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This paper presents a simplified joint synchronization scheme for the integer carrier frequency offset and physical cell identity using a primary synchronization signal (PSS) in 5G new radio (NR) communication systems. We demonstrate the efficiency of our proposed NR-PSS synchronization scheme by deriving its simplified implementation, which exploits the near-zero autocorrelation feature between cyclically shifted NR-PSS symbols. As a figure of merit, we compute the probability of detection failure of the proposed NR-PSS synchronization scheme and validate its accuracy via simulations. To illustrate the benefits and limitations of the proposed NR-PSS synchronization scheme, we compare it with the conventional NR-PSS synchronization scheme, considering factors such as detection performance and computation complexity. Numerical results indicate that, regardless of the channel environment, the proposed NR-PSS synchronization scheme achieves a significant reduction in arithmetic complexity while maintaining the same detection capability as existing NR-PSS synchronization schemes. [ABSTRACT FROM AUTHOR]

Synchronization is a challenging issue in vehicle-to-everything (V2X) cellular communication, especially when V2X devices need to directly communicate with each other outside the network coverage area. By adopting the maximum likelihood principle, we propose joint detection of the sidelink secondary synchronization signal (SL-SSS) and carrier frequency offset (CFO) in a V2X system using 5G new radio sidelink. We formulate an effective joint coherent synchronization scheme for cellular V2X applications by decoupling the estimation of the sidelink identity and CFO, which requires a priori knowledge of channel state information. To verify the feasibility of the proposed detection scheme, we derive a simplified implementation of the proposed SL-SSS detector and a closed-form expression for the detection probability. Simulation results demonstrate that the proposed SL-SSS detector exhibits either comparable performance in terms of detection probability or reduced complexity when compared with conventional SL-SSS detectors. Using the proposed method in the cellular V2X system enables V2X devices to achieve robust synchronization with reduced power consumption during the initial synchronization procedure, while also offering valuable insights for designing a simple, efficient sidelink synchronization receiver. [ABSTRACT FROM AUTHOR]

This paper presents a novel formulation for detecting the secondary synchronization signal in a narrowband Internet of Things communication system. The proposed approach is supported by a noncoherent algorithm that eliminates the need for channel information. A robust joint synchronization scheme is developed by decoupling the estimations of the physical cell identity and the carrier frequency offset. We derive the detection probability of the proposed physical cell identity detector and the mean squared error of the carrier frequency offset estimator, demonstrating their accuracy through simulation results. The performance of the proposed detection scheme is compared with that of existing detection schemes in terms of both estimation accuracy and computational complexity. Experimental results confirm that the proposed synchronization method exhibits superior performance while maintaining relatively lower complexity compared with benchmark methods. [ABSTRACT FROM AUTHOR]

Narrowband Internet of Things (NB-IoT) is one of the low-power wide-area network technologies that aim to support enormous connection, deep coverage, low power consumption, and low cost. Therefore, low cost of implementation and maintenance is one of the key challenges of NB-IoT terminals. This paper presents a low-complexity formulation for narrowband secondary synchronization signal (NSSS) detection in the NB-IoT system, supported by a coherent algorithm that requires a priori knowledge of the channel. By exploiting a symmetric conjugate feature of the NSSS sequence, a joint physical cell ID and radio frame number detection method with low complexity is proposed for coherent detection. The probability of erroneous detection of the presented NSSS detection method is computed, and the analytical model is verified by means of simulation. Numerical experiments will demonstrate that the proposed detection scheme remarkably reduces the computational complexity with almost the same detection ability compared to the existing detection scheme. [ABSTRACT FROM AUTHOR]

In this paper, a complexity-effective integer carrier frequency offset (IFO) and primary synchronization signal (PSS) detection scheme is proposed for 5G new radio systems. To estimate the IFO without any prior information about the PSS, the proposed detector uses the fact that three PSS sequences are cyclic-shifted versions of each other, which enables sequential detection of IFO and PSS. Both theoretical and simulation results are presented to verify the effectiveness of the proposed synchronization scheme. It is shown that the proposed scheme achieves a considerable complexity reduction while suffering from only slight degradation in the detection performance, compared to the conventional scheme. [ABSTRACT FROM AUTHOR]

