Abstract Future mobile networks are envisioned to provide wireless access to a massive number of devices. The substantial increase in connectivity comes mainly from machine-type communication (MTC), for which a large number of low-rate transmissions take place. Accommodating access for such a large number of user equipment (UEs) can be inefficient if applied to current network architectures, which are mainly based on orthogonal multiple access (OMA) and scheduling-based transmissions. This is due to the resulting control overhead and increased access delay. The framework of non-orthogonal multiple access (NOMA) has attracted attention recently as a promising solution to tackle these issues. It allows multiple UEs to access the network simultaneously over the same resources, and provides naturally, the support for grant-free access, in which no explicit scheduling of the UEs is required. Motivated by the potential benefits of NOMA in enabling ...

5G-and-beyond communication systems are expected to be in a heterogeneous form of multiple-antenna cellular base stations (BSs) overlaid with small cells. The fully-digital BS structures can incur significant power consumption and hardware complexity. Moreover, the wireless BSs for small cells usually have strict size constraints, which incur additional hardware effects such as mutual coupling (MC). Consequently, the transmission techniques designed for future wireless communication systems should respect the hardware structures at the BSs. For this reason, in this thesis we extend generic downlink precoding to more advanced hardware-informed transmission techniques for a variety of BS structures. This thesis firstly extends the vector perturbation (VP) precoding to multiple-modulation scenarios, where existing VP-based techniques are sub-optimal. Subsequently, this thesis focuses on the downlink transmission designs for hardware effects in the form of MC, limited number of radio frequency (RF) chains, and low-precision ...

The last ten years have seen a massive growth in the number of connected wireless devices. Billions of devices are connected and managed by wireless networks. At the same time, each device needs a high throughput to support applications such as voice, real-time video, movies, and games. Demands for wireless throughput and the number of wireless devices will always increase. In addition, there is a growing concern about energy consumption of wireless communication systems. Thus, future wireless systems have to satisfy three main requirements: i) having a high throughput; ii) simultaneously serving many users; and iii) having less energy consumption. Massive multiple-input-multiple-output (MIMO) technology, where a base station (BS) equipped with very large number of antennas (collocated or distributed) serves many users in the same time-frequency resource, can meet the above requirements, and hence, it is a promising candidate technology ...

In the last decades the world has experienced a massive growth in the demand for wireless services. The recent popularity of hand-held devices with data exchange capabilities over wireless networks, such as smartphones and tablets, increased the wireless data traffic even further. This trend is not expected to cease in the foreseeable future. In fact, it is expected to accelerate as everyday apparatus unrelated with data communications, such as vehicles or household devices, are foreseen to be equipped with wireless communication capabilities. Further, the next generation wireless networks should be designed such that they have increased spectral and energy efficiency, provide uniformly good service to all of the accommodated users and handle many more devices simultaneously. Massive multiple-input multiple-output (Massive MIMO) systems, also termed as large-scale MIMO, very large MIMO or full-dimension MIMO, have recently been proposed as a candidate ...

Mobile communications has become so successful today that conventional radio technologies, in traditional frequency bands below 6 GHz, are soon reaching their limits. To be able to develop massively deployed, ubiquitous, data-hungry, mobile applications, this study explores the use of higher frequency bands, or so-called millimeter waves in mobile communications. These radio bands above 30 GHz are mostly unoccupied and have dozens of gigahertz of bandwidth available. Moreover, advances in electronics have now made it possible to utilize these bands cost effectively. This thesis studied the millimeter wave wireless channel through conducting the following experiments: (1) two indoor millimeter wave measurement campaigns with directive horn antennas on both link ends, (2) an outdoor vehicular millimeter wave measurement campaign employing a horn antenna and an omni directional antenna, and (3) a railway communications ray-tracing study with directive antennas on both sides. ...

