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Retransmission Aware adaptive modulation and coding Toward Deterministic Delay Performance

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2024年第11期23卷 17683-17697页

作者： Jin, Yuze Wang, Wei Wang, Yitu Yin, Rui Zheng, Ziwei Zhang, Zhaoyang Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China North Minzu Univ Sch Elect & Informat Engn Yinchuan 750030 Peoples R China Hangzhou City Univ Coll Informat & Elect Engn Hangzhou 310015 Peoples R China

Ultra-reliable low-latency communication (URLLC) is an indispensable element towards supporting various latency-sensitive and reliability-critical applications. To optimize the average delay while satisfying the deterministic delay constraint, initial transmission and retransmission should be handled with different priorities due to the differentiated urgency, which creates complex interdependency and brings new technical challenges to delay-oriented optimization. In this paper, we propose a retransmission-aware adaptive modulation and coding (RAMC) scheme to improve the delay performance in URLLC scenarios. Specifically, we first establish a cascaded queue system, including an initial transmission queue and a retransmission queue. The deterministic delay constraint is satisfied through Lyapunov optimization, where we transform the Lyapunov drift-plus-penalty problem into an infinite horizon Markov decision process (MDP) by constructing a renewal system with sampling to overcome the challenge brought by queue coupling. Next, we propose the delay-optimal RAMC scheme by solving the associated Bellman equation by improved reinforcement learning, which is proved to be asymptotically optimal. Finally, the superiority of the proposed RAMC scheme is verified through simulations.

关键词： Delays Optimization Ultra reliable low latency communication Throughput modulation Couplings Signal to noise ratio URLLC deterministic delay constraint adaptive modulation and coding data retransmission

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Research on Threshold Adjustment Algorithm in adaptive modulation and coding

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The Journal of China Universities of Posts and Telecommunications 2006年第2期13卷 15-19页

作者： FAN Chen CHEN Mei-ya SU Li-jun YANG Da-cheng School of Telecommunication Engineering Beijing University of Posts and Telecommunications Beijing 100876 P.R. China

adaptive modulation and coding （AMC） has gained a lot of attentions in the research of High Speed Downlink Packet Access （HSDPA）. The idea is to adapt the transmission to the fast changing channel conditions by the use of different modulation and coding Schemes （MCS）. This paper presents an adaptive AMC algorithm and introduces a theoretical analysis model in order to to investigate its throughput and Frame Error Rate （FER）. Subject to the given FER target, our numerical and link level simulation results both show that our algorithm outperforms other existing adaptive algorithms.

关键词： adaptive modulation and coding threshold adjust markov model HSDPA

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Massive MIMO adaptive modulation and coding Using Online Deep Learning Algorithm

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IEEE COMMUNICATIONS LETTERS 2022年第4期26卷 818-822页

作者： Bobrov, Evgeny Kropotov, Dmitry Lu, Hao Zaev, Danila Huawei Technol Moscow Res Ctr Moscow 127106 Russia Moscow MV Lomonosov State Univ Moscow 119991 Russia Natl Res Univ Higher Sch Econ Moscow 101000 Russia

The letter describes an online deep learning algorithm (ODL) for adaptive modulation and coding in massive MIMO. The algorithm is based on a fully connected neural network, which is initially trained on the output of the traditional algorithm and then incrementally retrained by the service feedback of its output. We show the advantage of our solution over the state-of-the-art Q-learning approach. We provide system-level simulation results to support this conclusion in various scenarios with different channel characteristics and different user speeds. Compared with traditional OLLA, the algorithm shows a 10% to 20% improvement in user throughput in the full-buffer case.