The integrated services digital broadcasting-terrestrial (ISDB-T) system provides the interesting advantages of hierarchical transmission and partial reception using band segmented transmission orthogonal frequency division multiplexing scheme. In ISDB-T, the hierarchical configuration varies depending on whether a segment is modulated coherently or differentially. Thus, it is important to accomplish frequency synchronization regardless of segment type. For this purpose, an effective weighted least-squares (WLS) carrier frequency synchronization method is presented using transmission and multiplexing configuration control (TMCC) and auxiliary channel (AC) in a blind manner. Thus, the proposed estimation scheme is performed without resorting to a priori knowledge on segment type that can be known after correct TMCC decoding. To eliminate bias caused by using non-uniformly distributed TMCC and AC subcarriers, an appropriate subset is selected to form the basis of robust WLS estimation. Extensive simulations are conducted to verify the efficiency of the proposed WLS estimation method and compare its performance with that of the conventional WLS estimation scheme. [ABSTRACT FROM AUTHOR]

The integrated services digital broadcasting-terrestrial (ISDB-T) system adopts band segmented transmission orthogonal frequency division multiplexing (BST-OFDM) to support different services using hierarchical transmission. In the ISDB-T system, in particular, a hierarchical configuration depends on modulation type used in OFDM segment, which has to be decoded at the receiver. Therefore, it is necessary to detect integer carrier frequency offset (IFO) before decoding the modulation type carried through transmission and multiplexing configuration control (TMCC) signal. To address this issue, an effective IFO estimation scheme is presented for the ISDB-T system, considering information-carrying TMCC signal as pilot symbol without any need of additional pilots. In order to verify the performance of the proposed estimation scheme, theoretical detection error rate is derived. It is shown from simulation results that the redundantly transmitted TMCC signal can be efficiently utilized for IFO detection, offering an approximate performance of maximum likelihood detection. [ABSTRACT FROM AUTHOR]

In this paper, an efficient symbol timing offset (STO) and sampling frequency offset (SFO) estimation scheme is proposed in an orthogonal frequency division multiplexing-based digital radio mondiale system using cyclic delay diversity. By using a periodic nature of channel transfer function, cyclic delay and pilot pattern with a maximum channel power are chosen, which aids to enable a robust estimation of STO and SFO against frequency selectivity of the channel. As a performance measure, the mean squared error of the proposed scheme is theoretically derived and is verified through simulations. By simulation results, the proposed estimation scheme is proved to profit from properly selected cyclic delay and pilot pattern, with a superior performance over the conventional estimation scheme. [ABSTRACT FROM AUTHOR]

Let Ω be a smoothly bounded pseudoconvex domain in Cn with one degenerate eigenvalue and assume that there is a smooth holomorphic curve V whose order of contact with bΩ at z0∈bΩ is larger than or equal to η. We show that the maximal gain in Hölder regularity for solutions of the ∂¯-equation is at most 1/η. [ABSTRACT FROM AUTHOR]

This paper proposes a novel hybrid beamforming and relay selection scheme for spectral efficiency maximization in a non-regenerative multi-relay multi-input multi-output (MIMO) system. The analog beamforming component in the radio-frequency (RF) domain must follow an element-wise constant modulus constraint, which makes the underlying design problem mathematically intractable and therefore, it is quite challenging to obtain the global optimal solution. To address this problem, phase-only precoding/combining matrices are derived by maximizing the end-to-end received signal-to-noise ratio (SNR) under transmit power constraint at the source and each relay node. This task is achieved by decomposing the original complicated optimization problem into two independent components. The first component designs the RF precoder/combiner at source and relay nodes by maximizing the received SNR at relay nodes. While the second component attempts to derive the analog precoder/combiner at relay nodes and destination by maximizing the received SNR at the destination. Digital baseband processing matrices are obtained by deriving the closed-form expression, which minimizes interference among different sub-channels. Finally, the relay selection is made by maximizing the overall SNR from the source to the destination. Computer simulations reveal that the performance of the proposed algorithm is close to its fully digital counterpart and approximately 6% higher than the specified relay-assisted hybrid beamforming techniques. Moreover, the proposed method achieves more than 15% higher performance in a sparse scattering environment when compared with the given relay selection techniques. [ABSTRACT FROM AUTHOR]

