Downlink Transmission Research Articles

Delay Analysis of Wireless Federated Learning Based on Saddle Point Approximation and Large Deviation Theory

Federated learning (FL) is a collaborative machine learning paradigm, which enables deep learning model training over a large volume of decentralized data residing in mobile devices without accessing clients’ private data. Driven by the ever increasing demand for model training of mobile applications or devices, a vast majority of FL tasks are implemented over wireless fading channels. Due to the time-varying nature of wireless channels, however, random delay occurs in both the uplink and downlink transmissions of FL. How to analyze the overall time consumption of a wireless FL task, or more specifically, a FL’s delay distribution, becomes a challenging but important open problem, especially for delay-sensitive model training. In this paper, we present a unified framework to calculate the approximate delay distributions of FL over arbitrary fading channels. Specifically, saddle point approximation, extreme value theory (EVT), and large deviation theory (LDT) are jointly exploited to find the approximate delay distribution along with its tail distribution, which characterizes the quality-of-service of a wireless FL system. Simulation results will demonstrate that our approximation method achieves a small approximation error, which vanishes with the increase of training accuracy.

Performance Evaluation of MU-MIMO Transmissions with Joint Interference Constraint in HetNet

In this paper, we investigate the per-tier outage probability of multiuser multiple-input multiple-output (MU-MIMO) transmissions in heterogeneous networks (HetNets) with joint interference constraint. In the tier of cellular cell, user equipment (UE) is required to report measured channel information and the base station (BS) adopts ZF-based precoding MU-MIMO transmission to achieve multiuser diversity gain. With the constraint of cross-tier interference and unpredicted inter-beam interference, we derive the closed-form expression of outage probability of downlink MU-MIMO transmissions. Considering the capacity of nodes in the tier of ad hoc networks, a max-SINR scheduler and codebook-based MU-MIMO transmission are employed. The scheduler selects the best receiving nodes for each beam in predefined codebook according to measured signal to interference plus noise ratio (SINR), and the transmitting node performs data transmissions using orthogonal beams. In the presence of inter-node interference, inter-beam interference, and cross-tier interference, we obtain the closed-form expression of outage probability of MU-MIMO transmissions when downlink or uplink transmissions occur in cellular cell. Additionally, in case that the outage probability in ad hoc networks should satisfy quality of service (QoS) requirement, a restricted area in cellular cell in which the outage probability in ad hoc networks is not greater than a required threshold is explored. Numerical results show that the unpredictable inter-beam interference in cellular cell degrades the outage probability slightly. The restricted area increases with the outage probability threshold.

UAV-Assisted Underwater Sensor Networks Using RF and Optical Wireless Links

Underwater sensor networks (UWSNs) are of interest to gather data from underwater sensor nodes (SNs) and deliver information to a terrestrial access point (AP) in the uplink transmission, and transfer data from the AP to the SNs in the downlink transmission. In this paper, we investigate a triple-hop UWSN in which autonomous underwater vehicle (AUV) and unmanned aerial vehicle (UAV) relays enable end-to-end communications between the SNs and the AP. It is assumed that the SN–AUV, AUV–UAV, and UAV–AP links are deployed by underwater optical communication (UWOC), free-space optic (FSO), and radio frequency (RF) technologies, respectively. Two scenarios are proposed for the FSO uplink and downlink transmissions between the AUV and the UAV, subject to water-to-air and air-to-water interface impacts; direct transmission scenario (DTS) and retro-reflection scenario (RRS). After providing the channel models and their statistics, the UWSN's outage probability and average bit error rate (BER) are computed. Besides, a tracking procedure is proposed to set up reliable and stable AUV– UAV FSO communications. Through numerical results, it is concluded that the RSS scheme outperforms the DTS one with about 200% (32%) and 80% (17%) better outage probability (average BER) in the uplink and downlink, respectively. It is also shown that the tracking procedure provides on average 480% and 170% improvements in the network's outage probability and average BER, respectively, compared to poorly aligned FSO conditions. The results are verified by applying Monte-Carlo simulations.