关键词： Training Signal to noise ratio Interference Deep learning Neural networks Massive MIMO Throughput adaptive modulation and coding link adaptation Olla deep learning reinforcement learning massive MIMO wireless communications online training

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adaptive cooperation protocol with adaptive modulation and coding

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SIGNAL IMAGE AND VIDEO PROCESSING 2021年第2期15卷 323-329页

作者： Ben Halima, Nadhir Boujemaa, Hatem Taibah Univ Coll Comp Sci & Engn Yanbu Medina Saudi Arabia COSIM Lab Tunis Tunisia

In this paper, we propose two adaptive cooperation protocols for wireless systems. The first protocol chooses between cooperative communications (CC) and non-cooperative communications (NCC), the protocol that offers the highest instantaneous throughput. The best relay is activated only if the instantaneous throughput of relayed link is larger than that of direct link. The second protocol chooses between CC and NCC, the protocol that maximizes the average throughput. The best relay amplifies the received signal only when the average throughput of relayed link is larger than that of direct link. Both protocols include adaptive modulation and coding to increase the throughput by selecting the appropriate modulation and coding scheme. The results are valid for Rayleigh fading channels where relay nodes use amplify and forward relaying.

关键词： adaptive modulation and coding Rayleigh fading channels adaptive link layer protocol

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Analytical Methods for Performance Evaluations of adaptive modulation and coding in Cognitive Radio Systems That Employ Distance Statistics

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IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING 2019年第1期5卷 73-81页

作者： Borkotoky, Siddhartha S. Kottapalli, Sneha Latha Pursley, Michael B. Clemson Univ Clemson SC 29634 USA

Distance statistics have been employed in previous investigations of packet transmission and reception in cognitive radio systems. Such statistics are a good source of control information for packet-to-packet adaptation of modulation and coding to mitigate the effects of time-varying fading or interference. Previous research on distance statistics has relied on simulation for protocol design and performance evaluation. We devise new analytical methods for use in the design and evaluation of protocols for adaptive modulation and coding that obtain control information from a distance statistic. The primary advantage of our approach is the avoidance of simulations of the time-varying channel, generation of the adaptive control information, and adaptation process.

关键词： Cognitive radio ad hoc networks packet radio adaptive modulation and coding fading interference

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Space-time trellis and space-time block coding versus adaptive modulation and coding aided OFDM for wideband channels

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2006年第1期55卷 173-187页

作者： Liew, TH Hanzo, L Univ Southampton Dept Elect & Comp Sci Southampton SO17 1BJ Hants England

The achievable performance of channel coded space-time trellis (STT) codes and space-time block (STB) codes transmitted over wideband channels is studied in the context of schemes having an effective throughput of 2 bits/symbol (BPS) and 3 BPS. At high implementational complexities, the best performance was typically provided by Alamouti's unity-rate G(2) code in both the 2-BPS and 3-BPS scenarios. However, if a low complexity implementation is sought, the 3-BPS 8PSK space-time trellis code out-perforns the G2 code. The G2 space-time block code is also combined with symbol-by-symbol adaptive orthogonal frequency division multiplex (AOFDM) modems and turbo convolutional channel codecs for enhancing the system's performance. It was concluded that upon exploiting the diversity effect of the G2 space-time block code, the channel-induced fading effects are mitigated, and therefore, the benefits of adaptive modulation erode. In other words, once the time- and frequency-domain fades of the wideband channel have been counteracted by the diversity-aided G2 code, the benefits of adaptive modulation erode, and hence, it is sufficient to employ fixed-mode modems. Therefore, the low-complexity approach of mitigating the effects of fading can be viewed as employing a single-transmitter, single-receiver-based AOFDM modem. By contrast, it is sufficient to employ fixed-mode OFDM modems when the added complexity of a two-transmitter G(2) scheme is affordable.

关键词： adaptive modulation and coding HSDPA OTDM STBC STTC

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Optimal adaptive modulation and coding with Switching Costs

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IEEE TRANSACTIONS ON COMMUNICATIONS 2009年第3期57卷 697-706页

作者： Farrokh, Arsalan Krishnamurthy, Vikram Schober, Robert Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada

We present an optimal adaptive modulation and coding policy that minimizes the transmission latency and modulation/coding switching cost across a finite-state Markovian fading channel. We formulate the optimal tradeoff between transmission latency and modulation/coding switching cost as a discounted infinite horizon Markov Decision Problem (MDP). By exploiting special structures of the formulated MDP and under certain sufficient conditions, we show that optimal modulation and coding selection policies are monotone in the state variables. These monotone optimal policies are computationally inexpensive to implement and are scalable in terms of channel and switching cost parameters. Numerical results confirm the monotonicity and threshold-based structure of the optimal modulation and coding Scheme (MCS) selection policies under the proposed sufficient conditions.