In this paper, we propose an improved sampling frequency offset (SFO) estimation scheme for orthogonal frequency division multiplexing (OFDM) based digital radio mondiale (DRM) broadcasting systems. To demonstrate the performance of the proposed frequency estimator, analytical expression of the mean square error (MSE) is derived and performances are compared with conventional pilot-assisted estimators. Based on the simulation and theoretical analysis, our proposed estimator shows an improved estimation performance compared to the conventional estimators. [ABSTRACT FROM AUTHOR]

Summary: This letter presents a statistical analysis of the decision threshold for a multi-carrier (MC) DS/CDMA acquisition system with a reference filter. The probabilities of detection and false alarm are derived, and the mean acquisition time is evaluated as a measure of the system performance. From the results, it is shown that in the performance analysis of the hybrid acquisition system with reference filtering, the statistical evaluation of the decision threshold seems more appropriate than the approximation of the decision threshold adopted in other schemes [7,8]. [Copyright &y& Elsevier]

Abstract: This paper investigates the peak-to-average power ratio (PAR) reduction scheme employing a simple symbol transform in OFDM-CDMA systems. This approach is very simple because of no additional complexity and works without restriction on the allocation of spreading code, maintaining an original transmission efficiency. Simulation results show that the investigated scheme gives an additional PAR reduction gain compared to the original OFDM and OFDM-CDMA signals, respectively. Also, this approach can provide the further PAR reduction by combining the partial transmit sequence (PTS) scheme, which is less complex compared to the ordinary PTS approach. [Copyright &y& Elsevier]

Wireless communication technologies have profoundly impacted the interconnectivity of mobile users and terminals. Nevertheless, the exponential increase in the number of users poses significant challenges, particularly in interference management, which is a major concern in wireless communication. Machine learning (ML) approaches have emerged as powerful tools for solving various problems in this domain. However, existing studies have not fully addressed the problem of interference management for wireless communication using ML techniques. In this paper, we explore the application of recurrent neural network (RNN) approaches to address co-channel interference in wireless communication. Specifically, we investigate the effectiveness of long short-term memory (LSTM), bidirectional LSTM (Bi-LSTM), and gated recurrent unit (GRU) network architectures in two different network settings. The first network comprises 10 connected devices, while the second network involves 20 devices. Our experimental results demonstrate that Bi-LSTM outperforms LSTM and GRU in terms of mean squared error, normalized mean squared error, and sum rate. While LSTM and GRU produce similar results, LSTM exhibits a marginal advantage over GRU. In addition, a combined RNN approach is also studied, and it can provide better results in dense networks. [ABSTRACT FROM AUTHOR]

In this paper, we address scheduling methods for queue stabilization and appropriate power allocation techniques in downlink dense user-centric scalable cell-free multiple-input multiple-output (CF-MIMO) networks. Scheduling is performed by the central processing unit (CPU) scheduler using Lyapunov optimization for queue stabilization. In this process, the drift-plus-penalty is utilized, and the control parameter V serves as the weighting factor for the penalty term. The control parameter V is fixed to achieve queue stabilization. We introduce the dynamic V method, which adaptively selects the control parameter V considering the current queue backlog, arrival rate, and effective rate. The dynamic V method allows flexible scheduling based on traffic conditions, demonstrating its advantages over fixed V scheduling methods. In cases where UEs scheduled with dynamic V exceed the number of antennas at the access point (AP), the semi-orthogonal user selection (SUS) algorithm is employed to reschedule UEs with favorable channel conditions and orthogonality. Dynamic V shows the best queue stabilization performance across all traffic conditions. It shows a 10% degraded throughput performance compared to V = 10,000. Max-min fairness (MMF), sum SE maximization, and fractional power allocation (FPA) are widely considered power allocation methods. However, the power allocation method proposed in this paper, combining FPA and queue-based FPA, achieves up to 60% better queue stabilization performance compared to MMF. It is suitable for systems requiring low latency. [ABSTRACT FROM AUTHOR]

