The rapid development of railways worldwide has generated significant attention toward high-speed train (HST) communications. Disruptive technologies for the sixth-generation network, such as cell-free massive multiple-input–multiple-output (mMIMO) and reconfigurable intelligent surface (RIS), are set to substantially enhance the data transmission rate in wireless communication systems. In this article, we leverage the potential benefits of cell-free mMIMO and irregular RIS to achieve the ultimate performance benchmark in HST networks. Specifically, we investigate a cell-free mMIMO system supported by irregular RIS with many low-cost reflecting elements, aiming to improve the weighted sum-rate (WSR) in HST communications. The deployment of irregular RIS allows signals to be transmitted through reflected links with additional degrees of freedom, and thus, a more diverse transmission is facilitated to enhance the received signal power and the system capacity. A joint optimization problem is then formulated to maximize the WSR, while satisfying the constraints on access point power. To address the problem characterized by nonconvexity and high complexity, an alternating optimization algorithm is proposed to iteratively optimize the RIS topology, the transmit beamforming, and the phase shifts. The corresponding subproblems are tackled by exploiting improved tabu search, projected subgradient, and nonmonotone accelerated proximal gradient methods, respectively. Extensive simulations confirm the significant advantages of irregular RIS configurations on the WSR.

In this paper, we investigate channel estimation in a reconfigurable intelligent surface (RIS) assisted multi-user network while taking the mobility of users into consideration. Based on a time-varying channel model, we utilize Kalman filter (KF) that is able to exploit temporal correlation to track cascaded channel. In order to maintain a relatively low pilot overhead, we present a multiple sub-phases based transmission protocol where the number of pilot sequences in each sub-phase is less than the number of users, i.e., pilot contamination exists. For the sake of practicality, we directly utilize discrete Fourier transform (DFT) matrix as phase shift matrix. We analyze normalized mean square error and provide some asymptotic results. A more practical scenario with hardware impairments (HWI) at the transceiver and the RIS is also considered. Since HWI is also part of the measurement matrix and is unknown to the base station, we propose a joint estimation of the channel and HWI. Under this joint estimation framework, the underlying state space model becomes nonlinear. We develop an extended KF (EKF) algorithm to tackle the nonlinearity through which the model can be linearized. Numerical results show that the proposed KF and EKF algorithms outperform benchmark schemes under various scenarios.

Full-duplex relays (FDRs) are widely used to expand wireless transmission distance between the source and the destination. The fundamental challenge of FDR transmission is how to deal with the residual self-interference (RSI) at the relay. In this paper, we present an equivalent channel model by treating the RSI as an infinite impulse response (IIR) channel. For this equivalent IIR channel model, a relay transmission scheme with a low complexity equalization method is designed. The length of the cyclic prefix (CP) in this scheme can be extremely short, thereby improving the spectral efficiency. This paper evaluates the signal to noise ratio (SNR) of the proposed scheme. Compared with traditional OFDM system which can only collect the energy wherein CP length, the proposed scheme can collect almost all the energy of the IIR channel without inter-symbol-interference (ISI). Simulation results show that the proposed scheme can outperform other existing schemes especially when the self-interference cancellation ability is insufficient.

Channel state information (CSI) is vital for massive multiple-input multiple-output (MIMO) systems to provide high channel capacity and energy efficiency. However, the massive antennas will lead to high feedback overhead in frequency division duplex (FDD) MIMO systems. Recent applications of recurrent neural networks have demonstrated promising results of feedback CSI compression but with tremendous complexity. The markovian-based framework reduces the overall complexity but owns the high complexity of the user equipment (UE), which is not suitable for practical deployment. In this work, we aim to reduce the complexity of UE and improve the reconstruction performance. Leveraging the channel temporal correlation, we propose two differential frameworks called DIFNet1 and DIFNet2 to improve feedback accuracy and efficiency. Moreover, We unfold the Iterative Shrinkage-Thresholding Algorithm (ISTA) to provide excellent reconstruction performance. Simulation results demonstrate that the proposed framework improves the reconstruction performance while greatly reducing the complexity of UEs.

In this paper, we investigate the joint beamforming design for access and fronthaul links in a user-centric network with full-duplex fronthaul. We formulate an optimization problem to maximize the network energy efficiency while guaranteeing fronthaul rate requirements. Particularly, the power consumed by self-interference cancellation at full-duplex access points (APs) is taken into consideration to comprehensively reflect the effect of full-duplex technology. Due to the non-convexity and the nonlinear fractional form of the formulated problem, we resort to the successive convex approximation method. The original problem is approximated as a convex second-order cone program. We then extend the study to the scenario of imperfect and partial channel state information (CSI). To avoid the intractable expression of the achievable rate in this case, we derive its lower bound for further beamforming design. Simulation results demonstrate the superiority of the proposed algorithm in terms of energy efficiency and power consumption under both CSI scenarios. For our considered full-duplex fronthaul networks, moderate maximum transmit power of macro base station (MBS) and APs is sufficient to obtain desired energy efficiency performance. Moreover, the lower bound is verified to be tight at the low-maximum power region.

