Article
Engineering, Electrical & Electronic
Italo Atzeni, Antti Tolli
Summary: This paper presents an analytical framework for channel estimation and data detection in massive multiple-input multiple-output uplink systems. Closed-form expressions for channel estimation mean squared error and estimated symbol statistics in data detection are derived. The analysis depends on key system parameters and provides a precise characterization of performance with 1-bit ADCs.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Liangyuan Xu, Cheng Qian, Feifei Gao, Wei Zhang, Shaodan Ma
Summary: The study focuses on the application of one-bit ADC/DAC in mmWave MIMO systems for UL/DL channel estimation and precoding. Proposed algorithms show advantages over existing techniques in terms of accuracy and computational complexity.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Bule Sun, Yiqing Zhou, Jinhong Yuan, Ya-Feng Liu, Lu Wang, Ling Liu
Summary: This paper investigates high order PSK signal transmission in 1-bit ADC massive MIMO systems, theoretically proving that arbitrary modulation order PSK signals can be recovered with a large number of antennas at the base station. The impact of pilot based channel estimation on high order PSK signal recovery is analyzed, leading to an optimized pilot sequence proposal for improved detection performance. Simulation results confirm the effectiveness of the proposed optimized pilot sequence in enhancing detection performance in both single-MS and multi-MS scenarios for 1-bit ADC massive MIMO systems.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Jinsung Park, Namyoon Lee, Song-Nam Hong, Yo-Seb Jeon
Summary: This letter presents a data detection method for MIMO systems with one-bit ADCs. The method learns the likelihood function of the system from training samples. A training data generation strategy is proposed, which labels a one-bit received signal based on channel-based detection. An EM algorithm is developed for accurate learning from noisy labels. Numerical results show that the method performs similarly to optimal maximum likelihood detection.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Weimin Du, Zujun Liu
Summary: Quantization allows for cheap and power-efficient implementation of massive MIMO using radio frequency front-ends, but it also introduces severe amplitude distortion. The spatial sigma - delta structure is a key method for recovering amplitude information from one-bit quantized signals. However, existing schemes like zero forcing or maximum ratio combination struggle to achieve the upper bound of spatial quantization noise reduction (DQNR), limiting distortion suppression. To address this issue, we propose random and accurate beam shaping schemes that exploit the large-scale antenna array more efficiently to recover amplitude information.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Qi Lin, Hong Shen, Chunming Zhao
Summary: This letter proposes a deep learning based linear precoder design to improve the performance of uplink multiuser multiple-input multiple-output (MU-MIMO) systems with one-bit analog-to-digital converters (ADCs). By optimizing the precoder at each user equipment (UE) using a Bussgang decomposition based linear minimum mean squared error (MMSE) receiver at the base station (BS), the system MSE can be further minimized. To efficiently address this problem, a deep neural network based approach is proposed by unfolding the developed projected gradient descent (PGD) algorithm and treating the step size in each PGD iteration as trainable network parameters. Simulation results show that the proposed network design outperforms the conventional PGD algorithm under both perfect and estimated channel state information (CSI) and achieves improvement with reduced online complexity.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Youzhi Xiong, Sanshan Sun, Li Liu, Zhongpei Zhang, Ning Wei
Summary: This paper focuses on a cell-free massive MIMO network with variable-resolution ADCs. The authors propose a quantization-aware channel estimator based on LMMSE theory, and investigate bit allocation problems for intra-AP and inter-AP scenarios to maximize channel estimation quality. The theoretical expressions of achievable uplink SE for MRC and MMSE combining are derived, and bit allocation problems for both single-user and multi-user scenarios are also explored. Simulation results confirm the correctness of the theoretical analyses and provide insights into the proposed bit allocation techniques.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Tae-Kyoung Kim, Yo-Seb Jeon, Moonsik Min
Summary: This study introduces a RL-based detection method using one-bit ADCs in time-varying massive MIMO channels. The learned likelihood probability may vary with the true likelihood probability due to channel variations, leading to performance degradation. A training length adaptation method is proposed to minimize the training length while ensuring detection performance, with the optimal length depending on the change in likelihood probability. Simulation results show that the proposed method significantly improves spectral efficiency compared to conventional methods.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Doaa Abdelhameed, Kenta Umebayashi, Italo Atzeni, Antti Tolli
Summary: This paper investigates the design of a transmitter and receiver for a single-user massive SIMO system with 1-bit ADCs at the base station, where higher-order modulation is used for data transmission. Linear least-squares estimation and maximum ratio combining are employed for channel estimation and signal detection. The study reveals that the conventional 16-QAM detector and square 16-QAM modulation are not adequate in the presence of 1-bit ADCs. Three novel symbol detectors and a redesigned 16-QAM modulation are proposed to improve the SER performance.
