Imperfect Channel State Information Research Articles

Outage Performance of Underlay CR-NOMA-based D2D Communications under Imperfect CSI and SIC

Background: Non-orthogonal multiple access (NOMA) is a promising technique for improving wireless communication performance in the future. In addition to NOMA, cognitive radio (CR) is another technology that can address the issue of limited spectrum availability and meet the increasing demands for wireless connectivity. Methods: This paper focuses on investigating underlay CR-NOMA-based D2D communications. The study assumes a decode-and-forward (DF) mode used in the system, where nearby users (D1, D2) act as helper users to assist distant users (D3, D4). The paper derives the closed-form expressions for outage probability (OP) and throughput at the far users in three scenarios: (1) Perfect successive interference cancellation (SIC) and perfect channel state information (CSI), (2) Imperfect CSI, and (3) Imperfect SIC. Results: In CR-NOMA mode, the results indicate that the performance of user D4 was better than user D3. Additionally, the OP performance of distant users employing CR-NOMA mode surpasses that of users using CR-OMA mode. The optimal power allocation (PA) values are investigated. Conclusion: The presence of imperfect CSI and SIC has an unfavorable influence on the outage performance. Monte Carlo simulations are used to validate the derived analytical expressions.

Secure and Reliable IoT Communications in Underlay CRN With Imperfect CSI

Secure and Reliable IoT Communications in Underlay CRN With Imperfect CSI

Performance Prediction of Power Beacon-Aided Wireless Sensor-Powered Non-Orthogonal Multiple-Access Internet-of-Things Networks Under Imperfect Channel State Information

In this paper, we investigate a novel power beacon (PB)-aided wireless sensor-powered non-orthogonal multiple-access (NOMA) Internet-of-Things (IoT) network under imperfect channel state information (CSI). Furthermore, the exact expression outage probability (OP) of two IoT users is derived to analyze the performance of the considered network. To give further insight, the expression asymptotic OP and diversity order are also expressed when the transmit power at the PB goes to infinity. Furthermore, a deep neural network (DNN) framework is proposed to concurrently forecast IoT users’ OP in relation to real-time setups for IoT users. Additionally, when compared to the traditional analysis, our created DNN shows the shortest run-time prediction, and the outcomes predicted by the DNN model almost match those of the simulation. In addition, numerical results validate our analysis, simulation, and prediction through a Monte Carlo Simulation. Furthermore, the results show the impact of the main parameter on our proposed system. Finally, these findings show that NOMA performs better than the conventional orthogonal multiple-access (OMA) techniques.

Developing Laboratory Experiments to teach Undergraduate Engineering Students Multi-User Massive MIMO Technology for 5G Cellular Networks

An effective method of facilitating student learning in a laboratory environment is “practice by doing”. The study of modules related to signal-processing for digital communications requires deep mathematical and theoretical foundations but the practice goal is not really emphasized in the undergraduate curriculum at the University of Mauritius. This causes the students to lose interest in the corresponding modules resulting in high rate of failures. In this work, we propose to develop laboratory experiments with a view to bridge the gap between theoretical and practical aspects in the field of Massive Multiple-Input Multiple-Output (MIMO) systems for 5G cellular networks. Various laboratory scenarios are set up that consider a Maximum Ratio Combining (MRC) receiver in the uplink with an uncorrelated Rayleigh fading channel. Moreover, from a signal processing perspective to enhance the student’s understanding, we analyze the efficiency and error performance of Massive MIMO systems with MPSK and MQAM modulation schemes as well as perfect and imperfect channel estimates. The leading industry software package MATLAB R2022 is used to develop all laboratory experiments and the codes are elaborated in this analysis. Data collected from the experiments are used to generate spectral efficiency and error performance curves which can be used for future research. The findings underscore the significance of accounting for both scenarios and illuminate promising avenues for future research in the realm of massive MIMO education and learning. The assimilation of MATLAB® flowcharts for each MRC receiver, MPSK, and MQAM with perfect and imperfect Channel State Information (CSI) adds further depth to the study, ensuring a comprehensive understanding of the intricacies of massive MIMO systems. Ultimately, this contribution helps in the nurturing of expertise such that future generations of wireless communication pioneers can be inspired.

Outdoor-to-Indoor mmWave Relaying with Massive MIMO: Impact of Imperfect Channel Estimation

Assuming incomplete knowledge of the channel state information (CSI), we investigate two scenarios involving millimeter wave (mmWave) relaying to support outdoor-to-indoor communications. We proceed to derive the average signal-to-noise ratio (SNR) expressions for two relaying scenarios and quantify the asymptotic SNR. The performance of the two relaying scenarios is evaluated using the outage probability—for which we have derived closed-form equations—the end-to-end channel capacity, and the energy efficiency. The obtained results are compared with those derived assuming complete knowledge of the CSI. The effect of the imperfect CSI is therefore assessed in relation to the reference of perfect CSI. In these scenarios, an outside base station (BS) in an urban cellular network serves several indoor users. In the context of a two-hop full-duplex (FD) relaying scheme, we initially suggest a method in which the base station (BS) utilizes zero-forcing (ZF) precoding, and we take into account the overall channel response. Furthermore, we make the assumption that the base station (BS) engages in precoding only depending on the response of the channel in the first hop; in this second design, the relay precodes (using the response of the second-hop channel), amplifies, and sends the signals. Both techniques utilize massive multiple-input–multiple-output (mMIMO) arrays to permit transmission. We also present Monte Carlo simulation results to assess the accuracy of our analytical results. Finally, the two systems are compared in terms of channel estimation and precoding complexity, the number of antennas, as well as the number of users. Practical deployment recommendations are formulated at the end of this work.