The envisioned rapid and exponential increase of wireless data traffic demand in the next years imposes rethinking current wireless cellular networks due to the scarcity of the available spectrum. In this regard, three main drivers are considered to increase the capacity of today's most advanced (4G systems) and future (5G systems and beyond) cellular networks: i) use more bandwidth (more Hz) through spectral aggregation, ii) enhance the spectral efficiency per base station (BS) (more bits/s/Hz/BS) by using multiple antennas at BSs and users (i.e. MIMO systems), and iii) increase the density of BSs (more BSs/km2) through a dense and heterogeneous deployment (known as dense heterogeneous cellular networks). We focus on the last two drivers. First, the use of multi-antenna systems allows exploiting the spatial dimension for several purposes: improving the capacity of a conventional point-to-point wireless link, increasing the number ...

Multiple antennas at the base station side can be used to enhance the spectral efficiency and energy efficiency of the next generation wireless technologies. Indeed, massive multi-input multi-output (MIMO) is seen as one promising technology to bring the aforementioned benefits for fifth generation wireless standard, commonly known as 5G New Radio (5G NR). In this monograph, we will explore a wide range of potential topics in multi-user MIMO (MU-MIMO) relevant to 5G NR, • Sum rate maximizing beamforming (BF) design and robustness to partial channel state information at the transmitter (CSIT) • Asymptotic analysis of the various BF techniques in massiveMIMO and • Bayesian channel estimationmethods using sparse Bayesian learning. While massive MIMO has the aforementioned benefits, it makes the acquisition of the channel state information at the transmitter (CSIT) very challenging. Since it requires large amount of uplink (UL) ...

Massive multiple-input multiple-output (MIMO) evolved to a key enabling physical layer (PHY) technology for the fifth generation (5G) of mobile communication systems and beyond. While the envisioned use cases of such communications systems are diverse, so are the challenges to meet their respective requirements. As a large-scale evolution of already well-established MIMO communications technologies, massive MIMO promises benefits with respect to all possible use cases. Theoretical works on massive MIMO, however, typically assumes i.i.d. Rayleigh fading channels without spatial channel correlation. The application of this model is justified through the assumption of rich scattering environments, which is claimed to hold, for example, in indoor environments. Spatial correlation of wireless channels leads to inter-stream interference in single-user MIMO communications systems and to inter-user interference in multi-user MIMO systems with linear precoding. Channel correlation is therefore crucial for the performance of such ...

In a future perspective, the need of mapping an unknown indoor environment, of localizing and retrieving information from objects with zero costs and efforts could be satisfied by the adoption of next 5G technologies. Thanks to the mix of mmW and massive arrays technologies, it will be possible to achieve a higher indoor localization accuracy without relying on a dedicated infrastructure for localization but exploiting that designed for communication purposes. Besides users’ localization and navigation objectives, mapping and thus, the capability of reconstructing indoor scenarios, will be an important field of research with the possibility of sharing environmental information via crowd-sourcing mechanisms between users. Finally, in the Internet of Things vision, it is expected that people, objects and devices will be interconnected to each other with the possibility of exchanging the acquired and estimated data including those regarding objects identification, ...

After decades of research on multiple-input multiple-output (MIMO) technology, including paradigm shifts from point-to-point to multiuser MIMO (MU-MIMO), an ample literature exists on techniques to exploit the spatial dimension to increase link throughput and network capacity of wireless communication systems. Massive MIMO, which supports hundreds of antennas at the base station (BS), is celebrated as the key enabling technology of the upcoming fifth generation (5G) wireless communication standard. However, the use of large MIMO systems in the future is also indispensable, especially for high-speed wireless backhaul connectivity. Large MIMO systems use tens of antennas in communication terminals, and can afford a large number of antennas on both the transmitter and the receiver sides. While favorable propagation in massive MIMO ensures that reliable performance can be achieved by simple linear processing, the inherent symmetry in large MIMO renders the computational complexity ...