Hybrid WDM-FSO-PON with integrated SMF/FSO link for transportation of Rayleigh backscattering noise mitigated wired/wireless information in long-reach

This paper presents a hybrid Wavelength division multiplexing-free space optics-passive optical network for bidirectional transmission with 4×10 Gbps downlink and 2×10 Gbps uplink to provide information to the wired and wireless users simultaneously over total 60 km SMF and 650 m FSO or 62 km SMF link with enhanced fault protection capability. Noise tolerance against Rayleigh backscattering (RB) also enhanced by employing two different ports of interleavers and by allowing different wavelengths of light as carrier signals for uplink and downlink transmission through a single feeder fiber. Integrated single mode fiber (SMF)/free space optics (FSO) link increase the reliability against failure of any one channel between SMF and FSO link, besides that it maintains the continuity of data transfer even where fiber link installation is restricted due to environmental boundary such as between two mountains, wide river etc. Low bit error rate (10−9), <1 dB power penalties (0.7 dB, 0.85 dB, 0.9 dB) are obtained between B2B and over total transmission link. A comparison between our proposed network and the network when the signal transmitted over total transmission link (60 km SMF+ 650 m FSO, or 62 km SMF) at a time also verified with their power budgets. Divergence losses at different FSO lengths (17 m to 680 m) are also calculated to determine the maximum possible FSO length for this proposed set up. Therefore, the proposed architecture proofs its feasibility, reliability and the capacity to continue transfer of high data rate over long distance even in the unfair environmental situation, which makes it an attractive platform to the next generation communication system (5G) to fulfill the thirst of end users.

Frequency-Packed Multiband-Coherent Transceiver With Symbol Rate-Adaptive Nyquist WDM Signals

In the next-generation flexible point-to-multipoint optical networks such as optical access systems, it is desirable for one transceiver to handle various Internet-of-Things traffic streams. A symbol rate-adaptive multiband-coherent-transceiver, that can transmit and receive wavelength division multiplexing (WDM) signals arranged at the Nyquist spacing after Nyquist spectrum shaping, achieves flexibility by changing the number of subbands (SB) and the symbol rate per SB. Band-asymmetric coherent access systems with wide bandwidth optical transceivers on the optical-line-terminal side and narrowband optical transceivers on the optical-networking-unit side have been reported for uplink and downlink transmissions. We also examined the multiband-coherent-transceiver for ultra-dense WDM signals with a narrow analog-device bandwidth and narrow SB spacing to improve cost and spectral efficiency. To the best knowledge of the authors, there is no other research on a Nyquist spectrally shaped WDM-passive optical network system that applies these two functions and flexibly changes the symbol rate per SB with a SB spacing less than the Nyquist spacing.

Deep Learning-Based Antenna Selection and CSI Extrapolation in Massive MIMO Systems

A critical bottleneck of massive multiple-input multiple-output (MIMO) system is the huge training overhead caused by downlink transmission, like channel estimation, downlink beamforming and covariance observation. In this paper, we propose to use the channel state information (CSI) of a small number of antennas to extrapolate the CSI of the other antennas and reduce the training overhead. Specifically, we design a deep neural network that we call an antenna domain extrapolation network (ADEN) that can exploit the correlation function among antennas. We then propose a deep learning (DL) based antenna selection network (ASN) that can select a limited antennas for optimizing the extrapolation, which is conventionally a type of combinatorial optimization and is difficult to solve. We trickly designed a constrained degradation algorithm to generate a differentiable approximation of the discrete antenna selection vector such that the back-propagation of the neural network can be guaranteed. Numerical results show that the proposed ADEN outperforms the traditional fully connected one, and the antenna selection scheme learned by ASN is much better than the trivially used uniform selection.

Uplink-Downlink Duality Between Multiple-Access and Broadcast Channels With Compressing Relays

Uplink-downlink duality refers to the fact that under a sum-power constraint, the capacity regions of a Gaussian multiple-access channel and a Gaussian broadcast channel with Hermitian transposed channel matrices are identical. This paper generalizes this result to a cooperative cellular network, in which remote access-points are deployed as relays in serving the users under the coordination of a central processor (CP). In this model, the users and the relays are connected over noisy wireless links, while the relays and the CP are connected over noiseless but rate-limited fronthaul links. Based on a Lagrangian technique, this paper establishes a duality relationship between such a multiple-access relay channel and broadcast relay channel, under the assumption that the relays use compression-based strategies. Specifically, we show that under the same total transmit power constraint and individual fronthaul rate constraints, the achievable rate regions of the Gaussian multiple-access and broadcast relay channels are identical, when either independent compression or Wyner-Ziv and multivariate compression strategies are used. The key observations are that if the beamforming vectors at the relays are fixed, the sum-power minimization problems under the achievable rate and fronthaul constraints in both the uplink and the downlink can be transformed into either a linear programming or a semidefinite programming problem depending on the compression technique, and that the uplink and downlink problems are Lagrangian duals of each other. Moreover, the dual variables corresponding to the downlink rate constraints become the uplink powers; the dual variables corresponding to the downlink fronthaul constraints become the uplink quantization noises. This duality relationship enables an efficient algorithm for optimizing the downlink transmission and relaying strategies based on the uplink.

