Correlated Rician Fading Channels Research Articles

On the Performance of RIS-Aided CF-IoE-SWIPT Network Over Correlated Rician Fading Channels

On the Performance of RIS-Aided CF-IoE-SWIPT Network Over Correlated Rician Fading Channels

On the Performance of MMSE Channel Estimation in Massive MIMO Systems over Spatially Correlated Rician Fading Channels

Massive multiple-input-multiple-output (M-MIMO) offers remarkable advantages in terms of spectral, energy, and hardware efficiency for future wireless systems. However, its performance relies on the accuracy of channel state information (CSI) available at the transceivers. This makes channel estimation pivotal in the context of M-MIMO systems. Prior research has focused on evaluating channel estimation methods under the assumption of spatially uncorrelated fading channel models. In this study, we evaluate the performance of the minimum-mean-square-error (MMSE) estimator in terms of the normalized mean square error (NMSE) in the uplink of M-MIMO systems over spatially correlated Rician fading. The NMSE allows for easy comparison of different M-MIMO configurations, serving as a relative performance indicator. Besides, it is an advantageous metric due to its normalization, scale invariance, and consistent performance indication across diverse scenarios. In the system model, we assume imperfections in channel estimation and that the random angles in the correlation model follow a Gaussian distribution. For this scenario, we derive an accurate closed-form expression for calculating the NMSE, which is validated via Monte-Carlo simulations. Our numerical results reveal that as the Rician K-factor decreases, approaching Rayleigh fading conditions, the NMSE improves. Additionally, spatial correlation and a reduction in the antenna array interelement spacing lead to a reduction in NMSE, further enhancing the overall system performance.

Performance Analysis of Cell-Free Massive MIMO-URLLC Systems Over Correlated Rician Fading Channels with Phase Shifts

Performance Analysis of Cell-Free Massive MIMO-URLLC Systems Over Correlated Rician Fading Channels with Phase Shifts

Statistical CSI Aided MIMO-NOMA Transmission in Correlated Rician Fading Channels

Statistical CSI Aided MIMO-NOMA Transmission in Correlated Rician Fading Channels

Double RIS-Assisted MIMO Systems Over Spatially Correlated Rician Fading Channels and Finite Scatterers

This paper investigates double RIS-assisted MIMO communication systems over Rician fading channels with finite scatterers, spatial correlation, and the existence of a double-scattering link between the transceiver. First, the statistical information is driven in closed form for the aggregated channels, unveiling various influences of the system and environment on the average channel power gains. Next, we study two active and passive beamforming designs corresponding to two objectives. The first problem maximizes channel capacity by jointly optimizing the active precoding and combining matrices at the transceivers and passive beamforming at the double RISs subject to the transmitting power constraint. In order to tackle the inherently non-convex issue, we propose an efficient alternating optimization algorithm (AO) based on the alternating direction method of multipliers (ADMM). The second problem enhances communication reliability by jointly training the encoder and decoder at the transceivers and the phase shifters at the RISs. Each neural network representing a system entity in an end-to-end learning framework is proposed to minimize the symbol error rate of the detected symbols by controlling the transceiver and the RISs’ phase shifts. Numerical results verify our analysis and demonstrate the superior improvements of phase shift designs to boost system performance.

Scalable Cell-Free Massive MIMO Systems With Finite Resolution ADCs/DACs Over Spatially Correlated Rician Fading Channels

Scalable Cell-Free Massive MIMO Systems With Finite Resolution ADCs/DACs Over Spatially Correlated Rician Fading Channels

Two-Timescale Design for Reconfigurable Intelligent Surface-Aided Massive MIMO Systems With Imperfect CSI

This paper investigates the two-timescale transmission scheme for reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems, where the beamforming at the base station (BS) is adapted to the rapidly-changing instantaneous channel state information (CSI), while the nearly-passive beamforming at the RIS is adapted to the slowly-changing statistical CSI. Specifically, we first consider a system model with spatially independent Rician fading channels, which leads to tractable expressions and offers analytical insights on the power scaling laws and on the impact of various system parameters. Then, we analyze a more general system model with spatially correlated Rician fading channels and consider the impact of electromagnetic interference (EMI) caused by any uncontrollable sources present in the considered environment. For both case studies, we apply the linear minimum mean square error (LMMSE) estimator to estimate the aggregated channel from the users to the BS, utilize the low-complexity maximal ratio combining (MRC) detector, and derive a closed-form expression for a lower bound of the achievable rate. Besides, an accelerated gradient ascent-based algorithm is proposed for solving the minimum user rate maximization problem. Numerical results show that, in the considered setup, the spatially independent model without EMI is sufficiently accurate when the inter-distance of the RIS elements is sufficiently large and the EMI is mild. In the presence of spatial correlation, we show that an RIS can better tailor the wireless environment. Furthermore, it is shown that deploying an RIS in a massive MIMO network brings significant gains when the RIS is deployed close to the cell-edge users. On the other hand, the gains obtained by the users distributed over a large area are shown to be modest.

