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Hybrid Neural Network-Based Fading Channel Prediction for Link Adaptation

IEEE ACCESS 2021年 9卷 117257-117266页

作者： Eom, Chahyeon Lee, Chungyong Yonsei Univ Sch Elect & Elect Engn Seoul 03722 South Korea

We propose an artificial intelligence-based channel prediction scheme that can potentially facilitate link adaptation in customized communication systems. Link adaptation is a key process for wireless communication that requires accurate channel state information (CSI). However, the CSI may be outdated because of computational and propagation delays. In addition, a subframe with no CSI reference signal cannot provide CSI feedback. The proposed scheme solves these problems by predicting future channels. Although traditional stochastic methods suffer from marginal prediction accuracy or unacceptable computational complexity, neural networks allow time series prediction for channels even considering constraints for practical application. We introduce a hybrid architecture for improving the prediction accuracy of the neural network when extracting meaningful features. The proposed scheme uses a single hybrid network that can predict channels in different environments. Simulations were performed using a spatial channel model to evaluate the performance at the system-level, and the results indicated that the proposed scheme effectively increases the prediction accuracy for the channel quality indicator and spectral efficiency.

关键词： Predictive models OFDM Antenna arrays Delays Channel estimation Adaptation models Recurrent neural networks adaptive modulation and coding artificial intelligence channel prediction customized communication system link adaptation neural network sixth generation

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A learning approach to link adaptation based on multi-entities Bayesian network

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第4-Sup期22卷 S8463-S8473页

作者： Zhang, Cui Lei, Xia Yuan, Yannan Song, Lijun Univ Elect Sci & Technol China Natl Key Lab Sci & Technol Commun Chengdu Sichuan Peoples R China Chengdu Univ Informat Technol Coll Commun Engn Chengdu Sichuan Peoples R China

adaptive modulation and coding (AMC) is widely used in modern communications which attempts to predict the best available rate and select the most suitable modulation and coding scheme (MCS) by estimating the real-time channel quality to obtain higher throughput of communication system. However, due to the characteristics of wireless channel fading, there are a lot of uncertainties in the communication process, which makes deviation between the channel estimate and the true value and can affect performance of AMC system. Bayesian network is an important tool to research uncertainty. This paper considers learning with the multi-entities bayesian network (MEBN) as a new framework for adaptive modulation and coding which avoids the flaw of flexibility in traditional Bayesian network (BN). Simulation results show that our algorithm has more validity in the selection MCS and lower bit error rate (BER) by considering estimate deviation in MEBN-AMC system. We also provide the further simulation results by using Bayesian structure learning and parameter learning.

关键词： adaptive modulation and coding Multi-entities Bayesian network Learning framework

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EESM-Based Link Adaptation in Point-to-Point and Multi-Cell OFDM Systems: Modeling and Analysis

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2014年第1期13卷 407-417页

作者： Francis, Jobin Mehta, Neelesh B. Indian Inst Sci IISc Dept Elect Commun Eng Bangalore Karnataka India

In contemporary wideband orthogonal frequency division multiplexing (OFDM) systems, such as Long Term Evolution (LTE) and WiMAX, different subcarriers over which a codeword is transmitted may experience different signal-to-noise-ratios (SNRs). Thus, adaptive modulation and coding (AMC) in these systems is driven by a vector of subcarrier SNRs experienced by the codeword, and is more involved. Exponential effective SNR mapping (EESM) simplifies the problem by mapping this vector into a single equivalent fiat-fading SNR. Analysis of AMC using EESM is challenging owing to its non-linear nature and its dependence on the modulation and coding scheme. We first propose a novel statistical model for the EESM, which is based on the Beta distribution. It is motivated by the central limit approximation for random variables with a finite support. It is simpler and as accurate as the more involved ad hoc models proposed earlier. Using it, we develop novel expressions for the throughput of a point-to-point OFDM link with multi-antenna diversity that uses EESM for AMC. We then analyze a general, multi-cell OFDM deployment with co-channel interference for various frequency-domain schedulers. Extensive results based on LTE and WiMAX are presented to verify the model and analysis, and gain new insights.

关键词： Orthogonal frequency division multiplexing (OHM) adaptive modulation and coding exponential effective SNR mapping (EESM) scheduling cell throughput co-channel interference beta distribution

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Reconfigurable antennas and link adaptation algorithms for MIMO-OFDM wireless systems

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2015年第1期000卷 1-15页

作者： Sworo, George D. Dandekar, Kapil R. Kam, Moshe Drexel Univ Dept Elect & Comp Engn Philadelphia PA 19104 USA New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA

In this work, we study and analyze the performance of physical layer algorithms for adaptive multiple input-multiple output orthogonal frequency-division multiplexing (MIMO-OFDM) wireless systems that employ a new class of adaptive antenna systems known as reconfigurable antennas. These antennas are capable of adaptively modifying their radiation characteristics and thus leverage pattern diversity to affect how the transmitter and receiver perceive the wireless channel. We propose a low complexity spatial adaptive modulation and coding (AMC) algorithm that uses the advantages of pattern reconfigurable antennas in concert with link adaptation to improve MIMO-OFDM link throughput. The algorithm operates in two main stages;first, it searches for the antenna configuration that yields the highest post processing signal-to-noise ratio (ppSNR) and, then, applies AMC to improve spectral efficiency. The performance of the proposed scheme is experimentally evaluated for a 2x2 MIMO-OFDM wireless system in an indoor environment.

