Adaptive Wireless Communication Research Articles

End-to-end learning of adaptive coded modulation schemes for resilient wireless communications

Adaptive modulation and coding schemes play a crucial role in ensuring robust data transfer in wireless communications, especially when faced with changes or interference in the transmission channel. These schemes involve the use of variable coding rates, which can be achieved normally through code puncturing or shortening, and have been adopted in 4G and 5G communication standards. In recent works, auto-encoders for wireless communications have demonstrated the ability to learn short code representations that achieve gains over conventional codes. Such a methodology is attractive as it can learn optimal representations under a variety of channel conditions. However, due to its structure the auto-encoder does not currently support multiple code rates with a single model. This article draws upon the discipline of multi-task learning, as it applies to deep learning and therefore devises a branching architecture for the auto-encoder and custom training algorithm in training transmitter and receiver for adaptive modulation and coding. In this article we aim to demonstrate improvements in Block Error Rate over conventional methods in the Additive White Gaussian Noise channel, and to analyse the performance of the model under Rayleigh fading channels without retraining the auto-encoder on the new channel. This article demonstrates a novel approach towards training auto-encoder models to jointly learn adaptive modulation and coding schemes framed as a multi-task learning problem. The research outcomes extend end-to-end learning approaches to the design of adaptive wireless communications systems.

Reconfigurable Intelligent Surfaces for Beamforming in Upcoming Wireless Communications

Reconfigurable Intelligent Surfaces (RIS), also known as Intelligent Reflecting Surfaces (IRS), represent a groundbreaking advancement in wireless communication technology, enabling unprecedented control over electromagnetic (EM) wave propagation. Composed of numerous passive or active elements constructed from metasurfaces, RIS can dynamically alter their electromagnetic responses to optimize signal reflection, refraction, and scattering. These elements, capable of manipulating the phase, amplitude, and polarization of incoming waves, are centrally controlled through sophisticated algorithms that adapt to real-time environmental changes and communication requirements. RIS technology promises significant improvements in wireless communication by extending coverage, enhancing signal quality, managing interference, boosting energy efficiency, and improving security. Additionally, RIS can facilitate precise localization and sensing applications. Despite the high initial implementation costs and the need for complex control mechanisms and infrastructure compatibility, the potential benefits of RIS in creating efficient, secure, and adaptive wireless communication environments underscore its transformative impact on the field.

Adaptive Wireless Power Transfer and Backscatter Communication for Perpetual Operation of Wireless Brain–Computer Interfaces

Adaptive Wireless Power Transfer and Backscatter Communication for Perpetual Operation of Wireless Brain–Computer Interfaces

An intelligent adaptative architecture for wireless communication in complex scenarios

This paper discusses a communication node architecture that can intelligently adapt to the unknown and possible confrontation-communication environment. The architecture includes three core functions: communication environment understanding, communication waveform adaptation, and learning and evolution. To support these functions, it also provides a hardware platform that integrates the capabilities of communication and computation. The proposed intelligent adaptive architecture supports the continuous accumulation and evolution of knowledge bases of communication environments, communication waveforms, and the match between them. Through online waveform reconfiguration, communication nodes can adapt to typical communication scenarios and unknown environments, thus support the sustainable development of intelligent communication. Furthermore, this paper summarizes the applications of reinforcement learning, online learning, and transfer learning in intelligent adaptive wireless communications, also providing a typical example of the application of machine learning to the channel estimation process.

Design of an adaptive wireless communication system for mine hoist

Design of an adaptive wireless communication system for mine hoist

Tensor Communication Waveform Design With Semi-Blind Receiver in the MIMO System

A flexible mathematical framework for adaptive wireless communication waveform design is of importance for the implement of the cognitive radio-based software defined radio (CR-based SDR). As one of the popular models, the “spectrally modulated spectrally encoded” (SMSE) was proposed to tackle this problem but it cannot be trivially applied to the (massive) multiple input multiple output (MIMO) systems. In this paper, we extend the useful SMSE model into MIMO systems. Inspired by the tensor technique in signal processing and machine learning, we reformulate the desired waveforms as a higher-order tensors, of which the modes correspond to various modulation parameters such as coding chips, frequency and antennas. Beside the waveform design model, we further propose a new semi-blind receiver for the new model. Due the uniqueness of the applied tensor decomposition, we proved that the proposed receiver can jointly estimate the user symbols and channel state information without the aid of pilot sequences. Experimental results demonstrate the effectiveness of the proposed model in various communication scenes and outperforms the baseline systems. approximately 3 dB compared with the ideal receiver.

