourage the widespread use of deterministic propagation models in the future. Moreover, since future systems will be empowered with accurate positioning capabilities, deterministic propagation models such as ray tracing will be used not only "off-line" to assist in the system design and deployment phase, but also embedded into the system for on-line, real-time channel prediction to help estimate the CSI, thus reducing the need of costly and time-consuming channel sounding techniques. These and other future developments in the field of deterministic radio propagation modelling will be presented and discussed in this contribution.

Distributed antenna systems (DAS) are traditionally deployed for the coverage purpose, where multiple antennas connected with a common source are geographically separated within the cell. In order to provide high rate services in the 4G wireless system, DAS should be further enhanced with the help of advanced MIMO techniques. In this paper, we start with reviewing the typical scenarios for DAS, which are widely discussed in standardization. Then, the benefits of DAS with single antenna selection (SAS) are analyzed. Based on this, a DAS transmission mode compatible with 3GPP Long Time Evolution (LTE) Release 8 standard is proposed. According to the system level simulation, the cell average and cell edge throughput can be improved by 35.0% and 82.3% respectively, compared with LTE Release 8 system. Moreover, the total transmitted power can be reduced by 75%.

The BuNGee FP7 project is looking at achieving throughput densities substantially higher than available with today‘s systems. The project addresses this goal by a combination of techniques: below-rooftop access base stations and a unique feeding architecture using a combination of licensed in-band and out-of-band license exempt spectrum. Very high capacity feeding hubs with high-order spatial reuse are created using multi-beam antennas and advanced MIMO techniques, using millimeter waves.