关键词： Link adaptation MIMO-OFDM Reconfigurable antennas adaptive modulation and coding Spatial multiplexing

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Reinforcement Learning for Efficient and Tuning-Free Link Adaptation

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2022年第2期21卷 768-780页

作者： Saxena, Vidit Tullberg, Hugo Jalden, Joakim KTH Royal Inst Technol Div Informat Sci & Engn S-11428 Stockholm Sweden Ericsson Res S-16480 Stockholm Sweden

Wireless links adapt the data transmission parameters to the dynamic channel state - this is called link adaptation. Classical link adaptation relies on tuning parameters that are challenging to configure for optimal link performance. Recently, reinforcement learning has been proposed to automate link adaptation, where the transmission parameters are modeled as discrete arms of a multi-armed bandit. In this context, we propose a latent learning model for link adaptation that exploits the correlation between data transmission parameters. Further, motivated by the recent success of Thompson sampling for multi-armed bandit problems, we propose a latent Thompson sampling (LTS) algorithm that quickly learns the optimal parameters for a given channel state. We extend LTS to fading wireless channels through a tuning-free mechanism that automatically tracks the channel dynamics. In numerical evaluations with fading wireless channels, LTS improves the link throughout by up to 100% compared to the state-of-the-art link adaptation algorithms.

关键词： Wireless communication Interference Signal to noise ratio Reinforcement learning Fading channels Throughput Channel estimation Wireless networks adaptive modulation and coding reinforcement learning thompson sampling outer loop link adaptation

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Blind Reconstruction of Reed-Solomon Encoder and Interleavers Over Noisy Environment

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IEEE TRANSACTIONS ON BROADCASTING 2018年第4期64卷 830-845页

作者： Swaminathan, R. Madhukumar, A. S. Wang, Guohua Kee, Ting Shang Nanyang Technol Univ Sch Comp Sci & Engn Singapore 639798 Singapore Nanyang Technol Univ Temasek Labs Singapore 639798 Singapore

Blind estimation of code and interleaver parameters is useful in smart storage systems and ubiquitous communication applications such as adaptive modulation and coding, reconfigurable radio systems, non-cooperative radio systems, etc. In this paper, we analyze Reed-Solomon (RS) encoded data stream and propose blind estimation algorithms to identify RS code parameters. We also provide algorithms to estimate block interleaver parameters from RS coded and block interleaved data stream. In addition, synchronization compensation through appropriate bit/symbol positioning is integrated with the proposed code and interleaver parameter estimation algorithms. Simulation results validating the proposed algorithms are given for various test cases involving both erroneous and non-erroneous scenarios. Moreover, the accuracy of estimation of RS code and block interleaver parameters are also given with detailed inferences for different modulation schemes, codeword length, and code dimension values. It has been inferred that the accuracy of parameter estimation improves with decrease in code dimension and codeword length values of RS codes. Further, the accuracy of estimation of lower modulation order schemes is better when compared to higher modulation order schemes as expected. It has also been noted that the proposed code and interleaver parameter estimation algorithms for noisy environment consistently outperform the algorithms proposed in the prior works.

关键词： adaptive modulation and coding blind reconstruction block interleaver data storage systems non-cooperative systems and Reed-Solomon (RS) codes

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Dual-Hop adaptive Packet Transmission Systems with Regenerative Relaying

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2010年第1期9卷 234-244页

作者： Mueller, Andreas Yang, Hong-Chuan Univ Stuttgart Inst Telecommun Stuttgart Germany Univ Victoria Dept Elect & Comp Engn Victoria BC V8W 2Y2 Canada

We propose and analyze two different approaches for performing adaptive modulation and coding (AMC) in dual-hop transmission systems, where a source node S communicates with a certain destination node D via an intermediate decode-and-forwarding relay station R. In this regard, we consider the most general case, where the AMC on the S-R and R-D links might be performed independently of each other, thus requiring a potential buffering of data packets at the relay station before they can be forwarded to the destination D. With our first approach, AMC is performed solely based on the instantaneous channel realizations, without considering the current buffer level at the relay station, what consequently might result in packet losses due to potential buffer overflows. Our second approach eliminates this problem by taking the current buffer level into account in the AMC transmission over the first hop and reducing the transmission rate accordingly if the buffer would overflow otherwise. Both schemes are analyzed analytically based on a finite-state Markov chain model of our system. Building upon this model, we derive analytical closed-form expressions for a variety of different key performance indicators, which are illustrated for various practical cases by means of selected numerical results.