Optimal Rotated M-PSK Signaling for Multi-User Receive Diversity System Over Correlated Rician Fading Channels

In this letter, a two-user receive diversity non-orthogonal multiple-access (NOMA) wireless communication system is considered with the transmitter utilizing a rotated <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -ary phase-shift keying ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -PSK) modulation for data modulation over correlated Rician fading channels. A maximum ratio combining scheme followed by an optimum maximum-likelihood rule is employed for received data detection at each user end. Further, a simple separation scheme is proposed to eliminate the use of successive interference cancellation at the receiver end of the NOMA system. The receiver structure is utilized to derive a closed-form expression for the symbol error probability which is minimized by obtaining the optimal rotation angle of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -PSK constellation. The variations of the optimal rotation angle with system parameters are studied by numerical results which lead to novel modulation schemes for the considered system.

Multi-Pair D2D Communications Aided by an Active RIS Over Spatially Correlated Channels With Phase Noise

This paper investigates a multi-pair device-to-device (D2D) communication system aided by an active reconfigurable intelligent surface (RIS) with phase noise and direct link. The approximate closed-form expression of the ergodic sum rate is derived over spatially correlated Rician fading channels with statistical channel state information (CSI). When the Rician factors go to infinity, the asymptotic expressions of the ergodic sum rates are presented to give insights in poor scattering environment. The power scaling law for the special case of a single D2D pair is presented without phase noise under uncorrelated Rician fading condition. Then, to solve the ergodic sum rate maximization problem, a method based on genetic algorithm (GA) is proposed for joint power control and discrete phase shifts optimization. Simulation results verify the accuracy of our derivations, and also show that the active RIS outperforms the passive RIS.

Performance Analysis and Optimization of NOMA-Based Cell-Free Massive MIMO for IoT

This article investigates the performance of nonorthogonal multiple access (NOMA)-based cell-free massive multiple-input–multiple-output (mMIMO) for the Internet of Things (IoT) considering spatially correlated Rician fading channels. The exact closed form of downlink spectral efficiency (SE) and energy efficiency expressions is derived with three estimators and the maximum ratio transmission by taking the impacts of imperfect successive interference cancellation and pilot contamination into account. Subsequently, the performance of a local-MMSE precoder with the three aforementioned estimators is analyzed. Then, a large-scale fading-based user pairing scheme is proposed to further analyze the system SE. Besides, we formulate the optimum power control design as a max–min problem and a computational efficient suboptimal algorithm is proposed based on the successive convex approximation. Furthermore, our results reveal that the magnitude of the spatial correlation negligibly effects the SE in spatially correlated Rician fading channels. Then, numerical results confirm the positive effect of the proposed power control scheme. Also, our results further illustrate that NOMA-based cell-free mMIMO for IoT provides significant performance gain compared with its counterpart deploying conventional orthogonal multiple-access schemes.

Proximity co-located massive MIMO systems over correlated Rician fading channels

This paper considers the downlink transmission in a single-cell proximity co-located massive MIMO (PC-MIMO) system, in which antennas of the base station (BS) are divided into multiple antenna units (AUs) and these AUs are connected to a backhaul processor unit (BPU). The AUs are geographically deployed very close to the BPU which controls them to serve all users in the cell. Considering correlated Rician fading channels, we derive a closed-form expression of the sum spectral efficiency under the maximum-ratio transmission and statistical channel state information at each user. Based on the obtained expression, it is shown that as the number of AUs approaches infinity, the sum spectral efficiency approaches a constant value. Furthermore, we also give a closed-form expression of the average sum spectral efficiency when the arrival angles to the users seen from the AUs are varying. For the cases of correlated Rayleigh fading and uncorrelated Rician fading, we show how to find the number of antennas at each AU to maximize the average sum spectral efficiency when the total number of antennas at the BS is fixed.