Neural Network-Based Fading Channel Prediction: A Comprehensive Overview

By adapting transmission parameters such as the constellation size, coding rate, and transmit power to instantaneous channel conditions, adaptive wireless communications can potentially achieve great performance. To realize this potential, accurate channel state information (CSI) is required at the transmitter. However, unless the mobile speed is very low, the obtained CSI quickly becomes outdated due to the rapid channel variation caused by multi-path fading. Since outdated CSI has a severely negative impact on a wide variety of adaptive transmission systems, prediction of future channel samples is of great importance. The traditional stochastic methods, modeling a time-varying channel as an autoregressive process or as a set of propagation parameters, suffer from marginal prediction accuracy or unaffordable complexity. Taking advantage of its capability on time-series prediction, applying a recurrent neural network (RNN) to conduct channel prediction gained much attention from both academia and industry recently. The aim of this article is to provide a comprehensive overview so as to shed light on the state of the art in this field. Starting from a review on two model-based approaches, the basic structure of a recurrent neural network, its training method, RNN-based predictors, and a prediction-aided system, are presented. Moreover, the complexity and performance of predictors are comparatively illustrated by numerical results.

Number of Transmit Antennas Detection Using Time-Diversity of the Fading Channel

Detection of the number of transmit antennas plays an important role in the design of adaptive multiantenna wireless communication systems. This paper develops a detection algorithm based on second- and fourth-order statistics of the received signal and time-varying nature of the wireless channel. In contrast to existing feature-based algorithms, the proposed algorithm does not require a priori information about the transmitted signals, such as coding scheme, modulation type, and pilot patterns. Unlike information-theoretic algorithms, it does not require the number of receive antennas to be larger than that of transmit antennas. In fact, the proposed algorithm is capable of operating with a single receive antenna even for large numbers of transmit antennas. The performance analysis of the proposed algorithm is provided, and the results are verified through simulations. The algorithm exhibits a good performance over a wide range of signal-to-noise ratios, and is robust to the carrier frequency and timing offsets.

A Proposal for Applying Adaptive Wireless Communication System for Smart Factory

Activities to deploying devices that connect Internet, said Internet of Things in the industrial domain are accelerating to improve efficiency, prevent down time led by organizations such as Industry 4.0 and Industrial InternetConsortium. Moreover a trend in industrial domain that manufactures have to provide various and small amount of products let manufactures reorganize their manufacturing facilities frequently. In often the case, the most costlyportion of the reorganization is re-cabling cost. Basing on this background, wireless communications are highly desired especially devices that can operate without power line. In this study, we propose a wireless communicationsystem that configure properties of the system such as carrier wave frequency, bandwidth, modulation autonomously depending on application requirements and circumstance of radio wave propagation.

Lightweight QoE Driven and Invulnerability Guarantee Opportunistic Control Scheme for Wireless Sensor Networks

This paper proposed the lightweight QoE driven adaptive invulnerability wireless communication control method, including the wireless communication terminal equipment with invulnerability antenna. According to the quality of wireless network channel quality, the lightweight QoE driven scheme was developed. According to user needs, the quality of the network, survivable ability of wireless communication terminal and wireless communication survivability requirements, we proposed three matching rules by considering the wireless hop number, data size and life cycle. The experiments demonstrated that the proposed scheme can optimize wireless communication terminal equipment and wireless opportunistic communication network construction, guarantee the user experience quality and improve wireless communication network survivability.

Adaptive wireless communications under competition and jamming in energy constrained networks

We propose a framed slotted Aloha-based adaptive method for robust communication between autonomous wireless nodes competing to access a channel under unknown network conditions such as adversarial disruptions. With energy as a scarce resource, we show that in order to disrupt communications, our method forces the reactive adversary to incur higher energy cost relative to a legitimate node. Consequently, the adversary depletes its energy resources and stops attacking the network. Using the proposed method, a transmitter node changes the number of selected time slots and the access probability in each selected time slot based on the number of unsuccessful transmissions of a data packet. On the receiver side, a receiver node changes the probability of listening in a time slot based on the number of unsuccessful communication attempts of a packet. We compare the proposed method with two other framed slotted Aloha-based methods in terms of average energy consumption and average time required to communicate a packet. For performance evaluation, we consider scenarios in which: (1) Multiple nodes compete to access a channel. (2) Nodes compete in the presence of adversarial attacks. (3) Nodes compete in the presence of channel errors and capture effect.