Machine Learning for User Partitioning and Phase Shifters Design in RIS-Aided NOMA Networks

A novel reconfigurable intelligent surface (RIS) aided non-orthogonal multiple access (NOMA) downlink transmission framework is proposed. We formulate a long-term stochastic optimization problem that involves a joint optimization of NOMA user partitioning and RIS phase shifting, aiming at maximizing the sum data rate of the mobile users (MUs) in NOMA downlink networks. To solve the challenging joint optimization problem, we invoke a modified object migration automation (MOMA) algorithm to partition the users into equal-size clusters. To optimize the RIS phase shifting matrix, we propose a deep deterministic policy gradient (DDPG) algorithm to collaboratively control multiple reflecting elements (REs) of the RIS. Different from conventional training-then-testing processing, we consider a long-term self-adjusting learning model where the intelligent agent is capable of learning the optimal action for every given state through exploration and exploitation. Extensive numerical results demonstrate that: 1) The proposed RIS-aided NOMA downlink framework achieves enhanced sum data rate compared with the conventional orthogonal multiple access (OMA) framework. 2) The proposed DDPG algorithm is capable of learning a dynamic resource allocation policy in a long-term manner. 3) The performance of the proposed RIS-aided NOMA framework can be improved by increasing the granularity of the RIS phase shifts. The numerical results also show that increasing the number of reflecting elements (REs) is an efficient method to improve the sum data rate of the MUs.

Optimization of Duplex Mode Selection for Network-Assisted Full-Duplex Cell-Free Massive MIMO Systems

Network-assisted full-duplex enable simultaneous uplink (UL) and downlink (DL) communications by allocating remote antenna units (RAUs) to perform either UL reception of DL transmission at each time slot, which improve the spectral efficiency (SE) of cell-free massive multiple-input multiple-output (MIMO) systems. However, previous studies mainly focus on analyzing the system performance under given duplex mode of RAUs. In this letter, we propose to dynamically optimize the duplex mode of RAUs to further improve the SE. An algorithm based on parallel successive convex approximation is proposed to solve the non-convex duplex mode optimization problem. To reduce algorithm complexity and achieve higher SE, a reinforcement learning algorithm based on enhanced Q-learning is also proposed. Simulation results show that the proposed algorithms improve the SE of cell-free massive MIMO systems greatly with lower complexity.

Efficient Technique for PAPR and BER Reduction in Downlink Large Scale MU-MIMO-OFDM System

Background &amp; Objective: The Orthogonal Frequency Division Multiplexing (OFDM) based large scale multiuser multiple input multiple output (LS-MU-MIMO) system is a preferred choice for signal transmission because it can substantially enhance the spectral and energy efficiency of the next-generation wireless systems. However, there are several practical issues in implementing large multiuser-MIMO-OFDM systems and one of the critical issues is the high Peak-to-Average- Power Ratio (PAPR). Due to the use of a large number of antennas at the Base Station (BS) of an LSMU- MIMO-OFDM system, it requires a large number of Power Amplifiers (PAs) which are needed to be connected to each antenna element. The high PAPR in an OFDM based LS-MU-MIMO system results in the decrease in the efficiency of PAs and enhancement in nonlinear signal distortions. This work is concerned with the reduction in PAPR of LS-MU-MIMO-OFDM systems using the SCFDMA scheme for the downlink transmission. The reduction in PAPR is achieved on the basis of discrete Fourier transform spreading (DFT-S) scheme known as DFT-SC-FDMA. The SC-FDMA scheme can achieve the reduction in PAPR of MIMO-OFDM signal up to the level of single-carrier transmission. Further, the reduction in PAPR is achieved with the sub mapping schemes such as localized FDMA (LFDMA) and distributed FDMA (DFDMA), Interleaved FDMA (IFDMA). Result: In this work, we propose to perform jointly multiuser MMSE precoding, SC-IFDMA and antenna reservation technique to reduce the PAPR and Bit Error Rate (BER) of the large MU-MIMO system. To show the effectiveness of the proposed scheme in the reduction of PAPR with different modulation techniques, subcarriers, and subcarrier mapping schemes, the results are compared with the existing OFDM based large MU-MIMO system. Conclusion: The MATLAB simulation results confirm that our proposed combination of MMSE MUprecoding, SC-IFDMA and antenna reservation technique is able to reduce PAPR and BER to a significant extent for LS-MU-MIMO-OFDM systems.