SWIPT-Enhanced Cell-Free Massive MIMO Networks

Simultaneous wireless information and power transfer (SWIPT) has been advocated as a highly promising technology to provide near- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">perpetual</i> operation to low-powered wireless devices in Internet-of-Things (IoT)-based wireless networks. In this paper, a SWIPT-enhanced cell-free massive MIMO network is proposed. In such a network, a large set of spatially distributed access points (APs) interconnected via a central processing unit (CPU) can collaboratively serve a large number of both energy harvesting mobile stations (MSs) (requiring wireless energy transfer) and conventional MSs (not requiring wireless energy transfer) on the same time-frequency resources. We consider spatially correlated Rician fading channels and the use of different precoding schemes that are based on different channel estimators differing on the assumed knowledge of the line-of-sight component. Mathematically manageable expressions are derived for the harvested energy during the downlink (DL) energy harvesting phase and the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">achievable</i> spectral and energy efficiencies during the uplink (UL) payload transmission phase. A coupled UL/DL optimization problem is formulated aiming at finding the power control coefficients that maximize the minimum of the weighted achievable UL signal-to-interference-plus-noise ratios (SINRs) of all MSs. Extensive numerical results are presented that serve to highlight the existing trade-offs among the achievable spectral and energy efficiencies, the harvested energy, the energy dedicated to UL pilot transmission or the system configuration.

Hardware-Impaired Rician-Faded Massive MIMO FD Relay: Analysis and Optimization

We consider two-way multi-pair full-duplex (FD) massive multi-input-multi-output (mMIMO) relaying, where multiple FD user-pairs exchange information via a shared FD relay. We derive a closed-form spectral efficiency (SE) lower bound by considering i) dynamic analog-to-digital converter (ADC) and digital-to-analog converter (DAC) architecture at the relay, where each antenna is connected to a different resolution ADC/DAC; and ii) low cost radio frequency (RF) chains at the relay and users. The dynamic ADC/DAC architecture allows us to judiciously choose ADC/DAC resolution to achieve high SE with low power consumption. We unlike, the most existing mMIMO relaying works, consider a correlated Rician fading channel, which captures realistic line-of-sight (LoS) signal propagation and spatial correlation between closely-packed relay antennas. We maximize the derived SE lower bound by first proposing its valid surrogate function, and then by using minorization-maximization approach. We investigate the impact of ADC/DAC and RF impairments, and show that the proposed optimization allows reduction in ADC/DAC resolution without compromising the SE.

Uplink Performance of Cell-Free Massive MIMO Over Spatially Correlated Rician Fading Channels

We consider a practical cell-free massive multiple-input-multiple-output (MIMO) system with multi-antenna access points (APs) and spatially correlated Rician fading channels. The significant phase-shift of the line-of-sight component induced by the user equipment movement is modeled randomly. Furthermore, we investigate the uplink spectral efficiency (SE) with maximum ratio (MR)/local minimum mean squared error (L-MMSE) combining and optimal large-scale fading decoding based on the phase-aware MMSE, phase-aware element-wise MMSE and linear MMSE (LMMSE) estimators. Then new closed-form SE expressions with MR combining are derived. Numerical results validate our derived expressions and show that the SE benefits from the spatial correlation. It is important to observe that the performance gap between L-MMSE and MR combining increases with the number of antennas per AP and the SE of the LMMSE estimator is lower than that of other estimators due to the lack of phase-shifts knowledge.

BER analysis of MIMO ZF receiver with imperfect channel estimation under correlated Rician fading channel

Massive MIMO systems operating in spatial multiplexing mode provide greater capacities. Zero Forcing (ZF) is one of the simple detection techniques used in the massive MIMO systems to recover the transmitted data streams at the receiver. In this paper, a generalized expression for the post-detection Signal to Noise Ratio (SNR) of the substream is derived by accounting the spatial correlation and channel estimation error. Further the Average Bit Error Rate (ABER) of ZF receiver for M-Phase Shift Keying (PSK) and M-Quadrature Amplitude Modulation (QAM) is evaluated from the derived post-detection SNR. Also, a closed-form approximation for the ABER of ZF receiver under transmit correlated Rician fading channel with channel estimation error is derived. From the simulation results, it is quite interesting to notice that for equal number of transmitting and receiving antennas and at higher values of average received SNR (Es/N0), the ABER of ZF receiver becomes independent of the receiver correlation. Further, it is also observed that the value of Es/N0 at which the ABER with full spatial correlation converges to the ABER with transmitter correlation varies with respect to the correlation coefficient (ρt,ρr) and Mean Square estimation Error (MSE) (σε2), while keeping the other parameters constant.

Performance Analysis of Large Intelligent Surfaces (LISs): Asymptotic Data Rate and Channel Hardening Effects

The concept of a large intelligent surface (LIS) has recently emerged as a promising wireless communication paradigm that can exploit the entire surface of man-made structures for transmitting and receiving information. An LIS is expected to go beyond massive multiple-input multiple-output (MIMO) system, insofar as the desired channel can be modeled as a perfect line-of-sight. To understand the fundamental performance benefits, it is imperative to analyze its achievable data rate, under practical LIS environments and limitations. In this paper, an asymptotic analysis of the uplink data rate in an LIS-based large antenna-array system is presented. In particular, the asymptotic LIS rate is derived in a practical wireless environment where the estimated channel on LIS is subject to estimation errors, interference channels are spatially correlated Rician fading channels, and the LIS experiences hardware impairments. Moreover, the occurrence of the channel hardening effect is analyzed and the performance bound is asymptotically derived for the considered LIS system. The analytical asymptotic results are then shown to be in close agreement with the exact mutual information as the number of antennas and devices increase without bounds. Moreover, the derived ergodic rates show that hardware impairments, noise, and interference from estimation errors and the non-line-of-sight path become negligible as the number of antennas increases. Simulation results show that an LIS can achieve a performance that is comparable to conventional massive MIMO with improved reliability and a significantly reduced area for antenna deployment.