Article
Telecommunications
Ruizhe Wang, Hong Ren, Cunhua Pan, Jun Fang, Mianxiong Dong, Octavia A. Dobre
Summary: This study investigates the cascaded channel estimation for a mmWave massive MIMO system aided by a reconfigurable intelligent surface (RIS) with the base station equipped with few-bit analog-to-digital converters (ADCs). By introducing the Bayesian optimal inference framework and using the efficient bilinear generalized approximate message passing (BiG-AMP) algorithm, the proposed method accurately estimates the cascaded channel for the RIS-aided mmWave massive MIMO system with low-resolution ADCs.
IEEE COMMUNICATIONS LETTERS
(2023)
Article
Telecommunications
Ruizhe Wang, Hong Ren, Cunhua Pan, Jun Fang, Mianxiong Dong, Octavia A. Dobre
Summary: This letter investigates the cascaded channel estimation problem for a mmWave massive MIMO system aided by a reconfigurable intelligent surface (RIS) with the base station (BS) equipped with few-bit ADCs. By exploiting the low-rank property of the cascaded channel, the estimation problem is formulated as a low-rank matrix completion problem. The Bayesian optimal inference framework is introduced to tackle information loss caused by quantization. The efficient bilinear generalized approximate message passing (BiG-AMP) algorithm is used to implement the estimator and achieve matrix completion. Extensive simulation results verify the accurate estimation of the cascaded channel for the RIS-aided mmWave massive MIMO system with low-resolution ADCs.
IEEE COMMUNICATIONS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Yalin Wang, Xihan Chen, Yunlong Cai, Benoit Champagne, Lajos Hanzo
Summary: This paper investigates the challenges in achieving high channel estimation accuracy and reducing hardware cost and power dissipation in massive MIMO systems. By optimizing pilot sequences, the number of quantization bits and the hybrid receiver combiner, we address the channel estimation problem in the uplink of multiuser massive MIMO systems. Using fractional programming techniques, we propose novel algorithms for solving the associated mixed-integer problems.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Tianle Liu, Jun Tong, Jinhong Yuan, Jiangtao Xi, Haiquan Wang, Lou Zhao
Summary: This paper investigates the performance of uplink massive MIMO systems with low-resolution ADCs operating over Rician fading channels. Zero-forcing group successive interference cancellation receivers are studied and the spectrum efficiency is analyzed for general power allocation under both perfect and imperfect CSI. The optimal power allocation for a given QoS is derived for the GSIC receivers. Based on random matrix theory, the asymptotic approximations of SINR for the system and the power allocation are derived. The results show that power allocation improves the overall EE and GSIC receiver yields high EE with a small number of groups. Additionally, the system EE can be improved with intermediate-resolution ADCs and ordered SIC.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Youzhi Xiong, Sanshan Sun, Li Liu, Sun Mao, Zhongpei Zhang, Ning Wei
Summary: In this paper, we focus on cell-free massive MIMO networks with low-resolution ADCs. We derive the theoretical achievable uplink spectral efficiency for the MMSE-based LSFD. Additionally, we investigate the bit allocation among APs to maximize the asymptotic sum SE under the constraint of total ADC quantization bits. Simulation results confirm the accuracy of our theoretical analysis and validate the superiority of the proposed BA technique over random and fixed counterparts.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Don-Roberts Emenonye, Carl Dietrich, R. Michael Buehrer
