检索结果-内蒙古大学图书馆

On Minimizing Symbol Error Rate Over Fading Channels With low-resolution quantization

IEEE TRANSACTIONS ON COMMUNICATIONS 2021年第11期69卷 7205-7221页

作者： Bernardo, Neil Irwin Zhu, Jingge Evans, Jamie Univ Melbourne Dept Elect & Elect Engn Parkville Vic 3010 Australia

We analyze the symbol error probability (SEP) of M-ary pulse amplitude modulation (M-PAM) receivers equipped with optimal low-resolution quantizers. We first show that the optimum detector can be reduced to a simple decision rule. Using this simplification, an exact SEP expression for quantized M-PAM receivers is obtained when Nakagami-m fading channel is considered. The derived expression enables the optimization of the quantizer and/or constellation under the minimum SEP criterion. Our analysis of optimal quantization for equidistant M-PAM receiver reveals the existence of error floor which decays at a double exponential rate with increasing quantization bits, b. Moreover, by also allowing the transmitter to optimize the constellation based on the statistics of the fading channel, we prove that the error floor can be eliminated but at a lower decay exponent than the unquantized case. Characterization of this decay exponent is provided in this paper. We also expose the outage performance limitations of SEP-optimal uniform quantizers. To be more precise, its decay exponent does not improve with b. Lastly, we demonstrate that the decay exponent of a quantized receiver can be complemented by receive antenna diversity techniques.

关键词： low-resolution quantization symbol error probability optimization fading diversity order

来源：评论

学校读者我要写书评

暂无评论

Reliability Characterization for SIMO Communication Systems With low-resolution Phase quantization Under Rayleigh Fading

IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY

引用

IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY 2021年 2卷 2660-2679页

作者： Gayan, Samiru Senanayake, Rajitha Inaltekin, Hazer Evans, Jamie Univ Moratuwa Dept Elect & Telecommun Engn Katubedda 10400 Sri Lanka Univ Melbourne Dept Elect & Elect Engn Parkville Vic 3100 Australia Macquarie Univ Sch Engn N Ryde NSW 2109 Australia

This paper investigates the communication reliability for single-input-multiple-output wireless systems with low-resolution phase quantizers. First, the maximum-likelihood detector with n-bit phase quantization is derived when there are N antennas at the receiver. Then, three low-complexity antenna selection strategies for data detection are proposed and their symbol error probability performance is characterized. It is shown that having 3 or more bits is sufficient to attain the full diversity order N, achievable with infinite-bit quantizers, for quadrature phase shift keying modulation under Rayleigh fading. In particular, it is established that the proposed low-complexity max-distance and max-norm antenna selection strategies perform the same as the maximum-likelihood detector in terms of the asymptotic system reliability for n >= 3. On the other hand, the diversity order decreases dramatically from N to N/2 when n is equal to 2, as illustrated by our numerical results and proven for the case of N = 2. An extensive numerical and simulation study is performed to illustrate the accuracy of the derived results and asymptotic system reliability performance as well as verifying our hypotheses in the high signal-to-noise ratio regime.

关键词： low-resolution quantization ML detectors selection combining symbol error probability diversity order

来源：评论

学校读者我要写书评

暂无评论

Detection Schemes With low-resolution ADCs and Spatial Oversampling for Transmission With Higher-Order Constellations in Terahertz Band

引用

IEEE ACCESS 2025年 13卷 24643-24660页

作者： Forsch, Christian Zillmann, Peter Alrabadi, Osama Brueck, Stefan Gerstacker, Wolfgang Friedrich Alexander Univ Erlangen Nurnberg Inst Digital Commun D-91054 Erlangen Germany Qualcomm CDMA Technol D-90411 Nurnberg Germany