Multi-sensor information fusion technology is an effective method for fire detection. However, in the underground road scenario, due to the closed environment and dispersed sensor layout, common fire detection data fusion methods have defects of poor detection timeliness and low accuracy. Therefore, this paper proposes a new fire detection scheme combining BP neural network and D-S evidence theory, and further puts forward a evidence correction method based on exponential entropy. We compare this method with common methods, and the experimental results show that the new method can detect the fire at the earliest in both open fire and smoldering fire scenes of underground roads, which improves the real-time performance and accuracy of fire detection.

In this paper, we investigate an energy-efficient beamforming design in a user-centric full-duplex backhauling network, where simultaneous transmission and reception on the same frequency band for access and backhaul links are enabled by full-duplex access points. Specifically, multicast transmission is adopted by macro base station and cooperative transmission is adopted by access points to serve users. We first formulate an optimization problem to maximize the network energy efficiency while taking the power consumed by self-interference cancellation at full-duplex access points into consideration. This problem is formulated as a nonlinear fractional programming and is transformed into an equivalent subtractive form by Dinkelbach method. The equivalent optimization problem is still non-convex. To make it more tractable, we first adopt semidefinite relaxation to remove part of non-convexity, and then adopt the successive convex approximation method to further deal with the rest of non-convex parts, and finally propose an iterative algorithm. Simulation results demonstrate the superiority of the proposed algorithm and provide insights into the design of full-duplex backhauling network.

In this paper, we investigate the resource allocation problem for a full-duplex network with machine-to-machine devices and cellular users. Our objective is to maximize the network sum rate while achieving individual quality-of-service (QoS) requirements, considering imperfect and partial channel state information. The sum rate maximization problem is formulated as a mixed-integer nonlinear programming problem. We decouple it into a subcarrier assignment subproblem and a power allocation subproblem to make it more tractable. The non-convex subcarrier assignment problem is transformed to a convex problem by applying majorization minimization method, and then solved by the interior-point method. While the power allocation problem is solved by applying the Lagrange dual method. Simulation results demonstrate the impact of channel estimation error on sum rate performance and the superiority of the proposed algorithm. Furthermore, the fairness is improved among users by QoS guarantee.

Abstract By exploiting a dimension called orbital angular momentum (OAM) modes, a new modulation scheme referred to as multi‐dimensional space–frequency‐mode hybrid modulation (SFMHM) is proposed in this paper, which aims to further improve the MIMO‐OFDM system's spectrum efficiency and meet the demand of the future wireless communication networks. The key idea of SFMHM is to map a block of information bits to two information‐carrying units: (1) symbols chosen from a constellation diagram, (2) the indices of a subset chosen from all combinations of antennas, OAM modes, and subcarriers. A mapping method with low complexity for SFMHM is presented in this paper, which can reduce the computational complexity of the transmitter significantly. Simulation results show that, in LOS channels, SFMHM systems can achieve better performance compared with traditional MIMO‐OFDM systems.

Abstract This paper presents a time slot‐split non‐orthogonal multiple access (TSS‐NOMA) scheme for full‐duplex (FD) cooperative communication systems to improve resource utilisation. Aiming at the problem of low bandwidth efficiency when pairing users, TSS‐NOMA divides a complete time slot into several parts to improve the pairing process. Users can occupy all bandwidths in different slots to reduce the waste of bandwidth resources. Unlike the scheme of forwarding a single signal, TSS‐NOMA decodes the information symbols of relay, and re‐encodes the messages through the new power allocation factors of successfully paired users. The hybrid symbols are sent to increase the proportion of central users' own signals received by themselves, thus improving the ergodic capacity of the system. To maximise the minimum achievable rate of the system, TSS‐NOMA optimises the power allocation at the base station, and the relay. The performance of TSS‐NOMA is verified by simulation, where numerical results show that this scheme can achieve higher spectral, and energy efficiency.

To enhance spectrum efficiency for the future Internet-of-Things, in this paper, we investigate the joint subcarrier and power allocation problem for a full-duplex network with machine-to-machine nodes and cellular nodes. We aim to maximize the network spectral efficiency while achieving individual quality-of-service (QoS) requirements, considering imperfect and partial channel state information. The spectral efficiency maximization problem is formulated as a mixed-integer nonlinear programming problem and proved to be NP-hard. To make it more tractable, we first solve the coupling between subcarrier assignment and power allocation variables by replacing the product of two variables with one auxiliary variable. We then relax the binary subcarrier assignment variables to integer variables and introduce penalty terms to penalize the objective function. Majorization minimization method is adopted to further handle the coupling between uplink and downlink due to full-duplex transmission. We prove that the proposed joint resource allocation scheme converges to local optimal solution. Simulation results demonstrate the impact of channel estimation error on spectral efficiency and the superiority of the proposed algorithm.

