Lower bound on the capacity of distributed MIMO systems with spatially correlated Rician/Lognormal fading

This paper presents an analytic lower bound of ergodic capacity for distributed MIMO (D-MIMO) systems that experience not only Rician fading but also shadowing effects of Lognormal distributed. In particularly, we consider that the Rician fading channel is spatially correlated at both transmitter and receiver. In the communication environment corresponding to this setting, the angle spread at the transmitter and the angle spread at the receiver are both insufficient, and the non-fading components co-exists with the fading components. Such communication environment is very common. In the process of deriving the analytic lower bound, in order to avoid Hayakawa polynomials that cannot be analytically expressed, non-central quadratic forms are transformed to non-central Wishart matrices by use of inequality. The validity of the presented lower bound is verified by computer simulations. The simulation results show the influence of the number of radio ports at the transmitter, the number of antennas at the transmitter or receiver, correlation level (angle spreads) and Rician K-factor on the capacity of systems. In all cases, the presented bound remains tight across the entire signal-to-noise ratio (SNR) regime.     

Intelligent Reflecting Surface–Assisted Wireless Secret Key Generation against Multiple Eavesdroppers

In this paper, we propose an improved physical layer key generation scheme that can maximize the secret key capacity by deploying intelligent reflecting surface (IRS) near the legitimate user aiming at improving its signal-to-noise ratio (SNR). We consider the scenario of multiple input single output (MISO) against multiple relevant eavesdroppers. We elaborately design and optimize the reflection coefficient matrix of IRS elements that can improve the legitimate user’s SNR through IRS passive beamforming and deteriorate the channel quality of eavesdroppers at the same time. We first derive the lower bound expression of the achievable key capacity, then solve the optimization problem based on semi-definite relaxation (SDR) and the convex–concave procedure (CCP) to maximize the secret key capacity. Simulation results show that our proposed scheme can significantly improve the secret key capacity and reduce hardware costs compared with other benchmark schemes.     

Energy Efficiency of User-Centric,Cell-Free Massive MIMO-OFDM with Instantaneous CSI

In the user-centric, cell-free, massive multi-input, multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) system, a large number of deployed access points (APs) serve user equipment (UEs) simultaneously, using the same time–frequency resources, and the system is able to ensure fairness between each user; moreover, it is robust against fading caused by multi-path propagation. Existing studies assume that cell-free, massive MIMO is channel-hardened, the same as centralized massive MIMO, and these studies address power allocation and energy efficiency optimization based on the statistics information of each channel. In cell-free, massive MIMO systems, especially APs with only one antenna, the channel statistics information is not a complete substitute for the instantaneous channel state information (CSI) obtained via channel estimation. In this paper, we propose that energy efficiency is optimized by power allocation with instantaneous CSI in the user-centric, cell-free, massive MIMO-OFDM system, and we consider the effect of CSI exchanging between APs and the central processing unit. In addition, we design different resource block allocation schemes, so that user-centric, cell-free, massive MIMO-OFDM can support enhanced mobile broadband (eMBB) for high-speed communication and massive machine communication (mMTC) for massive device communication. The numerical results verify that the proposed energy efficiency optimization scheme, based on instantaneous CSI, outperforms the one with statistical information in both scenarios.     

无背景噪声时光多输入多输出系统的信道容量

信道容量是通信系统能够达到的最大传输速率,是衡量通信系统通信能力的重要指标之一。在建立了光多输入多输出(MIMO)的信道模型之后,结合脉冲位置调制(PPM)分析了光MIMO系统的平均容量和中断容量;在无背景辐射的条件下,分别推导出了有无衰落时光MIMO平均容量封闭形式的近似表达式。在相同发射功率和传输带宽条件下,得到了光MIMO技术能成倍提高现有系统信道容量的结论。通过Monte Carlo仿真实验进一步证明了理论的正确性。     

Full-Duplex Relay with Delayed CSI Elevates the SDoF of the MIMO X Channel

In this article, the sum secure degrees-of-freedom (SDoF) of the multiple-input multiple-output (MIMO) X channel with confidential messages (XCCM) and arbitrary antenna configurations is studied, where there is no channel state information (CSI) at two transmitters and only delayed CSI at a multiple-antenna, full-duplex, and decode-and-forward relay. We aim at establishing the sum-SDoF lower and upper bounds. For the sum-SDoF lower bound, we design three relay-aided transmission schemes, namely, the relay-aided jamming scheme, the relay-aided jamming and one-receiver interference alignment scheme, and the relay-aided jamming and two-receiver interference alignment scheme, each corresponding to one case of antenna configurations. Moreover, the security and decoding of each scheme are analyzed. The sum-SDoF upper bound is proposed by means of the existing SDoF region of two-user MIMO broadcast channel with confidential messages (BCCM) and delayed channel state information at the transmitter (CSIT). As a result, the sum-SDoF lower and upper bounds are derived, and the sum-SDoF is characterized when the relay has sufficiently large antennas. Furthermore, even assuming no CSI at two transmitters, our results show that a multiple-antenna full-duplex relay with delayed CSI can elevate the sum-SDoF of the MIMO XCCM. This is corroborated by the fact that the derived sum-SDoF lower bound can be greater than the sum-SDoF of the MIMO XCCM with output feedback and delayed CSIT.     