Asymmetrical bidirectional VLC based on beam homogenizer OAM generation technology.

An asymmetric bidirectional visible light communication (B-VLC) system is presented in this Letter. It combines beam homogenizers with a spatial light modulator (SLM) to implement the orbital angular momentum (OAM) generation technology at a terminal user for uplink data transmission. The major advantage of the proposed approach is that multiple OAM modes can be arbitrarily generated simultaneously by a single SLM. The uplink transmission capacity can also be significantly improved by multiplexing more generated OAM channels. For the proof of concept, an asymmetric B-VLC based on the OAM generation technology for uplink transmission at a distance of nearly 2 m has been implemented. The baseband modulation schemes, including on-off keying (OOK) and quadrature phase-shift keying, were also implemented to validate the transmission performance. The experimental results show that the downlink transmission capacity of up to 2.2 Gbit/s can be achieved using an S-polarization beam. In comparison, the uplink transmission capacity can also be significantly enhanced by using P-polarization through multiplexing four OAM channels, each with a maximum transmission rate of up to 800 Mbit/s. The bit error rates (BERs) of both uplink and downlink transmissions were all under the forward error correction limit (BER=3×10-3).

Proximity co-located massive MIMO systems over correlated Rician fading channels

This paper considers the downlink transmission in a single-cell proximity co-located massive MIMO (PC-MIMO) system, in which antennas of the base station (BS) are divided into multiple antenna units (AUs) and these AUs are connected to a backhaul processor unit (BPU). The AUs are geographically deployed very close to the BPU which controls them to serve all users in the cell. Considering correlated Rician fading channels, we derive a closed-form expression of the sum spectral efficiency under the maximum-ratio transmission and statistical channel state information at each user. Based on the obtained expression, it is shown that as the number of AUs approaches infinity, the sum spectral efficiency approaches a constant value. Furthermore, we also give a closed-form expression of the average sum spectral efficiency when the arrival angles to the users seen from the AUs are varying. For the cases of correlated Rayleigh fading and uncorrelated Rician fading, we show how to find the number of antennas at each AU to maximize the average sum spectral efficiency when the total number of antennas at the BS is fixed.

Cell-Free Massive MIMO Systems With Oscillator Phase Noise: Performance Analysis and Power Control

Cell-free massive multiple-input multiple-output (MIMO) is considered as a promising technology for satisfying higher rate requirement of users in beyond-5G networks. This paper investigates the impact of phase noise on the performance of cell-free MIMO systems which employ a large number of multi-antenna access points (APs). For both downlink and uplink transmissions, we derive the tractable closed-form achievable rate expressions when signal detection with channel state information (CSI) and channel distribution information (CDI), respectively, by utilizing the extended deterministic equivalence method in random matrix theory. The closed-form achievable rate expressions provide efficient evaluation for the impact of phase noise on system performance. The analytical results indicate that the phase noise influences the power of the desired signal, the beamforming uncertainty gain, and the inter-user interference increment caused by the pilot contamination. In addition, the special cases that only APs have phase noise and only users have phase noise are discussed. It is found that the impact of phase noise at users is more severe than that at APs. Besides, we discuss the system performance at low and high SNR regimes. It demonstrates that the phase noise is the major limitation of the system performance in high SNR regime while it can be neglected in low SNR regime. Furthermore, we formulate the max-min power control problem for both downlink and uplink transmissions to guarantee the users’ fairness and prove that the downlink max-min problem is a quasi-concave problem while the uplink max-min problem is a geometric programming (GP) problem. Then, the phase noise-aware max-min power control schemes for both downlink and uplink transmissions are proposed to ensure the users’ fairness. Finally, numerical results are provided to validate the analytical results and the proposed phase noise-aware power control scheme.