Summary: In this paper, a differential modulation and detection scheme for a multi-antenna base station with low-resolution ADCs is presented. The maximum likelihood detector for differentially encoded phase information symbol in the low-resolution ADC regime is derived, along with a reduced complexity receiver. A maximum likelihood expression for detecting differential amplitude phase shift keying symbols with low-resolution ADCs is also provided. The paper introduces two detectors capable of detecting the amplitude information using the Bussgang Theorem and the Central Limit Theorem (CLT). The performance and complexity of the proposed detectors are evaluated through simulations.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Editorial Material
Engineering, Electrical & Electronic
Cunhua Pan, Rui Zhang, Marco Di Renzo, A. Lee Swindlehurst, Ying-Jun Angela Zhang
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Cunhua Pan, Gui Zhou, Kangda Zhi, Sheng Hong, Tuo Wu, Yijin Pan, Hong Ren, Marco Di Renzo, A. Lee Swindlehurst, Rui Zhang, Angela Yingjun Zhang
Summary: This paper provides a comprehensive overview of recent advances in RIS-aided wireless systems and highlights promising research directions for the future.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2022)
Article
Computer Science, Hardware & Architecture
Ender Ayanoglu, Filippo Capolino, A. Lee Swindlehurst
Summary: Reconfigurable Intelligent Surfaces (RISs) are programmable metasurfaces that adaptively steer electromagnetic energy to provide wireless access and improve coexistence with other services. The wave-controlled RIS architecture proposed in this work reduces hardware requirements and enhances performance through signal processing and machine learning methods.
IEEE WIRELESS COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Ly V. Nguyen, Duy H. N. Nguyen, A. Lee Swindlehurst
Summary: This paper proposes a deep learning framework for channel estimation, data detection, and pilot signal design in few-bit MIMO systems with nonlinearity caused by low-resolution ADCs. The proposed networks utilize domain knowledge and model-driven structures to address the quantization process. Simulation results demonstrate significant performance improvements in estimation accuracy.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Ang Li, Chao Shen, Xuewen Liao, Christos Masouros, A. Lee Swindlehurst
Summary: In this paper, a constructive interference (CI)-based block-level precoding (CI-BLP) approach is proposed for the downlink of a multi-user multiple-input single-output (MU-MISO) communication system. The CI-BLP method applies a constant precoding matrix to a collection of symbols within a transmission block, reducing computational costs compared to existing CI precoding approaches. An optimization problem is formulated to maximize the minimum CI effect over the block, subject to a block-level power budget. The optimal precoding matrix for CI-BLP is mathematically derived and shown to be equivalent to a quadratic programming (QP) optimization.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Rang Liu, Ming Li, Honghao Luo, Qian Liu, A. Lee Swindlehurst
Summary: Integrated sensing and communication (ISAC) is a key solution for addressing spectrum congestion and increasing demands. By sharing resources and using reconfigurable intelligent surface (RIS) technology, ISAC achieves higher efficiencies. This article analyzes the potential of deploying RIS in ISAC systems to improve communication and sensing performance, discusses existing explorations, presents a case study, and outlines open challenges and research directions.
IEEE WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Ly V. Nguyen, Nhan T. Nguyen, Nghi H. Tran, Markku Juntti, A. Lee Swindlehurst, Duy H. N. Nguyen
Summary: Massive multiple-input multiple-output (MIMO) is a key technology for next-generation wireless systems, providing substantial spatial multiplexing gains. However, the complexity in signal processing increases with the number of users, making conventional algorithms less efficient. Low-complexity massive MIMO detection algorithms, particularly those based on deep learning, have emerged as a promising solution.