关键词： adaptive modulation and coding Markov decision problem (MDP) modulation and coding scheme (MCS) opportunistic selection threshold-based ordering

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Cross-layer in MIMO-OFDM System with adaptive modulation and coding:Design and Analysis

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Chinese Journal of Electronics 2014年第2期23卷 371-376页

作者： ZHAO Junhui GUAN Xin LI Xiuping ZENG Longji State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University National Mobile Communications Research Laboratory Southeast University Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences School of Electronic Engineering Beijing University of Posts and Telecommunications

The queuing performance of the cross-layer system with Space-time block code(STBC) over Multiinput-multi-output(MIMO) channel is analyzed. The adaptive modulation and coding(AMC) in physical layer and finite length of buffer in data-link layer are combined with this model. A simple cross-layer design and the queue state process are proposed based on finite state Markov channel model, which is to solve the service process. The proposed cross-layer design is also incorporated with STBC to further improve the system performance. Simulation results illustrate the dependence of system performance on various parameters, and quantify the performance gain due to cross-layer optimization. The adjustment of target packet loss rate of adaptive modulation coding in physical layer can maximize average throughput of the system,meanwhile a significant improvement of the system performance is brought.

关键词： adaptive modulation and coding Crosslayer design Multi-input-multi-output Space-time block coding

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Reinforcement Learning-Based adaptive modulation and coding for Efficient Underwater Communications

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IEEE ACCESS 2019年 7卷 67539-67550页

作者： Su, Wei Lin, Jiamin Chen, Keyu Xiao, Liang En, Cheng Xiamen Univ Key Lab Underwater Acoust Commun & Marine Informa Xiamen 361000 Fujian Peoples R China Xiamen Univ Dept Commun Engn Xiamen 361000 Fujian Peoples R China

In this paper, we propose a reinforcement learning-based adaptive modulation and coding scheme for underwater communications;more specifically, based on the network states such as the quality of service requirement of the sensing message, the previous transmission quality, and the energy consumption. This scheme applies reinforcement learning to choose the modulation and coding policy in a dynamic underwater communication system. We provide the performance bound of this scheme and perform experiments in both pool and sea environments. The experimental data were collected and post-processed. Compared with the benchmark schemes, this scheme can improve the throughputs and reduce the BER with less energy consumption.

关键词： Reinforcement learning adaptive modulation and coding underwater communication

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CNN-Based Joint SNR and Doppler Shift Classification Using Spectrogram Images for adaptive modulation and coding

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IEEE TRANSACTIONS ON COMMUNICATIONS 2021年第8期69卷 5152-5167页

作者： Kojima, Shun Maruta, Kazuki Feng, Yi Ahn, Chang-Jun Tarokh, Vahid Chiba Univ Grad Sch Engn Chiba 2638522 Japan Tokyo Inst Technol Acad Super Smart Soc Tokyo 1528552 Japan Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA

This paper proposes a novel convolutional neural network (CNN) based joint classification method to characterize the signal-to-noise power ratio (SNR) and Doppler shift using spectrogram images, in order to enable efficient adaptive modulation and coding (AMC) designs. It is necessary to maintain high communication performances even in stringent environments where transceivers move at high speed due to the diversification of wireless applications. To optimize the transmission rate in such dynamic environments, AMC scheme is known to be effective. AMC is generally designed based on feedback information (FBI) such as the SNR and Doppler shift acquired on the receiving side. Here, the challenge is an increase in calculation burden, processing delay and estimation accuracy of the FBI. We focused on the spectrogram which is composed of power values in the time and frequency domains. Its two-dimensional fluctuation represents the Doppler shift as well as noise values. In the proposed method, such key information for AMC can be simultaneously extracted from a single spectrogram via a trained CNN. Therefore it is expected to contribute to reducing the computational burden and speeding up the signal processing. Simulation results are presented to demonstrate that the proposed method achieves better performance than traditional methods.

关键词： Signal to noise ratio Estimation Doppler shift OFDM Spectrogram Channel estimation Receivers SNR estimation Doppler shift estimation convolutional neural network adaptive modulation and coding

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