Effect of Quantum Coherence on Landauer’s Principle

Landauer’s principle provides a fundamental lower bound for energy dissipation occurring with information erasure in the quantum regime. While most studies have related the entropy reduction incorporated with the erasure to the lower bound (entropic bound), recent efforts have also provided another lower bound associated with the thermal fluctuation of the dissipated energy (thermodynamic bound). The coexistence of the two bounds has stimulated comparative studies of their properties; however, these studies were performed for systems where the time-evolution of diagonal (population) and off-diagonal (coherence) elements of the density matrix are decoupled. In this paper, we aimed to broaden the comparative study to include the influence of quantum coherence induced by the tilted system–reservoir interaction direction. By examining their dependence on the initial state of the information-bearing system, we find that the following properties of the bounds are generically held regardless of whether the influence of the coherence is present or not: the entropic bound serves as the tighter bound for a sufficiently mixed initial state, while the thermodynamic bound is tighter when the purity of the initial state is sufficiently high. The exception is the case where the system dynamics involve only phase relaxation; in this case, the two bounds coincide when the initial coherence is zero; otherwise, the thermodynamic bound serves the tighter bound. We also find the quantum information erasure inevitably accompanies constant energy dissipation caused by the creation of system–reservoir correlation, which may cause an additional source of energetic cost for the erasure.     

Is Bitcoin’s Carbon Footprint Persistent? Multifractal Evidence and Policy Implications

The Bitcoin mining process is energy intensive, which can hamper the much-desired ecological balance. Given that the persistence of high levels of energy consumption of Bitcoin could have permanent policy implications, we examine the presence of long memory in the daily data of the Bitcoin Energy Consumption Index (BECI) (BECI upper bound, BECI lower bound, and BECI average) covering the period 25 February 2017 to 25 January 2022. Employing fractionally integrated GARCH (FIGARCH) and multifractal detrended fluctuation analysis (MFDFA) models to estimate the order of fractional integrating parameter and compute the Hurst exponent, which measures long memory, this study shows that distant series observations are strongly autocorrelated and long memory exists in most cases, although mean-reversion is observed at the first difference of the data series. Such evidence for the profound presence of long memory suggests the suitability of applying permanent policies regarding the use of alternate energy for mining; otherwise, transitory policy would quickly become obsolete. We also suggest the replacement of ‘proof-of-work’ with ‘proof-of-space’ or ‘proof-of-stake’, although with a trade-off (possible security breach) to reduce the carbon footprint, the implementation of direct tax on mining volume, or the mandatory use of carbon credits to restrict the environmental damage.     

The impact of intentional interference on the performances of ML detector in MIMO systems

Here we address the problem of performing the resilience of Multiple Input Multiple Output (MIMO) architecture against intentional and unintentional interferences. We investigate the performance of a non-linear receiver based on the Maximum Likelihood (ML) detector in MIMO systems over Gaussian fading channels in the presence of interfering signals. Using the properties of the Gaussian matrix, a finite expression of the Probability Density Function (PDF) for the Signal to Interference plus Noise Ratio (SINR) is obtained as a function of the brute jammer power budget and the number of affected antennas. By considering a particular closed-form of intelligent jamming strategies against MIMO architecture presented in the literature, approximated upper limits of the Bit Error Rate (BER) are performed under different jamming scenarios depending on the Channel State Information (CSI) availability. These results enable us to characterize the consequences of such conflicting attacks on the quality of the legitimate link. Furthermore, extensive simulations are carried out to justify the performance of the ML detector and validate the obtained results.     

Error Exponents and α-Mutual Information

Over the last six decades, the representation of error exponent functions for data transmission through noisy channels at rates below capacity has seen three distinct approaches: (1) Through Gallager’s E0 functions (with and without cost constraints); (2) large deviations form, in terms of conditional relative entropy and mutual information; (3) through the α-mutual information and the Augustin–Csiszár mutual information of order α derived from the Rényi divergence. While a fairly complete picture has emerged in the absence of cost constraints, there have remained gaps in the interrelationships between the three approaches in the general case of cost-constrained encoding. Furthermore, no systematic approach has been proposed to solve the attendant optimization problems by exploiting the specific structure of the information functions. This paper closes those gaps and proposes a simple method to maximize Augustin–Csiszár mutual information of order α under cost constraints by means of the maximization of the α-mutual information subject to an exponential average constraint.     