IEEE WIRELESS COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Renjie Xie, Wei Xu, Jiabao Yu, Aiqun Hu, Derrick Wing Kwan Ng, A. Lee Swindlehurst
Summary: Deep learning applied to a device's radio-frequency fingerprint has attracted attention in physical-layer authentication. We propose a disentangled representation learning framework that separates device-relevant and device-irrelevant components to avoid overfitting and improve generalizability to unknown devices and propagation environments.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Eyad Shtaiwi, Hongliang Zhang, Ahmed Abdelhadi, A. Lee Swindlehurst, Zhu Han, H. Vincent Poor
Summary: This paper proposes a method to address the potential harmful interference in integrated sensing and communication (ISAC) using a reconfigurable intelligent surface (RIS). The RIS can adjust the amplitude and phase shift of impinging signals, providing a high beamforming gain to maximize the communication system's sum-rate. Simulation results demonstrate that the proposed RIS-assisted design significantly reduces mutual interference and improves the system sum-rate for the communication system.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Shun-Chi Wu, Shih-Ying Wei, Chun-Shun Chang, A. Lee Swindlehurst, Jui-Kun Chiu
Summary: This study focuses on applying deep learning, especially convolutional neural networks (CNNs), to ECG biometric identification, addressing deficiencies through user-specific feature vectors and quantum evolutionary algorithm-based pruning. The proposed scheme achieved a high identification rate in closed-set identification and demonstrated the ability to resist attacks while reducing computational complexity.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Proceedings Paper
Remote Sensing
Fangzhou Wang, A. Lee Swindlehurst, Hongbin Li
Summary: This paper considers joint antenna selection and digital beamforming design for a DFRC system that serves multiple multicast communication groups and performs sensing. The optimization problem is formulated as maximizing the minimum target illumination power in multiple target directions subject to constraints on signal-to-interference-plus-noise ratio for communication users and clutter power for clutter scatterers. A penalized sequential convex relaxation scheme along with semidefinite relaxation is proposed to solve the mixed integer programming problem. Numerical results demonstrate the effectiveness of the proposed DFRC scheme and algorithm.
2023 IEEE RADAR CONFERENCE, RADARCONF23
(2023)
Proceedings Paper
Remote Sensing
Fangzhou Wang, Hongbin Li, A. Lee Swindlehurst
Summary: This paper explores the use of hybrid reconfigurable intelligent surface (RIS) for clutter mitigation and target detection in radar systems. The hybrid RIS can adjust both the phase and modulus of the impinging signal, making it a compromise solution between conventional reflect-only and active RIS. The RIS design is formulated as a convex problem without target range cell information and solved efficiently. With target range cell information, a non-convex optimization problem is solved using fractional programming algorithms. Numerical results demonstrate the performance of the proposed hybrid RIS in clutter suppression for target detection in comparison with conventional RIS.
2023 IEEE RADAR CONFERENCE, RADARCONF23
(2023)
Proceedings Paper
Computer Science, Hardware & Architecture
Azadeh Tabeshnezhad, A. Lee Swindlehurst, Tommy Svensson
Summary: In this paper, the authors investigate the use of reconfigurable intelligent surfaces (RIS) in an uplink power-domain non-orthogonal multiple access (NOMA) system to minimize the total transmit power required by user terminals in the presence of a jammer. The results show that the RIS can dramatically reduce the per user required transmit power in an interference-limited scenario.
2023 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC
(2023)
Proceedings Paper
Computer Science, Hardware & Architecture
Ang Li, Chao Shen, Xuewen Liao, Christos Masouros, A. Lee Swindlehurst
Summary: In this paper, a CI-based block-level precoding (CI-BLP) scheme is proposed for the downlink transmission of a multi-user multiple-input single-output (MU-MISO) communication system. The scheme maximizes the minimum constructive interference effect over the entire block by designing a constant precoding matrix for a block of symbol slots. Numerical results demonstrate that the proposed CI-BLP scheme outperforms traditional block-level precoding and symbol-level precoding methods due to the relaxed block-level power constraint.
2023 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC
(2023)