Narrowband Internet of Things is one of the most promising technologies to support low cost, massive connection, deep coverage, and low power consumption. In this paper, a computationally efficient narrowband secondary synchronization signal detection method is proposed in the narrowband Internet of Things system. By decoupling the detection of complementary sequence and Zadoff–Chu sequence that make up the synchronization signal sequence, the search space of narrowband secondary synchronization signal hypotheses is reduced. Such a design strategy along with the use of the symmetric property of synchronization signals allows reduced-complexity synchronization signal detection in the narrowband Internet of Things system. Both theoretical and simulation results are provided to verify the usefulness of the proposed detector. It is shown via simulation results that the complexity of the proposed detection method is significantly reduced while producing some performance degradation, compared to the conventional detection method. [ABSTRACT FROM AUTHOR]

In the integrated services digital broadcasting-terrestrial (ISDB-T) system, the combination of digital terrestrial transmission and MPEG-4 advanced video coding (MPEG-4 AVC) has offered ways to provide a variety of digital high-definition television (HDTV) programs. Using band segmented transmission orthogonal frequency division multiplexing (BST-OFDM), the delivery of innovative video-on-demand and HDTV services is supported. To take full advantage of the attractive benefits of BST-OFDM, it is important to estimate integer frequency offset (IFO) without a priori knowledge on the segment type that is transmitted over transmission and the multiplexing configuration control (TMCC) signal. To address this issue, an efficient IFO detection method is proposed for the ISDB-T system employing BST-OFDM. To enable IFO detection independent of the segment type, information-bearing TMCC signals that are asymmetrically distributed in the frequency domain are used as pilot symbols. Numerical analysis is performed to present the relationship between error probability and design parameter. We show via the numerical results that the multiple transmitted TMCC information is efficiently used for blind estimation of the IFO, achieving robust estimation in the presence of the fractional frequency offset. [ABSTRACT FROM AUTHOR]

Recently, the application of digital cable transmission standards as a second generation digital transmission system for cable systems (DVB-C2) in addition to MPEG-2 video compression has offered ways to provide a variety of digital high definition television (HDTV) programs. In the DVB-C2 system, the use of an orthogonal frequency division multiplexing (OFDM) modulation enables the delivery of innovative video-on-demand (VOD) and HDTV services. In this paper, a computationally-efficientleast-squares estimation of carrier frequency offset and sampling frequency offset is proposed in the OFDM-based DVB-C2 system. To obtain the noise averaging effect in the synchronization process, we adopt a block-by-block correlation, where observation symbols within two correlation blocks are added and the result is correlated. The use of block-by-block correlation improves the estimation performance and relieves the computational overhead. To optimize the performance of the block-by-block estimation method, the mean squared error is theoretically calculated. It is confirmed from simulation results that the performance of the proposed method is enhanced with a low complexity, in comparison with the existing methods. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) is appealing for the provision of high spectral efficiency in digital terrestrial broadcast systems. To fully obtain its advantageous features, it is very important to remove the frequency mismatch between the transmitter and the receiver. In this paper, we present the performance analysis of joint estimation of carrier and sampling frequency offsets in the MIMO-OFDM-based advanced television systems committee (ATSC) 3.0 system. In the MIMO-OFDM ATSC system, the continual pilot (CP) is primarily utilized to perform frequency synchronization. To efficiently suppress an unwanted bias introduced by the presence of random-likely located CPs, an optimal pilot subset is selected to form the basis of least squares frequency-offset estimation. A closed-form mean squared error is derived in the context of MIMO-OFDM, considering the multipath fading channel. We show via computer simulations and numerical analysis that the proposed estimation method achieves higher estimation accuracy than the existing estimation method. [ABSTRACT FROM AUTHOR]

The HomePlug Green PHY (HomePlug GP) specification provides an attractive solution to enable smart grid power line communication (PLC) applications by using robust orthogonal frequency division multiplexing (ROBO) mode. This paper proposes a computationally efficient sampling frequency offset (SFO) estimation technique in the HomePlug GP system without relying on pilot symbols. For this purpose, the proposed estimation scheme utilizes the redundant information contained within the repeat coding in the HomePlug GP ROBO mode, thus eliminating the need of dedicated pilots. Computer simulations are conducted to assess the performance of the proposed SFO estimation scheme and to compare it with the conventional decision-directed (DD) estimation schemes. Simulations indicate that the repeat coded ROBO signals are effectively used for the proposed estimation scheme, which provides an affordable estimation accuracy while reducing the complexity compared to the conventional DD estimation schemes. [ABSTRACT FROM AUTHOR]