Aerial RIS-Assisted High Altitude Platform Communications

We optimize the deployment of an aerial reconfigurable intelligent surface (ARIS) to assist the high altitude platform (HAP) downlink transmission when the direct link is blocked. Specifically, we maximize the received signal-to-noise ratio (SNR) of the ground users by jointly optimizing the trajectory and the phase-shift of the ARIS with the consideration of the unknown movement of HAP, which is caused by the changes in the stratospheric wind and air density. Due to the non-convex nature of the formulated optimization problem, we decouple the optimization problem and propose an alternative two-stage optimization. By proving that the movement of the HAP follows a finite state Markov stochastic process, we first learn the optimal ARIS trajectory via model-free reinforcement learning, and then adjust the optimal phase-shift of the ARIS, alternately. Next, the convergence of the proposed algorithm is analyzed based on the obtained upper bound of the accumulated reward. The numerical results show substantial performance gain of HAP communications with the optimized ARIS assistance.

Code design and latency analysis of distributed matrix multiplication with straggling servers in fading channels

This paper exploits coding to speed up computation offloading in a multi-server mobile edge computing (MEC) network with straggling servers and channel fading. The specific task we consider is to compute the product between a user-generated input data matrix and a large-scale model matrix that is stored distributively across the multiple edge nodes. The key idea of coding is to introduce computation redundancy to improve robustness against straggling servers and to create communication redundancy to improve reliability against channel fading. We utilize the hybrid design of maximum distance separable (MDS) coding and repetition coding. Based on the hybrid coding scheme, we conduct theoretical analysis on the average task uploading time, average edge computing time, and average output downloading time, respectively and then obtain the end-to-end task execution time. Numerical results demonstrate that when the task uploading phase or the edge computing phase is the performance bottleneck, the hybrid coding reduces to MDS coding; when the downlink transmission is the bottleneck, the hybrid coding reduces to repetition coding. The hybrid coding also outperforms the entangled polynomial coding that causes higher uplink and downlink communication loads.

Outage performance of downlink NOMA-aided small cell network with wireless power transfer

This article considers the outage performance of the downlink transmission for a small cell network in a heterogeneous network. Due to mobility and distribution of users, it is necessary to study massive connections and high energy efficiency for such kind of systems. To be an enabler of energy harvesting, a power beacon is helpful to support the base station to send signals to distant users, and wireless power transfer (WPT) is exploited to guarantee the data packets transmission from the power beacon to the base station. To provide massive connections, we propose a novel non-orthogonal multiple access (NOMA) technique combined with WPT to enhance outage performance and latency reduction. Furthermore, we derive outage probability (OP) to characterize the system performance. Simulation results are verified to match well between theoretical and analytical methods, and main parameters are determined to understand how they affect the proposed scheme.

Joint Power Allocation and Hybrid Beamforming for Downlink mmWave-NOMA Systems

This paper investigates the application of nonorthogonal multiple access (NOMA) in millimeter-Wave (mmWave) communications to address resource allocation issues for multiuser downlink transmission. Inspired by the K-means clustering algorithm, a NOMA user grouping policy is first employed in accordance with the channel correlation between users. The first-stage decoding order for each NOMA group is then determined by merely utilizing the users’ channel gain to formulate a joint power allocation and hybrid beamforming optimization problem. Specifically, we use signal-to-leakage-plus-noise ratio (SLNR) as the performance index of the optimization problem to reduce the computational complexity, because it can decouple the design of the beamforming and power allocation issues so they can be executed iteratively. Under given beamforming matrix, the power allocation issue is expressed as a quadratic programming (QP) problem, and then transformed into a convex problem by introducing an auxiliary-positive real variable to solve through the Lagrange multiplier method. On the contrary, the beamforming optimization problem is non-convex and very difficult to solve due to the constant modulus constraints in the hybrid architecture. However, the optimum solution of the ideal full-digital beamforming can be acquired primarily by generalized eigenvalue decomposition (GED). In this condition, two hybrid beamforming algorithms are proposed, in which normalized phase matching and equal gain transmission are performed respectively in the analog domain. On this basis, a second-stage decoding order can be employed according to the effective channel gain of users to perform successive interference cancellation (SIC) successfully. Numerical results show that the proposed joint power allocation and hybrid beamforming algorithms are superior to the classical mmWave-NOMA and orthogonal multiple access (OMA) schemes not only in lower implementation complexity, but also in better spectrum efficiency and energy efficiency performance.