Toward Optimal Adaptive Wireless Communications in Unknown Environments

Designing efficient channel access schemes for wireless communications without any prior knowledge about the nature of environments has been a very challenging issue, especially when the channel states distribution of all spectrum resources could be entirely or partially stochastic and/or adversarial at different time and locations. In this paper, we propose an adaptive channel access algorithm for wireless communications in unknown environments based on the theory of multi-armed bandits (MAB) problems. By automatically tuning two control parameters, i.e., learning rate and exploration probability, our algorithms are capable of finding the optimal channel access strategies and achieving the almost optimal learning performance over time under our defined four typical regimes for general unknown environments, e.g., the stochastic regime where channels follow some unknown i.i.d process, the adversarial regime where all channels are suffered by adversarial jamming attack, the mixed stochastic and adversarial regime where a subset of channels are attacked and the contaminated stochastic regime where occasionally adversarial events contaminate the stochastic channel process, etc. To reduce the implementation time and space complexity, we further develop an enhanced algorithm by exploiting the internal structure of the selection of channel access strategy. We conduct extensive simulations in all these regimes to validate our theoretical analysis. The quantitative performance studies indicate the superior throughput gain and the flexibility of our algorithm in practice, which is resilient to both oblivious and adaptive jamming attacks with different intelligence and any attacking strength that ranges from no-attack to the full-attack of all spectrum resources.

Performance of capacity-based adaptive STBC-VBLAST MIMO wireless communication

In this paper, an adaptive STBC-VBLAST transmission approach based on capacity is proposed. The scheme compares the capacity of STBC and VBLAST, selects the higher capacity MIMO mode and feedback its decision to the transmitter with one extra signalling bit. The input information are modulated using QPSK or 16 QAM or 64 QAM modulator and modulated information are further encoded using STBC or VBLAST and then split into n streams which are simultaneously transmitted through N transmit antennas. The simulation results show that the proposed scheme can provide higher capacity always by using STBC or VBLAST adaptively.

The Research on the Police Adaptive Wireless Communications

Most Current researches about the police adaptive wireless communication are concentrated on the area of the time-invariant channel model, which is not fit to the requirement of police application. This paper designed an time-variant ISI channel model, according to the characteristics of police wireless communication. And analyzed the performance of the LMS and the RLS algorithms in DFE structure adaptive equalizers, under the time-variant ISI channel model. Simulation shows that the designed adaptive equalizers obtained excellent performance.

WCS: The Adaptive Wireless Communication Strategy for Mobile Electronic Commerce

Mobile e-business, with a full use of its mobility, makes information exchange and commercial transaction anytime anywhere become possible. But in the transmission technology and terminal handling ability, there is a huge gap to the traditional e-commerce. According to the existing wireless network communication technology, this paper introduces a new communication control algorithm to the mobile e-commerce transmission control. This algorithm can adjust data sending time according to the user’s needs and the constant change in the wireless communication and channels status. In this way, it can reduce the number of redundant data and network energy consumption, and makes the fusion between network and technique under the time requirements become possible.

Channel Estimation and Prediction Based Adaptive Wireless Communication Systems

Channel Estimation and Prediction Based Adaptive Wireless Communication Systems

Degrees of freedom for energy savings in practical adaptive wireless systems

We present a new design concept for adaptive wireless communications with new trade-offs between system performance and energy consumption. The system performance, in terms of bit error rate, outage probability, and achieved spectral efficiency, depends on constellation signaling, applied diversity, and channel estimation. Resources dedicated to channel estimation and feedback traffic contribute to the overall system and network energy consumption, and the resulting CO2 emission. We consider the trade-offs among different methodologies and parameters toward an energy-efficient green communication system design. Below, we discuss the degrees of freedom in the design of communications systems with imperfect channel estimation and diversity, and investigate their energy saving options. We present the case studies of single- and multicarrier systems applying both margin-adaptive and rate-adaptive pilot-assisted transmission.

Cross Layer Considerations for an Adaptive OFDM-Based Wireless Communication System

Future applications require high, but variable data rates and different quality of services (QoS) which is a real challenge for the communication system design. Additionally, the broadband radio channel can be assumed to be frequency selective and time variant, which means the transmission performance varies over time and frequency. The OFDM transmission technique is very flexible in adapting the transmission parameters to the current channel situation and to the application-specific requirements. This kind of flexibility will be applied to solve the technical tasks in the design procedures of future communication systems.

The rapidly deployable radio network

The rapidly deployable radio network (RDRN) is an architecture and experimental system to develop and evaluate hardware and software components suitable for implementing mobile, rapidly deployable, and adaptive wireless communications systems. The driving application for the RDRN is the need to quickly establish a communications infrastructure following a natural disaster, during a law enforcement activity, or rapid deployment of military force. The RDRN project incorporates digitally controlled antenna beams, programmable radios, adaptive protocols at the link layer, and mobile node management. This paper describes the architecture for the RDRN and a prototype system built to evaluate key system components.