关键词： adaptive modulation and coding decode-and-forward multihop transmission regenerative relaying

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Iterative Learning for Reliable Link Adaptation in the Internet of Underwater Things

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IEEE ACCESS 2021年 9卷 30408-30416页

作者： Byun, Junghun Cho, Yong-Ho Im, Taeho Ko, Hak-Lim Shin, Kyungseop Kim, Juyeop Jo, Ohyun Chungbuk Natl Univ Dept Comp Sci Cheongju 28644 South Korea Mokpo Natl Univ Dept Elect Informat & Commun Engn Mokpo 58554 South Korea Hoseo Univ Dept Informat & Commun Engn Asan 31499 South Korea Sangmyung Univ Dept Comp Sci Seoul 03016 South Korea Sookmyung Womens Univ Dept Elect Engn Seoul 04310 South Korea

Given the ever-increasing interest in the Internet of Underwater Things (IoUT), various studies are ongoing to solve some of the practical problems affecting the development of underwater wireless communication. The main problems are related to the use of acoustic waves in a water medium, in which extremely high propagation loss and drastic channel fluctuation are common. On the basis of hands-on experience and measurements made in real underwater environments, the conventional adaptive modulation and coding (AMC), which uses the high correlation between SNR (Signal to Noise Ratio) and BER (Bit Error Rate), might not be affordable in underwater environments because the normal correlation between SNR and BER almost disappears altogether. This work therefore collectively takes into account multiple quality factors of communication at the same time by creating, analysing and validating the machine learning model to predict the most adequate communication parameters to solve the problem. The dataset of underwater wireless communication used in the learning models was obtained from measurements made in a real underwater environment near the Gulf of Incheon, South Korea, using a practical testbed designed and implemented by the authors. The estimated network throughput based on the communications parameters predicted using the machine learning models was enhanced by up to 25% compared with the conventional handcraft method.

关键词： Machine learning Correlation Signal to noise ratio Predictive models Wireless communication Sea measurements Binary phase shift keying Link adaptation adaptive modulation and coding underwater wireless communications machine learning Internet of Underwater Things

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Flexible block-wise loading algorithm for effective resource allocation and reduction of uplink feedback information in OFDMA systems

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WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2009年第10期9卷 1351-1359页

作者： Sun, TaeHyoung Wang, YuPeng Chang, KyungHi Inha Univ Grad Sch Informat Technol & Telecommun Inchon 402751 South Korea

adaptive modulation and coding (AMC) is a well-known technique that selects a suitable modulation level and coding rate according to the user's channel quality. The utilization of AMC in downlink (DL) requires the channel information of each user on DL to properly select the modulation and coding scheme (MCS) level. However, under a practical OFDMA system environment, it is unsuitable to feedback all the channel information over the whole frequency resources due to the limited uplink bandwidth. In this paper, to optimize the performance of the AMC system and to reduce the uplink feedback requirement, we propose a flexible block-wise loading (FBL) algorithm combined with a novel channel quality information (CQI) feedback scheme requiring less number of CQI feedback bits, which is suitable for the general OFDMA system with AMC. The proposed FBL algorithm dynamically allocates groups of sub-carriers to each user in DL based oil the channel quality information encapsulated in a newly defined feedback signal format. As a result, the sector throughput and outage performance is improved due to the flexibility oil the sub-channel allocation and increased accuracy on the CQI feedback information by the proposed FBL algorithm. Copyright (C) 2008 John Wiley & Sons, Ltd.

关键词： OFDMA adaptive modulation and coding FBL CQI reduction

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Cross-layer optimization for video summary transmission over wireless networks

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2007年第4期25卷 841-850页

作者： Wu, Dalei Ci, Song Wang, Haohong Univ Nebraska Dept Comp & Elect Engn Omaha NE 68182 USA Marvell Semicond Santa Clara CA 95054 USA

Video summarization has gained increased popularity in the emerging multimedia communication applications, however, very limited work has been conducted to address the transmission problem of video summary frames. In this paper, we propose a cross-layer optimization framework for delivering video summaries over wireless networks. Within a rate-distortion theoretical framework, the source coding, allowable retransmission, and adaptive modulation and coding have been jointly optimized, which reflects the joint selection of parameters at physical, data link and application layers. The goal is to achieve the best video quality and content coverage of the received summary frames and to meet the delay constraint. The problem is solved using Lagrangian relaxation and dynamic programming. Experimental results indicate the effectiveness and efficiency of the proposed optimization framework, especially when the delay budget imposed by the upper layer applications is small, where more than 10% distortion gain can be achieved.

关键词： universal multimedia access video summarization adaptive modulation and coding automatic repeat request cross-layer optimization rate distortion video communication

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