Neural Network-Based Fading Channel Prediction: A Comprehensive Overview <s> A. SYSTEM MODEL <s> This paper employs a high resolution quantization framework to study the effects of finite-rate feedback of the channel state information (CSI) on the performance of multiple-input-multiple-output (MIMO) systems over independently and identically distributed (i.i.d.) Rayleigh flat fading channels. The contributions of this paper are twofold. First, we extend the general distortion analysis of vector quantizers to deal with complex source variables. Necessary and sufficient conditions that guarantee a concise high-resolution distortion analysis in the complex domain is presented. Second, as an application of the proposed complex distortion analysis, tight lower bounds on the capacity loss due to the finite-rate channel quantization are provided for MIMO systems employing a fixed number of equal power spatial beams. Based on the obtained closed-form analytical results, it is shown that the system capacity loss decreases exponentially as the ratio of the quantization rate to the total degrees of freedom of the channel state information to be quantized. Moreover, MIMO CSI-quantizers using mismatched codebooks that are only optimized for high-signal-to-noise ratio (SNR) and low-SNR regimes are also investigated to quantify the penalties incurred by the use of mismatched codebooks. In addition, the analysis is extended to deal with MIMO systems using multi-mode spatial multiplexing transmission schemes with finite-rate CSI feedback. Finally, numerical and simulation results are presented which confirm the tightness of the derived theoretical distortion bounds. <s> BIB001 </s> Neural Network-Based Fading Channel Prediction: A Comprehensive Overview <s> A. SYSTEM MODEL <s> The concept of physical layer security builds on the pivotal idea of turning the channel’s imperfections, such as noise and fading, into a source of security. This is established through appropriately designed coding techniques and signal processing strategies. In this vein, it has been shown that fading channels can enhance the transmission of confidential information and that a secure communication can be achieved even when the channel to the eavesdropper is better than the main channel. However, to fully benefit from what fading has to offer, the knowledge of the channel state information at the transmitter (CSIT) is of primordial importance. In practical wireless communication systems, CSIT is usually obtained, prior to data transmission, through CSI feedback sent by the receivers. The channel links over which this feedback information is sent can be either noisy, rate-limited, or delayed, leading to CSIT uncertainty. In this paper, we present a comprehensive review of recent and ongoing research works on physical layer security with CSIT uncertainty. We focus on both information theoretic and signal processing approaches to the topic when the uncertainty concerns the channel to the wiretapper or the channel to the legitimate receiver. Moreover, we present a classification of the research works based on the considered channel uncertainty. Mainly, we distinguish between the cases when the uncertainty comes from an estimation error of the CSIT, from a CSI feedback link with limited capacity, or from an outdated CSI. <s> BIB002
This article focuses on point-to-point MIMO systems consisting of a single transmitter and a single receiver, whereas multi-user MIMO is not considered taking into account the state of the art in this field. A narrow-band MIMO system with N t transmit and N r receive antennas can be modeled by where r(t)= r 1 (t), . . . , r N r (t) T denotes the N r ×1 vector of received signals at time t, s(t)= s 1 (t), . . . , s N t (t) T is the N t ×1 vector of transmitted signals, n(t) stands for the vector of additive white noise, H(t)= h n r n t (t) N r ×N t is the matrix of continuous-time channel impulse responses, and h n r n t ∈C 1×1 represents the gain of the flat fading channel between transmit antenna n t and receive antenna n r , where 1 n r N r and 1 n t N t . Due to feedback and processing delays, the obtained CSI at the transmitter may be outdated before its actual usage, i.e., H(t) = H(t+τ ), resulting in severe performance degradation of adaptive transmission systems BIB001 - BIB002 . The aim of channel prediction is to extrapolate a predicted valueĤ(t+τ ) at time t that approximates its actual value at the upcoming time t+τ as close as possible, namelŷ H(t+τ ) → H(t+τ ).