Over-the-Air Computation in OFDM Systems With Imperfect Channel State Information

Over-the-Air Computation in OFDM Systems With Imperfect Channel State Information

Impact of Hardware Impairment on the Joint Reconfigurable Intelligent Surface and Robust Transceiver Design in MU-MIMO System

Reconfigurable intelligent surface (RIS) is a revolutionary passive radio technique to facilitate capacity enhancement beyond the current massive multiple-input multiple-output (MIMO) transmission. However, the potential hardware impairment (HWI) of the RIS usually causes inevitable performance degradation and the amplification of imperfect CSI. These impacts still lack full investigation in the RIS-assisted wireless network. This paper developed a robust joint RIS and transceiver design algorithm to minimize the worst-case mean square error (MSE) of the received signal under the HWI effect and imperfect channel state information (CSI) in the RIS-assisted multi-user MIMO (MU-MIMO) wireless network. Specifically, since the proposed robust joint RIS and transceiver design problem yields non-convex characteristics under severe HWI, an iterative three-step convex algorithm is developed to approach the optimality by relaxation and convex transformation. Compared with the state-of-the-art baselines that ignore the HWI, the proposed robust algorithm inhibits the destruction of HWI while raising the worst-case MSE effectively in several numerical simulations. Moreover, due to the properties of the HWI, the performance loss is notable under the magnification of the number of reflected elements in the RIS-assisted MU-MIMO wireless network.

Optimizing beamforming in IoT-WET: A symbiotic-based approach under imperfect channel state information

This study delves into the energy optimization problem in low-power Internet of Things (IoT) networks utilizing wireless energy transfer (WET) technology. In such IoT systems, conventional optimization schemes relying on complete knowledge of channel state information (CSI) are often irrelevant for practical implementation due to their high complexity and energy consumption. To address this challenge and enhance the fairness of energy harvesting among IoT devices with imperfect CSI, we propose a novel beamforming design based on the symbiotic organisms search (SOS) algorithm. Through comprehensive numerical analysis, we demonstrate the effectiveness of our proposed scheme in terms of computational complexity, convergence speed, and energy harvested at each IoT device. The results highlight the significant advantages of our approach compared to conventional methods, paving the way for practical and efficient energy optimization in IoT networks.

Optimizing secure power allocation in massive MIMO systems with an eavesdropper under imperfect CSI conditions

Optimizing secure power allocation in massive MIMO systems with an eavesdropper under imperfect CSI conditions

A Hierarchical Network Management Strategy for Distributed CIIoT With Imperfect CSI

A Hierarchical Network Management Strategy for Distributed CIIoT With Imperfect CSI

Robust Resource Allocation for Symbiotic Radio Systems With Imperfect CSI and Eavesdropper

Robust Resource Allocation for Symbiotic Radio Systems With Imperfect CSI and Eavesdropper

Energy-Efficient Resource Allocation for IRS-Assisted SWIPT-Enabled D2D Communications With Imperfect CSI

Energy-Efficient Resource Allocation for IRS-Assisted SWIPT-Enabled D2D Communications With Imperfect CSI

Analysis of Outage Probability for Massive MIMO Systems Under Multi-Cell and Imperfect CSI Environments

Analysis of Outage Probability for Massive MIMO Systems Under Multi-Cell and Imperfect CSI Environments

Cooperative NOMA in cognitive radio networks: A study on imperfect CSI, SIC and hardware impairments over Nakagami-m fading channel

This paper proposes a cooperative uplink–downlink non orthogonal multiple access (NOMA) in an overlay cognitive radio network (CR). We examine the impact of imperfect channel state information (impCSI), imperfect successive interference cancellation (impSIC) and residual hardware impairments (RHI) on the cooperative cognitive radio network over Nakagami-m fading channels. We derive the exact outage probabilities of primary user (PU) and multicast secondary users (SUs) under perfect/imperfect conditions for fixed and adaptive power allocations. We show that the use of multiple relays enhances the diversity order, but with fixed power allocation in perfect/imperfect case and adaptive power allocation in imperfect case both suffer from an error floor, which reduces the diversity order to zero. On the other hand, the adaptive power allocation for the perfect case achieves full diversity gain. We validate the analytical results with Monte Carlo simulations and demonstrate the diversity gains of the considered schemes.