The integrated services digital broadcasting-terrestrial (ISDB-T) system is designed in order to accommodate high-quality video/audio and multimedia services, using band segmented transmission orthogonal frequency division multiplexing (BST-OFDM) scheme. In the ISDB-T system, the pilot configuration varies depending on whether a segment uses a coherent or differential modulation. Therefore, it is necessary to perform a joint estimation of carrier frequency offset (CFO) and sampling frequency offset (SFO) independent of the segment format in the ISDB-T system. The goal is to complete those synchronization tasks while considering an information-carrying transmission and multiplexing configuration control (TMCC) signal as pilot symbols. It is demonstrated through numerical simulations that the differential BPSK-modulated TMCC information can be efficiently used for a least-squares estimation of CFO and SFO, offering an acceptable performance. [ABSTRACT FROM AUTHOR]

Graph convolutional networks (GCNs) provide an advantage in node classification tasks for graph-related data structures. In this paper, we propose a GCN model for enhancing the performance of node classification tasks. We design a GCN layer by updating the aggregation function using an updated value of the weight coefficient. The adjacency matrix of the input graph and the identity matrix are used to calculate the aggregation function. To validate the proposed model, we performed extensive experimental studies with seven publicly available datasets. The proposed GCN layer achieves comparable results with the state-of-the-art methods. With one single layer, the proposed approach can achieve superior results. [ABSTRACT FROM AUTHOR]

The reconfigurable intelligent surface (RIS) is one of the most innovative and revolutionary technologies for increasing the effectiveness of wireless systems. Deep learning (DL) is a promising method that can enhance system efficacy using powerful tools in RIS-based environments. However, the lack of extensive training of the DL model results in the reduced prediction of feature information and performance failure. Hence, to address the issues, in this paper, a combined DL-based optimal decoding model is proposed to improve the transmission error rate and enhance the overall efficiency of the RIS-assisted multiple-input multiple-output communication system. The proposed DL model is comprised of a 1-dimensional convolutional neural network (1-D CNN) and a gated recurrent unit (GRU) module where the 1-D CNN model is employed for the extraction of features from the received signal with further process over the configuration of different layers. Thereafter, the processed data are used by the GRU module for successively retrieving the transmission signal with a minimal error rate and accelerating the convergence rate. It is initially trained offline using created OFDM data sets, after which it is used online to track the channel and extract the transmitted data. The simulation results show that the proposed network performs better than the other technique that was previously used in terms of bit error rate and symbol error rate. The outcomes of the model demonstrate the suitability of the proposed model for use with the next-generation wireless communication system. [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]

The reconfigurable intelligent surface (RIS) and rate-splitting multiple access (RSMA) are considered as promising technologies for the beyond Fifth-Generation (B5G) and Sixth-Generation (6G) wireless systems by controlling the propagation environment, which attenuates the transmitted signal, and by managing the interference by splitting the user message into common and private messages. Because conventional RIS elements have each impedance connected to the ground, the sum-rate performance improvement of the RIS is limited. Therefore, the new RISs, which have impedance elements connected to each other, have been proposed recently. To be more adaptive to each channel, the optimization of the grouping of the RIS elements is required. Furthermore, since the solution of the optimal rate-splitting (RS) power-splitting ratio is complex, the value should be simply optimized to be more practical in the wireless system. In this paper, the grouping scheme of the RIS elements according to the user scheduling and the solution of the RS power-splitting ratio based on fractional programming (FP) are proposed. The simulation results showed that the proposed RIS-assisted RSMA system achieved a high sum-rate performance compared to the conventional RIS-assisted spatial-division multiple access (SDMA) system. Therefore, the proposed scheme can perform adaptively for the channel and has a flexible interference management. Furthermore, it can be a more suitable technique for B5G and 6G. [ABSTRACT FROM AUTHOR]