In this paper, a power allocation space-time coding scheme based on self-coding of residual loop interference (RLI) for two-way full-duplex (FD) amplify-and-forward (AF) relaying networks is proposed. In the proposed scheme, the relay first realizes a distributed space-time code by performing self-coding using the RLI at relay node after implementing some self-interference cancellation techniques. Then power allocation is performed between the terminals. With the proposed power allocation scheme, both amplifying factor and transmit powers of terminal nodes are jointly optimized under a total power constraint when estimated instantaneous channel state information is available. Simulation results show that the proposed scheme achieves performance improvement in an FD relaying system.

In this study, the authors propose a power allocation strategy for full‐duplex relay (FDR) networks, where two cases are considered according to whether the direct link is desired or not. The power allocation is studied in two scenes under the amplify‐and‐forward and decode‐and‐forward protocols, respectively. Aiming at maximising the system capacity, the authors derive the optimal power allocation strategy under the condition that the source and relay have the same maximum power constraint and the total power is limited. The effects of global and individual power constraints for FDR on system capacity are analysed. Simulations verify the theoretical analysis and indicate that the proposed power allocation strategy enhances the system performance greatly compared with uniform power allocation.

A new modulation scheme, referred to as space-frequency-mode multi-dimensional hybrid modulation (SFMHM), is proposed to be integrated with multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in this paper. The key idea of SFMHM is to map a block of information bits to two information carrying units: 1)symbols chosen from a constellation diagram and 2)a subset chosen from all possible combinations of antennas, orbital angular momentum (OAM) modes and subcarriers, which means that only a part of antennas, OAM modes and subcarriers will be activated at any given time. Specifically, the use of the second part will add three additional dimensions to conventional two-dimensional (2-D) amplitude/phase modulation techniques, which will improve the achievable rate significantly. For SFMHM scheme, we propose a computationally efficient mapping method by taking advantage of combinadic representation in combinatorial system, and we further study the achievable rate. Finally, simulation results show that, for the same configuration at the transmitter, SFMHM can achieve higher rate compared with conventional MIMO-OFDM.

In this paper, we study the self-interference (SI) cancellation of full-duplex massive MIMO relay systems over Rician fading channels. The decode-and-forward protocol is adopted at the relay station where the channel state information (CSI) is assumed to be imperfect. We demonstrate that the system bottleneck, SI, can be cancelled significantly by zero-forcing (ZF) processing at the relay station which is equipped with massive receive and transmit arrays. We derive a lower bound achievable rate for ZF with statistical CSI. When the number of relay station antennas are large, we illustrate that the performance gap between the achievable rates given by statistical CSI and instantaneous CSI are negligible for different values of Rician K-factors. Since Rayleigh fading is a special case of Rician fading, the results in this paper hold for Rayleigh fading channels.

In this paper, we consider two-way full-duplex (FD) relay networks, which allow relaying communications in both directions at the same time and over the same frequency band. We propose a distributed space-time coding scheme, which we call SC-DSTC (Self-Coded Distributed Space-Time Coding), where the main idea is to perform convolutional encoding at the relay node and form a distributed linear convolutional space-time code (DLC-STC) together with the direct link. The convolutional code at the relay is realized by using part of the residual loop interference (RLI), which produces an automatic convolutional encoder. The amplifying factor is optimized when the loop channel information is imperfect. Simulation results show that the proposed SC-DSTC scheme can achieve asynchronous full cooperative diversity and is robust to the error of the loop channel information.

High peak‐to‐average power ratio (PAPR) is a major drawback of orthogonal frequency division multiplexing (OFDM) systems. A new companding scheme is proposed to reduce PAPR by transforming the statistics of the companded signal into exponential distribution with adjustable parameters. The proposed scheme can enhance the bit error rate (BER) performance significantly by minimising the companding distortion in the reduction of PAPR. Moreover, with the introduction of an inflexion point and transform parameters, the proposed scheme can offer more flexibility in the PAPR reduction, and therefore achieves a better tradeoff among the PAPR reduction, BER and power spectral density (PSD) performance. With a theoretical analysis presented, the parameter selection criteria are derived. Simulation results verify that the proposed scheme can significantly improve the BER and PSD performance while reducing PAPR effectively.