In this work, we consider Terahertz (THz) communications with low-resolution uniform quantization and spatial oversampling at the receiver side, corresponding to a single-input multiple-output (SIMO) transmission. We fairly compare different analog-to-digital converter (ADC) parametrizations by keeping the ADC power consumption constant. Here, 1-, 2-, and 3-bit quantization is investigated with different oversampling factors. We analytically compute the statistics of the detection variable, and we propose the optimal and several suboptimal detection schemes for arbitrary quantization resolutions. Then, we evaluate the symbol error rate (SER) of the different detectors for 16- and 64-ary quadrature amplitude modulation (QAM). The results indicate that there is a noticeable performance degradation of the suboptimal detectors compared to the optimal detector when the constellation size is larger than the number of quantization levels. Furthermore, at low signal-to-noise ratios (SNRs), 1-bit quantization outperforms 2- and 3-bit quantization, respectively, even when employing higher-order constellations. We confirm our analytical results by Monte Carlo simulations. Both a pure line-of-sight (LoS) and a more realistically modeled indoor THz channel are considered. Then, we optimize the input signal constellation with respect to SER for 1- and 2-bit quantization. The results give insights for optimizing higher-order constellations for arbitrary quantization resolutions and show that the minimum SER can be lowered significantly by appropriately placing the constellation points.

关键词： quantization (signal) Detectors Terahertz communications Symbols Receivers OFDM Vectors Quadrature amplitude modulation Signal to noise ratio Maximum likelihood detection Constellation optimization low-resolution quantization maximum-likelihood detection oversampling symbol error rate terahertz communications

来源：评论

学校读者我要写书评

暂无评论

Optimal Precoding for Multiuser MIMO Systems With Phase quantization and PSK Modulation via Branch-and-Bound

引用

IEEE WIRELESS COMMUNICATIONS LETTERS 2020年第9期9卷 1393-1397页

作者： Lopes, Erico S. P. Landau, Lukas T. N. Pontificia Univ Catolica Rio De Janeiro Ctr Estudos Telecomunicacoes BR-22453900 Rio De Janeiro Brazil

With an increasing number of antennas in MIMO systems, the energy consumption and costs of the corresponding front ends become relevant. In this context, a promising approach is the consideration of low-resolution data converters. In this letter we propose an optimal precoding algorithm constrained to constant envelope signals and phase quantization that maximizes the minimum distance to the decision threshold at the receivers using a branch-and-bound strategy. The proposed algorithm is superior to the existing methods in terms of bit error rate. Numerical results show that the proposed approach has significantly lower complexity than exhaustive search.

关键词： Precoding quantization (signal) Phase shift keying Transmitting antennas MIMO communication Upper bound Energy consumption Precoding low-resolution quantization MIMO systems branch-and-bound methods

来源：评论

学校读者我要写书评

暂无评论

Analytical Solution of Optimal Symbol Error Rate for Multilevel Pulse-Amplitude-Modulated Signals With One-Bit quantization

引用

IEEE COMMUNICATIONS LETTERS 2023年第10期27卷 2732-2736页

作者： Wei, Shumei Xu, Jin Tao, Xiaofeng Zhen, Ziqing Beijing Univ Posts & Telecommun Natl Engn Res Ctr Mobile Network Technol Beijing 100876 Peoples R China

low-resolution ADC is a promising solution to reduce circuit cost and energy consumption in 6G wireless communication systems. There are few analytical results on symbol error performance with low-resolution quantization. In this letter, novel, analytical solution for the optimal symbol error rate (SER) of $M$ -ary pulse amplitude modulated ( $M$ -PAM) signals with one-bit quantization over additive white Gaussian noise (AWGN) channel is derived. The SER expression is shown to be the function of quantization thresholds, modulated symbol levels and sampling numbers by utilizing the asymptotic distribution of the quantized outputs. The new solution shows that temporal oversampling compensates for 1-bit quantization and the SER performance bound when sampling number goes to infinity degrades by a factor of $2/\pi $ compared to the unquantized case. These results allow for a rapid and accurate evaluation of the system performance when using 1-bit ADCs, and thus offer a useful tool for system design, analysis and optimization.

关键词： quantization (signal) Symbols Receivers Gaussian distribution AWGN channels Detectors Additives low-resolution quantization 1-bit ADC symbol error rate multilevel PAM quantization threshold

来源：评论

学校读者我要写书评

暂无评论

Asymptotic Analysis for low-resolution Massive MIMO Systems with MMSE Receiver

引用

China Communications 2018年第9期15卷 189-199页

作者： Kai Liu Cheng Tao Liu Liu Tao Zhou Yinsheng Liu Institute of Broadband Wireless Mobile Communications School of Electronics and Information Engineering Beijing Jiaotong University National Mobile Communications Research Laboratory Southeast University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University

The uplink achievable rate of massive multiple-input-multiple-output(MIMO) systems, where the low-resolution analog-to-digital converters(ADCs) are assumed to equip at the base station(BS), is investigated in this paper. We assume that only imperfect channel station information is known at the BS. Then a new MMSE receiver is designed by taking not only the Gaussian noise, but also the channel estimation error and quantizer noise into account. By using the Stieltjes transform of random matrix, we further derive a tight asymptotic equivalent for the uplink achievable rate with proposed MMSE receiver. We present a detailed analysis for the number of BS antennas through the expression of the achievable rates and validate the results using numerical simulations. It is also shown that we can compensate the performance loss due to the low-resolution quantization by increasing the number of antennas at the BS.