A reconfigurable intelligent surface (RIS) has potential for enhancing the performance of wireless communication. A RIS includes cheap passive elements, and the reflecting of signals can be controlled to a specific location of users. In addition, machine learning (ML) techniques are efficient in solving complex problems without explicit programming. Data-driven approaches are efficient in predicting the nature of any problem and can provide a desirable solution. In this paper, we propose a temporal convolutional network (TCN)-based model for RIS-based wireless communication. The proposed model consists of four TCN layers, one fully connected layer, one ReLU layer, and lastly a classification layer. In the input, we provide data in the form of complex numbers to map a specified label under QPSK and BPSK modulation. We consider 2 × 2 and 4 × 4 MIMO communication using one base station and two single-antenna users. We have considered three types of optimizers to evaluate the TCN model. For benchmarking, long short-term memory (LSTM) and without ML are compared. The simulation results are conducted in terms of the bit error rate and symbol error rate which show the effectiveness of the proposed TCN model. [ABSTRACT FROM AUTHOR]

In this paper, we propose a low-complexity joint detection of sector cell index and integer carrier frequency offset for a long-term evolution downlink system. In order to implement a low-cost detection scheme, a primary synchronization signal used for joint parameter estimation is grouped into a number of subsets so that the pilots in each subset are strongly correlated. The estimation performance and the computational load of the proposed scheme are compared with those of the commonly used conventional detection scheme using a differential correlation to remove common channel effects. It is found that the proposed scheme can jointly detect the cell index and integer carrier frequency offset with higher accuracy and much lower complexity, compared with the conventional scheme. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) has contributed new unused spectrum in addition to the traditional radio frequency communication and can play a significant role in wireless communication. The adaptation of VLC technology enhances wireless connectivity both in indoor and outdoor environments. Multiple-input multiple-output (MIMO) communication has been an efficient technique for increasing wireless communications system capacity and performance. With the advantages of MIMO techniques, VLC can achieve an additional degree of freedom. In this paper, we systematically perform a survey of the existing work based on MIMO VLC. We categorize the types of different MIMO techniques, and a brief description is given. Different problem-solving approaches are given in the subsequent sections. In addition, machine learning approaches are also discussed in sufficient detail. Finally, we identify the future study direction for MIMO-based communication in VLC. [ABSTRACT FROM AUTHOR]

This paper proposes an improved pilot-based algorithm for joint estimation of carrier frequency offset (CFO) and sampling frequency offset (SFO) in ultrawideband orthogonal frequency division multiplexing (UWBOFDM) systems with cyclic delay diversity. By proper selection of cyclic delay time and a frequency band with maximum channel power, a joint estimation of CFO and SFO is derived. Via computer simulation and analysis, the proposed frequency estimator is shown to benefit from the properly selected delay parameter and frequency band. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has great potential to implement the fifth-generation (5G) requirements of wireless communication. For a NOMA traditional detection method, successive interference cancellation (SIC) plays a vital role at the receiver side for both uplink and downlink transmission. Due to the complex multipath channel environment and prorogation of error problems, the traditional SIC method has a limited performance. To overcome the limitation of traditional detection methods, the deep-learning method has an advantage for the highly efficient tool. In this paper, a deep neural network which has bi-directional long short-term memory (Bi-LSTM) for multiuser uplink channel estimation (CE) and signal detection of the originally transmitted signal is proposed. Unlike the traditional CE schemes, the proposed Bi-LSTM model can directly recover multiuser transmission signals suffering from channel distortion. In the offline training stage, the Bi-LTSM model is trained using simulation data based on channel statistics. Then, the trained model is used to recover the transmitted symbols in the online deployment stage. In the simulation results, the performance of the proposed model is compared with the convolutional neural network model and traditional CE schemes such as MMSE and LS. It is shown that the proposed method provides feasible improvements in performance in terms of symbol-error rate and signal-to-noise ratio, making it suitable for 5G wireless communication and beyond. [ABSTRACT FROM AUTHOR]

This paper proposes an effective cooperative communication scheme to obtain high reliability in a long-term evolution-advanced (LTE-A) uplink system. The proposed scheme constitutes the virtual multiple input multiple output antenna array by the cooperative communication scheme and suggests the transmission signal configuration applying spatial phase coding (SPC) with the modified hierarchical modulation. In the proposed transmission signal configuration, high diversity gain is provided by the SPC scheme and the data rate is improved by modified hierarchical modulation. The modified hierarchical modulation transforms the constellation of the conventional hierarchical-modulated signal in order to minimize the influence by noise in the proposed scheme. In the LTE-A uplink system, the proposed scheme is effective to a user equipment (UE) based on single carrier-frequency division multiple access because UE using only single antenna can obtain high reliability without additional antennas. [ABSTRACT FROM PUBLISHER]