Performance of Generalized Receiver Employed by Broadband Multicarrier DS-CDMA System Using Space-Time Spreading-Assisted Transmit Diversity

In this paper the multicarrier direct-sequence code-division multiple access (MC DS-CDMA) using space-time spreading assisted transmit diversity is investigated in the context of broadband wireless communi-cations systems constructed based on the generalized approach to signal processing in noise over frequency-se-lective Rayleigh fading channels. We consider the issue of parameter design for the sake of achieving high-ef-ficiency communications in various dispersive environments. In contrast to the conventional MC DS-CDMA wireless communication system employing the time (T)-domain spreading only, in the present paper the broad-band wireless MC DS-CDMA wireless communication schemes employ both the time (T)-domain and frequen-cy (F)-domain spreading, i.e., employ the TF-domain spreading. The bit-error rate (BER) performance of the space-time spreading assisted broadband MC DS-CDMA wireless communications system is investigated for down-link transmissions associated with the single user and multiuser generalized detectors and is compared with that of the single user correlation detector and the multiuser decorrelating detector. Our study demonstra-tes that with appropriately selecting the system parameters, the broadband MC DS-CDMA wireless communi-cation system using the space-time spreading assisted transmit diversity constitutes a promising downlink tran-smission scheme. This scheme is capable to support ubiquitous communications over diverse communication environments without the BER performance degradation

A novel bidirectional RoF link with compensated SBS and RB for 16-QAM OFDM based mm-wave downlink and uplink vector signal generation and transmission on a single fiber

A novel bidirectional RoF link with compensated SBS and RB for 60 GHz OFDM-based 16-QAM downlink and uplink vector signal generation and co-propagation over a single fiber is proposed. At the central station (CS), 60 GHz optical mm-wave is generated and modulated in the optical single-sideband modulation (OSSB) technique by the 16-QAM OFDM downlink vector signal. At the base station (BS), the 60 GHz downlink signal is detected by a high-speed photodetector (PD). The 60 GHz electrical mm-wave signal is transmitted to the user end by an antenna. The uplink carrier is extracted from the unmodulated sideband of the mm-wave downlink vector signal. This reduces the complexity of BS and makes it free from the laser source. The 16-QAM OFDM-based mm-wave uplink signal is received from the user end through an antenna and down-converted to a 10 GHz uplink vector signal. The uplink signal modulates the extracted blank carrier in the OSSB technique. The uplink and downlink vector signals are co-propagated through the standard single bidirectional fiber. Although the carrier reuse over a single fiber reduces the fiber capacity by half, it generates non-linear backscattering such as Rayleigh Backscattering (RB) and Stimulated Brillouin Scattering (SBS). A theoretical analysis is made on the backscattered power and its effect on the fiber transmission. The compensation of SBS by maintaining the SBS threshold and mitigation of RB is carried out by appropriate modulation technique. In addition, downlink and uplink signal with different data rate is transmitted through the compensated bidirectional RoF link, and the transmission performance is analyzed. Based on the analysis, the theoretical model for simultaneous downlink and uplink signal transmission over a single fiber is proposed and verified by the software simulation. The compensated bidirectional RoF link shows up a better performance up to 75 km with negligible power penalty.

Multi-resources management in 6G-oriented terrestrial-satellite network

The six-generation (6G) wireless network is expected to satisfy the requirements of ubiquitous connectivity and intelligent endogenous. Terrestrial-satellite networks (TSN) enable seamless coverage for terrestrial users in a wide area, making it very promising in 6G. As data traffic in TSNs surges, the integrated management for caching, computing, and communication (3C) has attracted much research attention. In this paper, we investigate the multi-resource management in the uplink and downlink transmission of TSN, respectively. In particularly, we aim to guarantee both throughput fairness and data security in the uplink transmission of TSN. Considering the intermittent communication of the satellite, we introduce two kinds of relays, i.e., terrestrial relays (TRs) and aerial relays (ARs) to improve the system throughput performance in the downlink transmission of TSN. Finally, we study a specific case of TSN with the uplink and downlink transmission, and the corresponding simulation results validate the effectiveness of our proposed schemes.