On the SINR statistics of a VFDM cognitive spectrum sharing system

An analytical precise approximation of the SINR statistics of the two-tier Vandermonde-subspace frequency division multiplexing (VFDM) cognitive spectrum sharing systems over frequency-selective Rayleigh fading channels is presented. It is shown that the gamma distribution provides the best fitting accuracy and that its use leads to simple, yet accurate, closed-form expressions for evaluating the ergodic capacity (EC) and average bit error probability (ABEP) performance of such systems. In deriving these expressions, the parameters of the gamma distribution have been obtained for various operating conditions of the considered VFDM system using distribution fitting. Furthermore, regression analysis has been used to obtain approximate analytical expressions for these parameters in relation to the system operating parameters. Performance evaluation results, obtained for various system implementations, including the standardized IEEE 802.11 and 3GPP LTE, are presented to demonstrate the validity of the proposed methodology. Its accuracy has been verified by means of computer simulations.     

Space Division Multiple Access in MIMO Systems with Parallel Data Transmission

We study multiple-input multiple-output (MIMO) cellular communication systems with antenna arrays at both link ends and parallel channels for data transmission. These channels (the so-called eigenchannels) are formed with the help of adaptive transmitting and receiving beamformer processors matched with a random fading environment. To increase the capacity of MIMO systems, we propose a space-division multiple-access (SDMA) method, which does not require estimation of signal-arrival directions and is based on orthogonalization of the parallel channels of all users. We find the signal-to-noise ratios at the eigenchannel outputs and the total capacity of a MIMO system in the case of simultaneous servicing of an arbitrary number of users. We present numerical results for the case of Rayleigh fading of signals, which confirm the high effectiveness of the proposed SDMA method.     

Shannon information capacity of time reversal wideband multiple-input multiple-output system based on correlated statistical channels

Utilizing channel reciprocity, time reversal(TR) technique increases the signal-to-noise ratio(SNR) at the receiver with very low transmitter complexity in complex multipath environment. Present research works about TR multiple-input multiple-output(MIMO) communication all focus on the system implementation and network building. The aim of this work is to analyze the influence of antenna coupling on the capacity of wideband TR MIMO system, which is a realistic question in designing a practical communication system. It turns out that antenna coupling stabilizes the capacity in a small variation range with statistical wideband channel response. Meanwhile, antenna coupling only causes a slight detriment to the channel capacity in a wideband TR MIMO system. Comparatively, uncorrelated stochastic channels without coupling exhibit a wider range of random capacity distribution which greatly depends on the statistical channel. The conclusions drawn from information difference entropy theory provide a guideline for designing better high-performance wideband TR MIMO communication systems.     

Improved Chernoff Bound of Gaussian Q-function with ABC algorithm and its QAM applications to DB SC and MRC systems over Beaulieu–Xie channels

In this study, we propose an improved upper bound for the Gaussian Q function by using artificial bee colony algorithm. Then, we investigate the performance of the dual-branch (DB) selection combining (SC) and maximal ratio combining (MRC) systems over the Beaulieu–Xie fading channels. The probability density functions of the instantaneous signal to noise ratio for the considered systems are obtained. Employing the proposed upper bound, we derive closed-form expressions of the error probability for the quadrature amplitude modulation (QAM) techniques such as rectangular QAM (RQAM), cross QAM (XQAM), and hexagonal QAM (HQAM). Furthermore, the asymptotic error probability expressions for the DB SC system are also obtained to simplify the analyses. The effects of some key parameters in the systems are shown in the results. Comparisons of the different modulation types and the different upper bound approaches for the Gaussian Q function are presented. Finally, it has been shown that the upper bound approximation presented in this study can be widely used for many communication applications.     

On achievable rate of massive MIMO multiple access channels via virtual representation

This paper investigates the uplink achievable rates of massive multiple-input multiple-output (MIMO) systems in correlated fading channels via virtual representation. The fast fading MIMO channel matrix is assumed to have a Rayleigh-distributed random component with variance profile. Under the minimum mean-squared error receiver employed, we first derive the first and second asymptotic moments of signal-to-interference-plus-noise ratio (SINR). Then, we propose that the probability distribution function of SINR, which can be well approximated by a Gamma distribution. Finally, we derive a lower bound on the SINR and approximation of achievable rate. Numerical results demonstrate that both the lower bound on the SINR and the approximated rate apply for a finite number of antennas and remain tight.     