An integrative numerical method for evaluating Ergodic capacity of multi-user NOMA over faded channels with imperfect-CSI and SIC

With increased demand for the internet and the Internet of Things (IoT), future wireless communication networks are draw more attention to afford the massive connectivity, capacity, and extensive coverage requirements. Recently, multi-user (MU) NOMA was introduced as a potential technique to address these challenges. Owing to the wide applicability of MU-NOMA, precise expressions for Ergodic capacity under realistic scenarios are very much required to evaluate its performance. Hence, in this paper, we derive the ergodic capacity expressions for MU-NOMA for generalized fading channels. To achieve precision, we have taken imperfect-successive interference cancellation (SIC) and channel state information (CSI) into account. The impact of imperfect SIC and CSI and fading parameters is investigated over Nakagami-m, Rayleigh, and Rician fading channels. The proposed approach is valid for any type fading channels. The obtained expressions for the Ergodic capacity over various fading channels are validated through the simulation results.

Performance evaluation for multi-antenna UWOC-RF NOMA systems with imperfect CSI and SIC

Information transmission is easily affected by obstacles or other factors, which makes it challenging to achieve perfect channel state information (CSI) and successive interference cancellation (SIC) in practical applications. Therefore, in this paper, a dual-hop underwater wireless optical communication-radio frequency (UWOC-RF) system with non-orthogonal multiple access (NOMA) in the presence of both imprecise CSI and imperfect SIC is investigated. In particular, the underwater source sends a superimposed optical NOMA signal to a pair of land-based users via a decode-and-forward relay on the surface, which decodes the received signal and encodes it into the RF one before broadcasting it to the terrestrial users. Considering a scenario that both the land-based users are equipped with multiple antennas and adopt a maximal-ratio combining technique to deal with those multiple copies of received signals, we first format the expressions of probability density function, cumulative distribution function, and the p-th moment of the imperfect channel gain in the UWOC link. And then the analytical and asymptotic expressions for outage probability as well as the closed-form expression for average achievable rate of each user are obtained by utilizing the Meijer's-G and the Fox's-H functions. Finally, Monte-Carlo simulations are performed to validate the accuracy of those analytical expressions.

Analysis one‐bit DAC for MU massive MIMO downlink via efficient autoencoder based deep learning

AbstractMulti‐user (MU) massive multiple input multiple output (mMIMO) is considered a potential technology for fifth generation (5G) and sixth‐generation (6G) wireless systems. The presence of the antenna arrays at the base station level to communicate with the users or to serve tens of single antenna users leads to excessively high system costs and power consumption. The deployment 1‐bit digital‐to‐analogue converters (DACs) in the base station can solve these problems. This paper starts by presenting an analytical study centered on the effects of 1‐bit DACs on the system envisaged for a Rayleigh‐type fading channel. Compact‐form expressions are derived for the symbol error rate. Afterwards, an efficient end‐to‐end deep learning technique to compensate for the joint effect of 1‐bit DAC and imperfect channel state information in downlink mMIMO systems. Moreover, to improve the performance of the considered system, a DAC mixed architecture is proposed, where a number of antennas use 1 bit DACs while the others do not. The simulations results showed the improvement in transmission quality of the downlink of the MU‐mMIMO system in the presence of hardware imperfections using the considered end‐to‐end compensation technique.

Performance of Selective DF-Based Multiple Relayed NOMA System With Imperfect CSI and SIC Errors

Performance of Selective DF-Based Multiple Relayed NOMA System With Imperfect CSI and SIC Errors

Performance Analysis for Reconfigurable Intelligent Surface-aided Communication Systems with Energy Harvesting under Imperfect Nakagami-m Channel Information

Reconfigurable intelligent surface (RIS) can serve as a passive relay to maintain communication between a transceiver in severe scenarios of no direct link between them. In addition, harvesting energy from radio frequency (RF) signals can meliorate significantly energy efficiency. In this research, we propose RIS-aided communication systems with energy harvesting (RISwEH) which combine both RIS and RF energy harvesting to improve energy efficiency as well as communication reliability. To evaluate realistically and quickly the performance of the RISwEH, we propose the explicit formulas of the system throughput and the outage probability under the realistic scenario of Nakagami-m fading and imperfect channel state information (CSI). Moreover, we propose an optimization algorithm relied upon a Golden section search to attain the optimum value of the time splitting factor of energy harvester to obtain the best system performance. Various results corroborate the theoretical derivations, confirm the efficacy of the proposed optimization algorithm, and illustrate the influence of innumerable system settings on the system performance. Particularly, the imperfect CSI deteriorates considerably the system performance. Nonetheless, the performance of the RISwEH can be enhanced by accreting the quantity of the elements of the RIS as well as with the lower fading severity. Furthermore, the time splitting factor also impacts dramatically the outage performance of the RISwEH and its optimal value mitigates significantly the outage probability.

Error Performance of NOMA System With Outdated, Imperfect CSI, and RHI Over $\alpha-\mu$ Fading Channels

Error Performance of NOMA System With Outdated, Imperfect CSI, and RHI Over $\alpha-\mu$ Fading Channels