关键词： massive MIMO low-resolution quantization MMSE receiver

来源：评论

学校读者我要写书评

暂无评论

Throughput Analysis of Massive MIMO Uplink With low-resolution ADCs

引用

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2017年第6期16卷 4038-4051页

作者： Jacobsson, Sven Durisi, Giuseppe Coldrey, Mikael Gustavsson, Ulf Studer, Christoph Ericsson AB S-41756 Gothenburg Sweden Chalmers Univ Technol S-41296 Gothenburg Sweden Cornell Univ Ithaca NY 14853 USA

We investigate the uplink throughput achievable by a multiple-user (MU) massive multiple-input multiple-output (MIMO) system, in which the base station is equipped with a large number of low-resolution analog-to-digital converters (ADCs). Our focus is on the case where neither the transmitter nor the receiver have any a priori channel state information. This implies that the fading realizations have to be learned through pilot transmission followed by channel estimation at the receiver, based on coarsely quantized observations. We propose a novel channel estimator, based on Bussgang's decomposition, and a novel approximation to the rate achievable with finite-resolution ADCs, both for the case of finite-cardinality constellations and of Gaussian inputs, that is accurate for a broad range of system parameters. Through numerical results, we illustrate that, for the 1-bit quantized case, pilot-based channel estimation together with maximal-ratio combing, or zero-forcing detection enables reliable multi-user communication with high-order constellations, in spite of the severe nonlinearity introduced by the ADCs. Furthermore, we show that the rate achievable in the infinite-resolution (no quantization) case can be approached using ADCs with only a few bits of resolution. We finally investigate the robustness of low-ADC-resolution MU-MIMO uplink against receive power imbalances between the different users, caused for example by imperfect power control.

关键词： Analog-to-digital converter (ADC) channel capacity linear minimum mean square error (LMMSE) channel estimation low-resolution quantization multi-user massive multiple-input multiple-output (MIMO)

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Channel Extrapolation for Hybrid RIS-Aided mmWave Systems With low-resolution ADCs

引用

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2024年第10期23卷 14408-14420页

作者： Gong, Tingting Zhang, Shun Gao, Feifei Li, Zan Di Renzo, Marco Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Tsinghua Univ Inst Artificial Intelligence Beijing 100084 Peoples R China Tsinghua Univ Beijing Natl Res Ctr Informat Sci & Technol Dept Automat State Key Lab Intelligent Technol & Syst Beijing 100084 Peoples R China Univ Paris Saclay CNRS Cent Supelec Lab Signaux & Syst F-91192 Gif Sur Yvette France

Millimeter wave communications are sensitive to complex scattering environments (e.g., to the presence of obstacles), which can be mitigated by reconfigurable intelligent surfaces (RISs). Traditional nearly passive RISs lack the ability to perform signal processing operations, which makes channel estimation in RIS-aided communications more challenging. Hence, in this paper, we focus on a hybrid RIS architecture, which is equipped with a small number of active elements. These active elements can be connected with baseband processing units through radio frequency (RF) chains. We estimate the whole channel, including the channel between the base station (BS) and the RIS, that between the users and the RIS, and that between the BS and the users. The whole channel is acquired at the hybrid RIS through the transmission of several segments of training pilots. In order to decrease the hardware cost, the BS and the hybrid RIS are equipped with RF chains with low-resolution analog-to-digital converters (ADCs). Since the numbers of BS antennas and RIS elements are very large, the estimation of the full-space channels is not straightforward. To tackle this problem, we propose a channel extrapolation scheme based on a joint selection model. Specifically, we select a BS antenna subset and an RIS element subset to be connected to the RF chains and to estimate the partial-space channels related to these subsets. Then, a reference-based variational auto-encoder model is used to implement the extrapolation from the partial-space channels to the full-space channels. Besides, the optimal joint selection pattern is acquired through a selection network to improve the channel extrapolation performance. Moreover, to overcome the quantization error caused by the use of low-resolution ADCs, we propose a two-stage repair scheme for channel estimation. Simulation results are provided to demonstrate the effectiveness of the designed channel extrapolation scheme.

