In multiple-input multiple-output (MIMO) communications systems, the channel state information (CSI) is typically estimated at the receiver side by sending a few known pilots and then used for decoding at the receiver and/or for precoding at the transmitter. These are known as coherent schemes. However, in scenarios dominated by fast fading or massive MIMO systems dedicated to ultra-reliable low-latency communications (URLLC), getting an accurate channel estimate would require pilots to occupy a disproportionate fraction of communication resources. This becomes also a problem in machine-to-machine (M2M) communications that arise in the so-called Internet of Things (IoT). The advent of 5G and beyond (B5G) systems has introduced these novel scenarios that underscore the need for noncoherent communications schemes in which neither the transmitter nor the receiver has any knowledge about the instantaneous CSI. The Grassmannian and Stiefel manifolds play a significant role ...

The majority of communication systems need the previous knowledge of the channel, which is usually estimated by means of a training sequence. However, the transmission of pilot symbols provokes a reduction in bandwidth efficiency, which precludes the system from reaching the limits predicted by the Information Theory. This problem has motivated the development of a large number of blind channel estimation and equalization techniques, which are able to obtain the channel or the source without the need of transmitting a training signal. Usually, these techniques are based on the previous knowledge of certain properties of the signal, such as its belonging to a finite alphabet, or its higher-order statistics. However, in the case of multiple-input multipleoutput (MIMO) systems, it has been proven that the second-order statistics of the observations provide the sufficient information for solving the blind problem. The aim ...

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 ...

Multiple-input multiple-output (MIMO) systems will be applied in wireless communications in order to increase the performance, spectral efficiency, and reliability. Theoretically, the channel capacity of those systems grows linearly with the number of transmit and receive antennas. An important performance metric beneath capacity is the normalised mean square error (MSE) under the assumption of optimal linear reception. Clearly, both performance measures depend on the properties of the MIMO channel as well as on the considered system approach, e.g. on the type of channel state information which is available at the transmitter. It has been shown that even partial CSI at the transmitter can increase the performance. In this thesis, we analyse the performance and design optimal transmit strategies of singleand multiuser MIMO systems with respect to the statistical properties of the fading channel and under different types of CSI at ...

The widespread use of mobile internet and smart applications has led to an explosive growth in mobile data traffic. With the rise of smart homes, smart buildings, and smart cities, this demand is ever growing since future communication systems will require the integration of multiple networks serving diverse sectors, domains and applications, such as multimedia, virtual or augmented reality, machine-to-machine (M2M) communication / the Internet of things (IoT), automotive applications, and many more. Therefore, in the future, the communication systems will not only be required to provide Gbps wireless connectivity but also fulfill other requirements such as low latency and massive machine type connectivity while ensuring the quality of service. Without significant technological advances to increase the system capacity, the existing telecommunications infrastructure will be unable to support these multi-dimensional requirements. This poses an important demand for suitable waveforms with ...

In the last decade, cooperation among multiple terminals has been seen as one of the more promising strategies to improve transmission speed in wireless communications networks. Basically, the idea is to mimic an antenna array and apply distributed versions of well-known space-diversity techniques. In this context, the simplest cooperative scheme is the relay channel: all the terminals (relays) that overhear a point-to-point communication between a source and a destination may decide to aid the source by forwarding (relaying) its message. In a mobile system, it is common to assume that the relays do not have any information about the channel between them and the destination. Under this hypothesis, the best solution to exploit the diversity offered by multiple transmitting antennas is to use space-time coding (STC). However, classical STC's are designed for systems with a fixed and usually low number ...

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 ...

In the recent years, a significant portion of the research within the field of wireless communications has been motivated by two aspects: the constant increase in the number of wireless devices and the higher and higher data rate requirements of the individual applications. The undisputed outcome of these phenomena is the heavy congestion of the suitable spectral resources. This has inspired many innovative solutions for improving the spectral efficiency of the wireless communications systems by facilitating more simultaneous connections and higher data rates without requiring additional spectrum. These include technologies such as in-phase/quadrature (I/Q) modulation, multiple-input and multiple-output (MIMO) systems, and the orthogonal frequency-division multiplexing (OFDM) waveform, among others. Even though these existing solutions have greatly improved the spectral efficiency of wireless communications, even more advanced techniques are needed for fulfilling the future data transfer requirements in the ultra high ...

