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By adjusting the propagation environment using reconfigurable reflecting elements, intelligent reflecting surfaces (IRSs) have become potential techniques used to improve the efficiency of wireless communication networks. In IRS-assisted communication systems, accurate channel estimation is crucial for optimizing signal transmission and achieving high spectral efficiency. As mobile data traffic continues to surge and the demand for high-capacity and low-latency wireless connectivity grows, IRSs are becoming pivotal technologies in the development of next-generation communication networks. IRSs offer the potential to revolutionize wireless propagation environments, improving network capacity and coverage, particularly in high-frequency wave scenarios where traditional signals encounter obstacles. Amidst this evolving landscape, machine learning (ML) emerges as a powerful tool to harness the full potential of IRS-assisted communication systems, particularly given the escalating computational complexity associated with deploying and operating IRSs in dynamic environments. This paper presents an overview of preliminary results for IRS-assisted communication using recurrent neural networks (RNNs). We first implement single- and double-layer LSTM, BiLSTM, and GRU techniques for an IRS-based communication system. In the next phase, we explore a hybrid approach, combining different RNN techniques, including LSTM-BiLSTM, LSTM-GRU, and BiLSTM-GRU, as well as their reverse configurations. These RNN algorithms were evaluated with respect to bit error rate (BER) and symbol error rate (SER) for IRS-enhanced communication. According to the experimental results, the BiLSTM double-layer model and the BiLSTM-GRU combination demonstrated the highest BER and SER accuracy compared to other approaches. [ABSTRACT FROM AUTHOR]

The reconfiguration of wireless channels with reconfigurable reflecting surface (RIS) technology offers new design options for future wireless networks. Due to its high altitude and increased probability of establishing line-of-sight linkages with ground source/destination nodes, aerial RIS (ARIS) has greater deployment flexibility than traditional terrestrial RIS. It also provides a wider-view signal reflection. To leverage the advantages of ARIS-enabled systems, this paper defines air-to-ground linkages via Nakagami-m small-scale fading and inverse-Gamma large-scale shadowing, considering realistic composite fading channels. To construct a tight approximate closed-form formula for the outage probability (OP), a new mathematical framework is proposed. Additionally, a deep-learning-based system called the BiLSTM model is deployed to evaluate OP performance in the 3D spatial movement of the ARIS system. In the offline phase, the proposed model is trained with real-value channel state estimation sets and enhances OP performance in the online phase by learning channel information in a bidirectional manner. Simulation results demonstrate that the proposed BiLSTM model outperforms all other models in analyzing OP for the ARIS system. [ABSTRACT FROM AUTHOR]

The intelligent reflecting surface (IRS) is a two-dimensional (2D) surface with a programmable structure and is composed of many arrays. The arrays are used to supervise electromagnetic wave propagation by altering the electric and magnetic properties of the 2D surface. IRS can influentially convert wireless channels to very effectively enhance spectral efficiency (SE) and communication performance in wireless systems. However, proper channel information is necessary to realize the IRS anticipated gains. The conventional technique has been taken into consideration in recent attempts to fix this issue, which is straightforward but not ideal. A deep learning model which is called the long short-term memory (Bi-LSTM) model can tackle this issue due to its good learning capability and it plays a vital role in enhancing SE. Bi-LSTM can collect data from both forward and backward directions simultaneously to provide improved prediction accuracy. Because of the tremendous benefits of the Bi-LSTM model, in this paper, an IRS-assisted Bi-LSTM model-based multi-user multiple input single output downlink system is proposed for SE improvement. A Wiener filter is used to determine the optimal phase of each IRS element. In the simulation results, the proposed system is compared with other DL models and methods for the SE performance evaluation. The model exhibits satisfactory SE performance with a different signal-to-noise ratio compared to other schemes in the online phase. [ABSTRACT FROM AUTHOR]