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 evaluates the performance of a cell-specific reference signal (RS)-assisted residual carrier-frequency offset (CFO) detection scheme for a long-term evolution (LTE) downlink in a time-varying channel. Channel variations severely degrade the performance of OFDM by introducing both a complicated multiplicative distortion and an additive inter-carrier interference. Taking into consideration the effect of time-variant fading channels, an analytical closed-form expression of the mean square error (MSE) of the post-FFT CFO detection scheme is derived. The analytical expression is verified through simulations using the parameters of the LTE standard. [ABSTRACT FROM AUTHOR]

Cyclic delay diversity (CDD) is a simple transmit diversity technique for coded OFDM systems with multiple transmit antennas. However, high frequency selectivity caused by CDD degrades the performance of post- FFT estimation, i.e., integer frequency offset (IFO). This paper suggests a simple way of improving the performance of the IFO estimator based on the pilot subset partitioning which is designed to reduce the effect of frequency selective fading by adopting the CDD. By partitioning uncorrelated pilot subcarriers into subsets to satisfy high correlation, and performing frequency estimation for each pilot subset, a robust IFO estimation scheme is derived. The simulation results show that the proposed method can provide benefit to the overall system performance . [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]

The key features for future machine-type communication cellular systems facilitate low-power, low-cost, narrow-band, and wide-area systems. One of the challenging tasks to realize these requirements in machine-type communication cellular networks is a low-cost initial synchronization. To address this issue, this paper presents a reduced-complexity joint estimation of integer carrier frequency offset and cell identity for machine-type communication in the long-term evolution system. Using the conjugate property of a primary synchronization signal, joint search space of a number of hypotheses is reduced by two-thirds, facilitating low-complexity detection. The performance is assessed in terms of theoretical probability of detection failure. Simulation results confirm that the proposed estimation scheme achieves approximately the same performance as the conventional scheme with notably low complexity. [ABSTRACT FROM AUTHOR]

In this paper, we focus on improving the accuracy of frequency offset estimation for an orthogonal frequency-division multiplexing (OFDM) system under the conditions of the joint impairments in both carrier frequency offset (CFO) and in-phase/quadrature (I/Q) imbalance. To propose a robust CFO estimation scheme and to benchmark its performance, the performance of the conventional frequency estimation algorithm in the presence of I/Q imbalance is analyzed, and some modifications to the conventional estimation scheme are highlighted. We show via simulations that such a design achieves a remarkable robustness against I/Q imbalance; thereby, the proposed scheme can efficiently estimate the CFO, irrespective of the I/Q mismatch. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an improved and low-cost integer frequency offset (IFO) estimation method by partitioning pilot symbols effectively in an orthogonal frequency division multiplexing based digital radio mondiale (DRM) system. To this end, the time reference cell (TRC) symbol for frequency estimation is grouped into a number of pilot clusters, so that the TRC subcarriers in each cluster are closely spaced to show approximately frequencynonselective characteristics. The performance of the proposed IFO estimator is compared with that of the conventional estimator, and shows that the proposed technique can effectively achieve lower estimation errors in frequency offset estimation as well as can be implemented with reduced computational complexity. [ABSTRACT FROM AUTHOR]

A wireless body area network (WBAN) is a radio-frequency-based wireless communication technology that consists of a number of different sensor and actuator nodes interconnected with a body gateway. Considering the constrained resources in WBAN devices, simple and noise-robust synchronization algorithms are required. Frame synchronization and frequency offset estimation are extremely important in the design of a robust WBAN receiver. In this paper, a detection strategy such as frame synchronization and frequency estimation is described in the WBAN system, which can improve the receiver performance. In doing so, algorithms are designed or chosen for the frame detection, carrier frequency offset synchronization, and joint fine-time and phase-offset estimation by exploiting the spike-like property of the physical layer convergence protocol preamble and the frame structure in the WBAN system. The performance of the WBAN synchronization receiver is verified by computer simulation. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]