关键词： channel extrapolation hybrid reconfigurable intelligent surface Deep learning probabilistic sampling theory probabilistic sampling theory low-resolution quantization low-resolution quantization probabilistic sampling theory low-resolution quantization

来源：评论

学校读者我要写书评

暂无评论

Hermite Expansion Model and LMMSE Analysis for low-resolution Quantized MIMO Detection

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2021年 69卷 5313-5328页

作者： Liu, Lifu Ma, Yi Yi, Na Univ Surrey 5G Innovat Ctr Guildford GU2 7XH Surrey England Univ Surrey 6G Innovat Ctr Inst Commun Syst Guildford GU2 7XH Surrey England

In this paper, the Hermite polynomials are employed to study linear approximation models of narrowband multi-antenna signal reception (i.e., MIMO) with low-resolution quantizations. This study results in a novel linear approximation using the second-order Hermite expansion (SOHE). The SOHE model is not based on those assumptions often used in existing linear approximations. Instead, the quantization distortion is characterized by the second-order Hermite kernel, and the signal term is characterized by the first-order Hermite kernel. It is shown that the SOHE model can explain almost all phenomena and characteristics observed so far in the low-resolution MIMO signal reception. When the SOHE model is employed to analyze the linear minimum-mean-square-error (LMMSE) channel equalizer, it is revealed that the current LMMSE algorithm can be enhanced by incorporating a symbol-level normalization mechanism. The performance of the enhanced LMMSE algorithm is demonstrated through computer simulations for narrowband MIMO systems in Rayleigh fading channels.

关键词： quantization (signal) Mathematical model Analytical models MIMO communication Linear approximation Equalizers Computational modeling Detection Hermite expansion model linear minimum mean-square-error (LMMSE) low-resolution quantization multiple-input multiple-output (MIMO)

来源：评论

学校读者我要写书评

暂无评论

Enhancing the Downlink Rate Fairness of low-resolution Active RIS-Aided Signaling by Closed-Form Expression-Based Iterative Optimization

引用

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2024年第6期73卷 8013-8029页

作者： Chen, Yufeng Tuan, Hoang Duong Fang, Yong Yu, Hongwen Poor, H. Vincent Hanzo, Lajos Shanghai Univ Sch Commun & Informat Engn Shanghai 200444 Peoples R China Univ Technol Sydney Sch Elect & Data Engn Sydney NSW 2007 Australia Princeton Univ Dept Elect & Comp Engn Princeton NJ 08544 USA Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ England

This paper proposes a joint design strategy for enhancing individual user rates in a multi-user system by optimizing both the programmable reflecting elements (PREs) of an active reconfigurable intelligent surface (aRIS) and the transmit beamforming at a base station. Given that the aRIS's PREs are bound by discrete constraints due to low-resolution quantization, this design approach relies on large-scale mixed discrete-continuous problems, which are addressed through a new universal penalised optimization reformulations. Initially, we develop iterations based on convex quadratic solvers (CQ) to tackle the problem of maximizing the users' minimum rate (MR). Given that the computational complexity of these CQs is cubic, leading to high costs in large-scale computations, we introduce a pair of surrogate objectives. These objectives are designed in a way that their constrained optimization can be efficiently managed through iterations of closed-form expressions with scalable complexity, rendering them practical for large-scale computations. This pair of surrogate objectives comprises the maximization of the geometric mean of users' rates (GM-rate maximization) and the soft-maximization of users' MR (soft max-min rate optimization). Remarkably, they not only enhance MR but also contribute to the improvement of the sum-rate (SR). Building upon the GM-rate optimization, we further propose addressing the energy efficiency problem, which achieves a high ratio of SR to power consumption and MR to power dissipation through closed-form expressions. Comprehensive simulations are conducted to validate the efficacy of the proposed solutions.

关键词： Optimization Closed-form solutions Minimax techniques Reconfigurable intelligent surfaces quantization (signal) Iterative methods Energy efficiency Active power control active reconfigurable intelligent surface (aRIS) large-scale computation low-resolution quantization max-min rate optimization mixed discrete continuous optimization transmit beamforming

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：