"Written by the pioneers of the concept, this is the first complete guide to the physical and engineering principles of Massive MIMO. Assuming only a basic background in communications and statisti ...

Fundamentals of Massive MIMO

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Linear And Nonlinear Programming

The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

/pdf/towards-6g-wireless-communication-networks-vision-enabling-2tj7a36yux.pdf

Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

Intelligent reflecting surfaces (IRSs) constitute a disruptive wireless communication technique capable of creating a controllable propagation environment. In this paper, we propose to invoke an IRS at the cell boundary of multiple cells to assist the downlink transmission to cell-edge users, whilst mitigating the inter-cell interference, which is a crucial issue in multicell communication systems. We aim for maximizing the weighted sum rate (WSR) of all users through jointly optimizing the active precoding matrices at the base stations (BSs) and the phase shifts at the IRS subject to each BS’s power constraint and unit modulus constraint. Both the BSs and the users are equipped with multiple antennas, which enhances the spectral efficiency by exploiting the spatial multiplexing gain. Due to the non-convexity of the problem, we first reformulate it into an equivalent one, which is solved by using the block coordinate descent (BCD) algorithm, where the precoding matrices and phase shifts are alternately optimized. The optimal precoding matrices can be obtained in closed form, when fixing the phase shifts. A pair of efficient algorithms are proposed for solving the phase shift optimization problem, namely the Majorization-Minimization (MM) Algorithm and the Complex Circle Manifold (CCM) Method. Both algorithms are guaranteed to converge to at least locally optimal solutions. We also extend the proposed algorithms to the more general multiple-IRS and network MIMO scenarios. Finally, our simulation results confirm the advantages of introducing IRSs in enhancing the cell-edge user performance.

/pdf/multicell-mimo-communications-relying-on-intelligent-x5bnpnqnlw.pdf

Multicell MIMO Communications Relying on Intelligent Reflecting Surfaces

Space-Time Block Coding for Wireless Communications

Block diagonalization (BD) is one of the most effective preprocessing techniques for multiuser multi-input multi-output (MU-MIMO) systems. By using BD the MU-MIMO broadcast channel can be decomposed into multiple parallel independent SU-MIMO channels through two singular value decomposition (SVD) operations. Complex lattice reduction (CLR) is another technique that aims to enforce orthogonality between the columns of the channel matrix and reduce its size as well. In this paper, only the first SVD is adopted to obtain parallel SU-MIMO channels with zero interference, the orthogonalization and size-reduction work are left for the CLR algorithm so that a modification of the channel matrix is carried out, resulting in a better precoding and detection performances. Simulation results show that the proposed algorithm greatly outperforms conventional BD detection and linear precoding techniques.

Lattice Reduction-Aided Preprocessing and Detection Techniques for MU-MIMO in Broadcast Channel

This paper investigates the M-estimate affine projection spline adaptive filtering (MAPSAF) algorithm, which utilizes a modified Huber function with robustness against impulsive interference, and employs historical regression data to update the weight and the knot vector estimates for nonlinear filtering tasks. The detailed convergence and steady-state analyses of MAPSAF are also carried out in the mean and mean-square senses. In addition, an improved MAPSAF by exploiting the combined step sizes, called the CSS-MAPSAF algorithm, is derived to speed up the convergence on the premise of low steady-state misalignment. Numerical experiments in nonlinear system identification and nonlinear acoustic echo cancellation problems corroborate the theoretical performance analysis and the superiority of the proposed algorithms. 

M-estimate affine projection spline adaptive filtering algorithm: Analysis and implementation

We propose blind adaptive multi-input multi-output (MIMO) linear receivers for DS-CDMA systems using multiple transmit antennas and space-time block codes (STBC) in multipath channels. A space-time code-constrained constant modulus (CCM) design criterion based on constrained optimization techniques is considered and recursive least squares (RLS) adaptive algorithms are developed for estimating the parameters of the linear receivers. A blind space-time channel estimation method for MIMO DS-CDMA systems with STBC based on a subspace approach is also proposed along with an efficient RLS algorithm. Simulations for a downlink scenario assess the proposed algorithms in several situations against existing methods.

Blind Adaptive MIMO Receivers for Space-Time Block-Coded DS-CDMA Systems in Multipath Channels Using the Constant Modulus Criterion

In this paper, we consider a general cooperative wireless sensor network (WSN) and the problem of channel estimation. A matrix-based set-membership recursive least squares (RLS) algorithm called BEACON is developed for the estimation of the complex channel parameters in order to reduce the computational complexity significantly and extend the lifetime of the WSN by reducing its power consumption. Then, we present and incorporate an error bound function into the BEACON channel estimation method which can adjust the error bound automatically with the update of the channel estimates. Computer simulations show good performance of our proposed algorithms in terms of convergence speed and steady state mean square error, reduced complexity and robustness to the time-varying environment and different signal-to-noise ratio (SNR) values.

BEACON channel estimation for cooperative wireless sensor networks based on data selection

In this paper, we investigate an opportunistic relay and jammer scheme along with relay selection algorithms based on the secrecy rate criterion in multiple-input multiple-output buffer-aided down link relay networks, which consist of one source, a number of relay nodes, legitimate users and eavesdroppers, with the constraints of physical layer security. The opportunistic relay and jammer scheme is employed to improve the transmission rate and different relay selection policies are performed to achieve better secrecy rate with the consideration of eavesdroppers. Among all the investigated relay selection policies, a relay selection policy which is developed to maximize the secrecy rate based on exhaustive searches outperforms other relay selection policies in terms of secrecy rate. Based on the secrecy rate criterion, we develop a relay selection algorithm without knowledge of the channels of the eavesdroppers. We also devise a greedy search algorithm based on the secrecy rate criterion to reduce the computational complexity of the exhaustive search technique. Simulations show the superiority of the secrecy rate criterion over competing approaches.

Rodrigo C. de Lamare

Papers

Lattice Reduction-Aided Preprocessing and Detection Techniques for MU-MIMO in Broadcast Channel

M-estimate affine projection spline adaptive filtering algorithm: Analysis and implementation

Blind Adaptive MIMO Receivers for Space-Time Block-Coded DS-CDMA Systems in Multipath Channels Using the Constant Modulus Criterion

BEACON channel estimation for cooperative wireless sensor networks based on data selection

Relay Selection Based on the Secrecy Rate Criterion for Physical-Layer Security in Buffer-Aided Relay Networks