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 the last years, research has focused on multiple-input multiple-output (MIMO) wireless technology due to the capacity and performance improvement it provides, offering a higher spectral efficiency. In addition, when multiple users take part in the network, the scenario becomes much more complex, since resources like bandwidth, time or transmission power must be shared. Furthermore, the performance of the system is degraded as a consequence of the noise and multiuser interference (MUI). When the transmission is conducted from a base station (BS) to multiple users, a pre-equalization stage called precoding is applied. By means of this, each user will be able to interpret the signal independently, without the knowledge of the channel. Precoding techniques are classified into linear and non-linear. In fact, the non-linear Tomlinson-Harashima precoding (THP) and vector precoding (VP) techniques have been shown to achieve very good results ...

In the last few years, wireless devices have evolved to unimaginable heights. Current forecasts suggest that, in the near future, every device that may take advantage of a wireless connection will have one. In addition, there is a gradual migration to smart devices and high-speed connections, and, as a consequence, the overall mobile traffic is expected to experience a tremendous growth in the next years. The multiuser interference will hence become the main limiting factor and the most critical point to address. As instrumental to efficiently manage interference between different systems, this thesis provides a thorough study on cooperative techniques. That is, users share information and exploit it to improve the overall performance. Since multiuser cooperation represents a very broad term, we will focus on algorithm design and transceiver optimization for three cooperative scenarios that capture some of the main ...

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) ...

Polynomial eigenvalue decomposition (PEVD) is an extension of the eigenvalue decomposition (EVD) for para-Hermitian polynomial matrices, and it has been shown to be a powerful tool for broadband extensions of narrowband signal processing problems. In the context of broadband sensor arrays, the PEVD allows the para-Hermitian matrix that results from the calculation of a space-time covariance matrix of the convolutively mixed signals to be diagonalised. Once the matrix is diagonalised, not only can the correlation between different sensor signals be removed but the signal and noise subspaces can also be identified. This process is referred to as broadband subspace decomposition, and it plays a very important role in many areas that require signal separation techniques for multichannel convolutive mixtures, such as speech recognition, radar clutter suppression, underwater acoustics, etc. The multiple shift second order sequential best rotation (MS-SBR2) algorithm, built ...

Cooperative communications and multiple-input multiple-output (MIMO) communication systems are important topics in current research that will play key roles in the future of wireless networks and standards. These techniques can provide gains in data throughput, network capacity, coverage, outage, reduced error rates and power consumption, but can have an increased cost in computational complexity and present new problems in many areas. In this thesis, the various challenges in accurately detecting and estimating data signals and allocating resources in the cooperative systems are investigated. Firstly, we propose a cross-layer design strategy that consists of a cooperative maximum likelihood (ML) detector operating in conjunction with link selection for a cooperative MIMO network. The cooperative ML detector is derived, with considerations and approximations made for the knowledge of the system information that is available to the detector. Link selection in the cooperative network ...

Multiple-input multiple-output (MIMO) systems are encountered for example in communications if several transmit and receive antennas are empoyed, such that a separate transmit channel exists between every possible pairing of transmitter and receiver antennas. As a results if this spatial diversity, the channel capacity is dramatically increased over the single-inout single-output (SISO) case. While this increase is desired, the use of high data rates requires sophistiocated equalisation and/or detection schemes in the receiver to compensate for spatial and temporal dispersion in broadband MIMO channels, since a time-dispersive, in addition ot spatially-dispersice channel, must be assumed. The estimation of the broadband MIMO channel or its inverse is in general difficult and calls for training sequences that reduce the slot time for the transmission of actual data, which may counteract the promised gain in channel capacity. Another problem can be the computational ...