This study analyses the achievable cooperative diversity order of the distributed linear convolutional space‐time coding (DLC‐STC) scheme for time–frequency asynchronous cooperative networks. The authors first prove that perfect time or frequency synchronisation is impractical for cooperative networks with multiple relays serving multiple destinations even when the relays know all accurate time delays and frequency offsets. Then the DLC‐STC scheme, in which the exact time synchronisation at the relay nodes is unnecessary, is introduced into this type of cooperative networks. This study proves that the achievable time–frequency asynchronous cooperative diversity order of the DLC‐STC scheme with maximum‐likelihood receivers is equal to the number of relays. Simulation results verify the analysis.

In this paper, two-relay full-duplex asynchronous cooperative networks with cross-talks are considered. We show that the cross-talk interference at relays cannot be removed well even when the relays know all the accurate channel state information, for which a partial distributed linear convolutional space-time coding scheme (partial DLC-STC) is proposed by using the two-relay cross-talks instead of removing them. Simulation results show that the partial DLC-STC for two-relay full-duplex asynchronous cooperative networks can achieve full asynchronous diversity.

This paper deals with time and frequency offset in coordinated multipoint (CoMP) transmission/reception networks by using distributed linear convolutional space-time coding (DLC-STC). We first prove that perfect time synchronization is impractical for CoMP transmission/reception networks. Then the DLC-STC scheme, in which exact time synchronization at the relay nodes is unnecessary, is proposed for the CoMP joint processing mode (CoMP-JP). Finally, we show the detecting method by minimum mean-squared error decision-feedback equalizer (MMSE-DFE) receivers with any frequency offsets. Simulation results show that with MMSE-DFE receivers, the proposed DLC-STC scheme outperforms the delay diversity scheme and the MMSE-DFE receivers can achieve the same diversity orders as the maximum likelihood sequence detection (MLSD) receivers.

In the scenario of dynamic spectrum access application for orthogonal frequency division multiplexing (OFDM)‐based cognitive radio systems, the out‐of‐band radiation of the OFDM signals must be strictly controlled to protect licensed users in the adjacent band. This study proposes a constellation expansion‐based scheme for suppressing the sidelobes. The proposed approach can provide much faster decaying sidelobes by remapping the adjacent symbols in the original sequence with preferred mapping or alternative mapping chosen from a higher constellation set. Moreover, a simple clipping technique, which has little effect on the sidelobe suppression, is used for peak‐to‐average power ratio reduction of the proposed system. At the receiver, the specific associations in the mapping can be used to correct decision errors. Simulation results show that our proposed scheme can effectively reduce sidelobe power levels with only a slight bit error rate performance degradation.

In this paper, a two-relay full-duplex asynchronous cooperative network with the amplify-and-forward (AF) protocol is considered. We propose two distributed space-time coding schemes for the cases with and without cross-talks, respectively. In the first case, each relay can receive the signal sent by the other through the cross-talk link. We first study the feasibility of cross-talk cancellation in this network and show that the cross-talk interference cannot be removed well. For this reason, we design space-time codes by utilizing the cross-talk signals instead of removing them. In the other case, the self-coding is realized individually through the loop channel at each relay node and the signals from the two relay nodes form a space-time code. The achievable cooperative diversity of both cases is investigated and the conditions to achieve full cooperative diversity are presented. Simulation results verify the theoretical analysis.

In this paper, we propose two distributed linear convolutional space-time coding (DLC-STC) schemes for full-duplex (FD) asynchronous cooperative communications. The DLC-STC Scheme 1 is for the case of the complete loop channel cancellation, which achieves the full asynchronous cooperative diversity. The DLC-STC Scheme 2 is for the case of the partial loop channel cancellation and amplifying, where some loop signals are used as the self-coding instead of treated as interference to be directly cancelled. We show this scheme can achieve full asynchronous cooperative diversity. We then evaluate the performance of the two schemes when loop channel information is not accurate and present an amplifying factor control method for the DLC-STC Scheme 2 to improve its performance with inaccurate loop channel information. Simulation results show that the DLC-STC Scheme 1 outperforms the DLC-STC Scheme 2 and the delay diversity scheme if perfect or high quality loop channel information is available at the relay, while the DLC-STC Scheme 2 achieves better performance if the loop channel information is imperfect.

The transmit adaptation is a key technique to realize the full potentials of orthogonal frequency-division multiplexing (OFDM) systems. In this paper, we first present a new channel state information (CSI) model in order to save the reverse channel spectrum. By using clustering and interpolation according to the correlation between subcarriers, the estimation of CSI is obtained at the transmitter. Then, the transmit adaptation scheme including power allocation and adaptive modulation is proposed. In this scheme, the transmit power is allocated to the subcarriers by water filling theory, during which a fast search algorithm for the water filling line is presented, and then the adaptive modulation is carried out maintaining a certain system BER. Compared with the existing schemes, the proposed scheme achieves a better performance with the same cost of feedback data.