The metaverse is emerging as a next-generation internet paradigm that will enhance human interaction and connectivity. Digital twinning, a fundamental strategy used in the metaverse, allows for the virtualization of real-world items, people, actions, and settings. A virtual world called the metaverse is built on a variety of technologies. Wireless communication is an important part of these technologies. In particular, wireless 6G communication can be essential for the growth of the metaverse. In line with the goal of achieving higher rates in the next-generation wireless network for the metaverse, in this paper, a novel conceptualization of intelligent reflecting surface (IRS)-assisted multiple-input single output-based wireless communication in physical world environments is proposed. More specifically, this paper proposes that in the physical world, the IRS-assisted communication between a communication network and users can be reflected in the metaverse through the virtual world (such as digital avatars and the virtual environment). In the simulations, the bit-error rate and spectral efficiency of the receiver terminal were performed and calculated in the metaverse engine for future consideration. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) has emerged as a promising technology to enhance the spectral efficiency of wireless communication systems. However, if there are many obstacles between the RIS and users, a single RIS may not provide sufficient performance. For this reason, a double RIS-aided communication system is proposed in this paper. However, this system also has a problem: the signal is attenuated three times due to the three channels created by the double RIS. To overcome these attenuations, an active RIS is proposed in this paper. An active RIS is almost the same as a conventional RIS, except for the included amplifier. Comprehensively, the proposed system overcomes various obstacles and attenuations. In this paper, an active RIS is applied to the second RIS. To reduce the power consumption of active elements, a partially active RIS is applied. To optimize the RIS elements, the sum of the covariance matrix is found by using channels related to each RIS, and the right singular vector is exploited using singular value decomposition for the sum of the covariance matrix. Then, the singular value of the sum of the covariance value is checked to determine which element is the active element. Simulation results show that the proposed system has better sum rate performance compared to a single RIS system. Although it has a lower sum rate performance compared to a double RIS with fully active elements, the proposed system will be more attractive in the future because it has much better energy efficiency. [ABSTRACT FROM AUTHOR]

An intelligent reflecting surface (IRS) is a programmable device that can be used to control electromagnetic waves propagation by changing the electric and magnetic properties of its surface. Therefore, IRS is considered a smart technology for the sixth generation (6G) of communication networks. In addition, machine learning (ML) techniques are now widely adopted in wireless communication as the computation power of devices has increased. As it is an emerging topic, we provide a comprehensive overview of the state-of-the-art on ML, especially on deep learning (DL)-based IRS-enhanced communication. We focus on their operating principles, channel estimation (CE), and the applications of machine learning to IRS-enhanced wireless networks. In addition, we systematically survey existing designs for IRS-enhanced wireless networks. Furthermore, we identify major issues and research opportunities associated with the integration of IRS and other emerging technologies for applications to next-generation wireless communication. [ABSTRACT FROM AUTHOR]

A cell-free massive multiple input multiple output (MIMO) system is an attractive network model that is in the spotlight in 5G and future communication systems. Despite numerous advantages, the cell-free massive MIMO system has a problem in that it is difficult to operate in reality due to its vast amount of calculation. The user-centric cell-free massive MIMO model has a more feasible and scalable benefit than the cell-free massive MIMO model. However, this model has the disadvantage that as the number of users in the area increases, there are users who do not receive the service. In this paper, the proposed scheme creates connections for unserved users under a user-centric scheme without additional access point (AP) installation and disconnection for existing users. A downlink user-centric cell-free massive MIMO system model in which the APs are connected to the central processing unit (CPU) and the APs and users are geographically distributed is considered. First, the downlink spectral efficiency formula is derived and applied to the user-centric cell-free massive MIMO system. Then, the proposed scheme and power control algorithm are applied to the derived formula. The simulation results show that the unserved users within the area disappear by using the proposed scheme, while the bit error rate (BER) performance and sum rate improve compared to the existing scheme. In addition, it is shown that the proposed scheme works well even with a very large number of users in the area, and a significant service performance improvement for the worst 10% of users and the overall improvement of per-user throughput for the bottom 70% of users are ensured. [ABSTRACT FROM AUTHOR]