MIMO量子信道的空间自由度研究

量子通信是一个量子密钥分发过程,目前采用的通信技术严重制约了量子密钥分发的比特率.将多输入多输出（MIMO）技术应用于量子通信系统,提高量子密钥分发的比特率,促进量子通信向高速大容量发展.然而,量子场本身不可避免地存在量子噪声约束容量的增长,限制了可利用空间资源,即空间自由度.文中采用光子场的量子化和满足Schrdinger方程条件的电磁场波动方程推导出MIMO量子信道的空间自由度上限,为开发稳健的MIMO量子通信空时处理算法和优化设计高性能MIMO量子通信系统提供理论基础和技术支持. 关键词： 多输入多输出 量子密钥分发 Schrdinger方程 光子场的量子化     

Data detection based on matrix decomposition for massive MIMO systems in realistic channel scenarios

Massive multiple-input multiple-output (MIMO) is a key technology for modern wireless communication systems. In massive MIMO receivers, data detection is a computationally expensive task. In this paper, we explore the performance and the computational complexity of matrix decomposition based detectors in realistic channel scenarios for different massive MIMO configurations. In addition, data detectors based on decomposition algorithms are compared to the approximate-inversion detection (AID) methods. It is shown that the alternating-direction-method-of-multipliers-based-Infinity-Norm (ADMIN) detection is promising in realistic channel environment and the performance is stable even when the ratio of the base-station (BS) antenna elements to the number of users is small. In addition, this paper studies the performance of several detectors in imperfect channel state information (CSI) and correlated channels. Our work provides valuable insights for massive MIMO systems and very large-scale integration (VLSI) designers to select the appropriate massive MIMO detector based on their specifications.     

Spherical-Symmetry and Spin Effects on the Uncertainty Measures of Multidimensional Quantum Systems with Central Potentials

The spreading of the stationary states of the multidimensional single-particle systems with a central potential is quantified by means of Heisenberg-like measures (radial and logarithmic expectation values) and entropy-like quantities (Fisher, Shannon, Rényi) of position and momentum probability densities. Since the potential is assumed to be analytically unknown, these dispersion and information-theoretical measures are given by means of inequality-type relations which are explicitly shown to depend on dimensionality and state’s angular hyperquantum numbers. The spherical-symmetry and spin effects on these spreading properties are obtained by use of various integral inequalities (Daubechies–Thakkar, Lieb–Thirring, Redheffer–Weyl, ...) and a variational approach based on the extremization of entropy-like measures. Emphasis is placed on the uncertainty relations, upon which the essential reason of the probabilistic theory of quantum systems relies.     

Effectiveness of Space-Division Multiple-Access in MIMO Communication Systems with Parallel Data Transmission

We consider multiple-input multiple-output (MIMO) cellular communication systems with antenna arrays at both link ends and data transmission via parallel eigenchannels matched with a random spatial channel. We analyze the effectiveness of the space-division multiple-access (SDMA) method, which does not require estimation of signal-arrival directions and is based on orthogonalization of the parallel channels of all users. We obtained approximate analytical expressions for the mean ratio of the signal power to the noise power and the MIMO system capacity, which are derived for the case of Rayleigh fading of signals. Although the obtained formulas are much simpler than the exact ones, they ensure high accuracy for an arbitrary number of transmitting and receiving antennas and an arbitrary power of transmitter. Our results demonstrate the high effectiveness of the proposed SDMA method.     

Robust Beamforming Based on Graph Attention Networks for IRS-Assisted Satellite IoT Communications

Satellite communication is expected to play a vital role in realizing Internet of Remote Things (IoRT) applications. This article considers an intelligent reflecting surface (IRS)-assisted downlink low Earth orbit (LEO) satellite communication network, where IRS provides additional reflective links to enhance the intended signal power. We aim to maximize the sum-rate of all the terrestrial users by jointly optimizing the satellite’s precoding matrix and IRS’s phase shifts. However, it is difficult to directly acquire the instantaneous channel state information (CSI) and optimal phase shifts of IRS due to the high mobility of LEO and the passive nature of reflective elements. Moreover, most conventional solution algorithms suffer from high computational complexity and are not applicable to these dynamic scenarios. A robust beamforming design based on graph attention networks (RBF-GAT) is proposed to establish a direct mapping from the received pilots and dynamic network topology to the satellite and IRS’s beamforming, which is trained offline using the unsupervised learning approach. The simulation results corroborate that the proposed RBF-GAT approach can achieve more than 95% of the performance provided by the upper bound with low complexity.