Massive MIMO (multiple-input–multiple-output) is a multi-antenna technology for cellular wireless communication, where the base station uses a large number of individually controllable antennas to multiplex users spatially. This technology can provide a high spectral efficiency. One of its main challenges is the immense hardware complexity and cost of all the radio chains in the base station. To make massive MIMO commercially viable, inexpensive, low-complexity hardware with low linearity has to be used, which inherently leads to more signal distortion. This thesis investigates how the degenerated linearity of some of the main components—power amplifiers, analog-to-digital converters (ADCs) and low-noise amplifiers—affects the performance of the system, with respect to data rate, power consumption and out-of-band radiation. The main results are: Spatial processing can reduce PAR (peak-to-average ratio) of the transmit signals in the downlink to as low as 0B; this, however, does ...

The next generation of wireless communication networks will facilitate the connection of a large number of devices and a broad range of services. Serving such a large amount of user equipment (UEs) can be of very high cost if using active antenna solutions such as increasing the number of base stations (BSs), using massive multiple-input multiple-output (MIMO) antennas, and deploying relays between the BSs and the UEs. In this context, a passive antenna solution, such as reconfigurable intelligent surfaces (RISs), would be more beneficial and attractive. RIS has become an emerging technology with diverse applications in future wireless networks, owing to its ability to dynamically control and optimize the propagation environment. The rapid evolution driven by escalating performance demands of coverage in blocked line-of-sight (LOS) scenarios has prompted the exploration of RIS. Motivated by the potential benefits of RIS in ...

The thriving development of wireless communications calls for innovative and advanced signal processing techniques targeting at an enhanced performance in terms of reliability, throughput, robustness, efficiency, flexibility, etc.. This thesis addresses such a compelling demand and presents new and intriguing progress towards fulfilling it. We mainly concentrate on two advanced multi-dimensional signal processing challenges for wireless systems that have attracted tremendous research attention in recent years, multi-carrier Multiple-Input Multiple-Output (MIMO) systems and multi-dimensional harmonic retrieval. As the key technologies of wireless communications, the numerous benefits of MIMO and multi-carrier modulation, e.g., boosting the data rate and improving the link reliability, have long been identified and have ignited great research interest. In particular, the Orthogonal Frequency Division Multiplexing (OFDM)-based multi-user MIMO downlink with Space-Division Multiple Access (SDMA) combines the twofold advantages of MIMO and multi-carrier modulation. It is the essential element ...

Since several years, multi-antenna systems are foreseen as a potential solution for increasing the throughput of future wireless communication systems. The aim of this thesis is to study and to improve the transmitter and receiver's techniques of these MIMO (Multiple Input Multiple Output) systems in the context of a multi-carrier transmission. On the one hand, the OFDM (Orthogonal Frequency Division Multiplex) modulation, which transform a frequency selective channel into multiple non frequency selective channels, is particularly well adapted to the conception of MIMO receivers with low complexity. On the other hand, two techniques allowing to improve the exploitation of frequential and/or temporal diversities are associated with OFDM, namely linear precoding (LP-OFDM) and CDMA in a MC-CDMA (Multicarrier Code division Multiplex Access) scheme. We have associated LP-OFDM and MC-CDMA with two MIMO techniques which require no channel state information at the ...

Future wireless networks will evolve to integrate communication, localization, and sensing capabilities. This evolution is driven by emerging application platforms such as digital twins, on the one hand, and advancements in wireless technologies, on the other, characterized by increased bandwidths, more antennas, and enhanced computational power. Crucial to this development is the application of artificial intelligence (AI), which is set to harness the vast amounts of available data in the sixth-generation (6G) of mobile networks and beyond. Integrating AI and machine learning (ML) algorithms, in particular, with wireless localization offers substantial opportunities to refine communication systems, improve the ability of wireless networks to locate the users precisely, enable context-aware transmission, and utilize processing and energy resources more efficiently. In this dissertation, advanced ML algorithms for enhanced wireless localization are proposed. Motivated by the capabilities of deep neural networks (DNNs) and ...