This paper proposes the Internet connectivity of RF-powered devices in the backscatter system. The RF-powered devices do not use a battery and charge energy by harvesting from ambient RF signals of TV, a cellular phone and Wi-Fi devices. The Internet connectivity of the RF-powered devices in the backscatter system is very useful in Internet of things technology because the RF-powered devices which are called to a tag have a small size by the harvesting from ambient RF signals without a battery. This paper proposes a method improving the communication performance of the Wi-Fi backscatter system by applying the cooperative communication scheme. [ABSTRACT FROM AUTHOR]

In a wireless communication system, the performance is decreased by various interference and disturbance elements. In order to decrease the influence by these elements, the various schemes have been studied. In this paper, the method mitigating inter-cell interference (ICI) is proposed when a mobile user is located in the cell edge. ICI is one reason among the reasons of the performance reduction. The proposed scheme constructs the cooperative communication system and suggests the signal transmission method using pre-coding vectors. The proposed scheme can provide improved performance when the mobile user is located in the cell edge. [ABSTRACT FROM AUTHOR]

In this paper, the cellular system and broadcasting system use a cooperative transmission scheme. The conventional scheme is not consider the condition of a channel between a cellular base station (CBS) and a destination user. In this conventional scheme, two CBSs communicate with the user by the cooperative transmission scheme when the user is located in the cell edge. If CBS is distant from a user and the channel condition is poor, the performance of communication is degraded. The proposed scheme using the relay between CBS and the user located in the edge of CBSs improves the performance of the communication when the channel state between CBS and the user is bad. Also, space time block code and cyclic delay diversity scheme are used for the reliable transmission in the proposed scheme. The proposed scheme using the relay achieves good BER and throughput performance. Through the simulation, it is confirmed that the proposed scheme is better than the conventional scheme. [ABSTRACT FROM AUTHOR]

In this paper, the hierarchical space time cyclic delay diversity (H-STCDD) scheme is proposed. Proposed scheme uses hierarchical modulation and achieves approximately full rate. It also uses a cyclic delay diversity scheme, which improves the benefit of channel coding particularly in high SNR environment between source to relay and source to destination. According to simulation result, proposed scheme has up to 2.2 dB better BER performance than conventional cooperative scheme at BER of 10 and has similar BER performance with the STCDD scheme particularly in high SNR environment between source to relay and source to destination. Throughput of the proposed scheme is better than those of other cooperative schemes. Therefore proposed scheme is more efficient than other cooperative scheme and can be efficiently used in high SNR environment between source to relay and source to destination. [ABSTRACT FROM AUTHOR]

A combining of MIMO signal processing with OFDM is regarded as a promising solution of enhancing the performance of next generation wireless system. Therefore, in the paper, an OFDM-based wireless system employing layered space-time architecture is considered for a high-rate transmission. With an emphasis on a preamble design for multi-channel separation, we address a channel estimation based on the time-domain windowing and its imperfectness in MIMO-OFDM system. By properly designing each preamble for multiple antennas to be orthogonal in the time domain, the channel estimation can be executed based on semi-blind processing in the case of more than two transmitting antennas. And also we evaluate PAR performance in the MIMO-OFDM system using the SLM and PTS approaches. The investigated SLM and PTS schemes for MIMO-OFDM signals select the transmitted sequence with lowest average PAR over all transmitting antennas and retrieve the side information very accurately at the expense of a slight degradation of the PAR performance. The low probability of false side information can improve the overall detection performance of the MIMO-OFDM system with erroneous side information compared to the ordinary SLM and PTS approaches, respectively. Also, we provide closed form of the average BER performance in MIMO-OFDM system using analytic approach. [ABSTRACT FROM AUTHOR]