Channel Hardening in Cell-Free and User-Centric Massive MIMO Networks With Spatially Correlated Ricean Fading

The irruption of the cell-free (CF) massive multiple-input multiple-output (MIMO) network topology has meant taking one step further the concept of massive MIMO as a means to provide uniform service in large coverage areas. A key property of massive MIMO networks is channel hardening, by which the channel becomes deterministic when the number of antennas grows large enough relative to the number of serviced users, easing the signal processing and boosting the performance of simple precoders. However, in CF massive MIMO, the fulfillment of this condition depends on several aspects that are not considered in classical massive MIMO systems. In this work, we address the presence of channel hardening in both CF massive MIMO and the recently appeared user-centric (UC) approach, under a spatially correlated Ricean fading channel using distributed and cooperative precoding and combining schemes and different power control strategies for both the downlink (DL) and uplink (UL) segments. We show that the line-of-sight (LOS) component, spatially correlated antennas and UC schemes have an impact on how the channel hardens. In addition, we examine the existent gap between the estimated achievable rate and the true network performance when channel hardening is compromised. Exact closed-form expressions for both the hardening metric and achievable DL/UL rates are given as well.

On the Energy Efficiency of Multi-Cell Massive MIMO With Beamforming Training

This paper is concerned with a multi-cell downlink (DL) massive multiple-input multiple-output (MIMO) system operating over spatially correlated Rician fading channels. We not only consider estimating channel state information (CSI) at the base station (BS), but also adopt beamforming training (BT) to obtain CSI at the users. With maximum-ratio transmission (MRT) or zero-forcing (ZF) employed at the BS to process the transmit signals, the paper derives closed-form expressions of the sum spectral efficiency for both cases: with and without BT. Based on the obtained closed-form expressions, we investigate the effect of the DL pilot length on the system performance for MRT and ZF precoding and with or without BT. Moreover, when the DL pilot length falls within different ranges, we find out whether using BT leads to better system performance. To address the energy efficiency (EE) maximization problem under the constraints of a given sum spectral efficiency and a maximum total DL transmit power, we transform the problem into a geometric program (GP), which can be solved more efficiently. In particular, we develop one iterative power allocation algorithm for the system with BT scheme. Simulation and numerical results demonstrate that the proposed power allocation algorithm can improve the system EE. Numerical results also show that when the BS uses MRT precoding, the sum spectral efficiency in the high signal-to-noise ratio (SNR) region is much improved with BT.

Low-Cost Design of Massive Access for Cellular Internet of Things

In this paper, we investigate the issue of low-cost design of massive access for cellular internet of things (IoT) over spatially correlated Rician fading channels. Specifically, by exploiting a low-overhead transmission protocol, a base station (BS) equipped with a large-scale antenna array and low-resolution analog-to-digital converters (ADCs) is deployed to serve a massive number of IoT devices with low-complexity successive interference cancellation (SIC) receivers. We first analyze the impacts of the low-cost design on the system performance and derive closed-form expressions for uplink and downlink spectral efficiencies of the cellular IoT. Then, for alleviating the negative impacts of the low-cost design, we propose an algorithm allocating the time for channel estimation, uplink data transmission, and downlink data transmission in a data frame. Finally, extensive simulation results confirm the effectiveness of the proposed low-cost design for the cellular IoT.

Massive MIMO With Spatially Correlated Rician Fading Channels

This paper considers multi-cell Massive MIMO (multiple-input multiple-output) systems where the channels are spatially correlated Rician fading. The channel model is composed of a deterministic line-of-sight (LoS) path and a stochastic non-line-of-sight (NLoS) component describing a practical spatially correlated multipath environment. We derive the statistical properties of the minimum mean squared error (MMSE), element-wise MMSE (EW-MMSE), and least-square (LS) channel estimates for this model. Using these estimates for maximum ratio (MR) combining and precoding, rigorous closed-form uplink (UL) and downlink (DL) spectral efficiency (SE) expressions are derived and analyzed. The asymptotic SE behavior when using the different channel estimators are also analyzed. Numerical results show that the SE is higher when using the MMSE estimator than the other estimators, and the performance gap increases with the number of antennas.