http://journal.bit.edu.cn/jbit/ JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY blgywb@bit.edu.cn blgywb@bit.edu.cn en blgywb@bit.edu.cn 1004-0579 http://journal.bit.edu.cn/jbit/article/id/06751f64-b706-479f-b601-a1f24bbda021 JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 1-2. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 1-2. 2022-5 Contents 2022-10-31 Personal use only, all commercial or other reuse prohibited JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 1-2. article doi: JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY 31 5 2022-10-31 http://journal.bit.edu.cn/jbit/article/id/06751f64-b706-479f-b601-a1f24bbda021 1 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.065?pageType=en Xiaochuan Sun, Biao Wei, Jiahui Gao, Difei Cao, Zhigang Li, Yingqi Li Spatio-temporal cellular network traffic prediction at wide-area level plays an important role in resource reconfiguration, traffic scheduling and intrusion detection, thus potentially supporting connected intelligence of the sixth generation of mobile communications technology (6G). However, the existing studies just focus on the spatio-temporal modeling of traffic data of single network service, such as short message, call, or Internet. It is not conducive to accurate prediction of traffic data, characterised by diverse network service, spatio-temporality and supersize volume. To address this issue, a novel multi-task deep learning framework is developed for citywide cellular network traffic prediction. Functionally, this framework mainly consists of a dual modular feature sharing layer and a multi-task learning layer (DMFS-MT). The former aims at mining long-term spatio-temporal dependencies and local spatio-temporal fluctuation trends in data, respectively, via a new combination of convolutional gated recurrent unit (ConvGRU) and 3-dimensional convolutional neural network (3D-CNN). For the latter, each task is performed for predicting service-specific traffic data based on a fully connected network. On the real-world Telecom Italia dataset, simulation results demonstrate the effectiveness of our proposal through prediction performance measure, spatial pattern comparison and statistical distribution verification. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 441-453. Xiaochuan Sun, Biao Wei, Jiahui Gao, Difei Cao, Zhigang Li, Yingqi Li Spatio-temporal cellular network traffic prediction at wide-area level plays an important role in resource reconfiguration, traffic scheduling and intrusion detection, thus potentially supporting connected intelligence of the sixth generation of mobile communications technology (6G). However, the existing studies just focus on the spatio-temporal modeling of traffic data of single network service, such as short message, call, or Internet. It is not conducive to accurate prediction of traffic data, characterised by diverse network service, spatio-temporality and supersize volume. To address this issue, a novel multi-task deep learning framework is developed for citywide cellular network traffic prediction. Functionally, this framework mainly consists of a dual modular feature sharing layer and a multi-task learning layer (DMFS-MT). The former aims at mining long-term spatio-temporal dependencies and local spatio-temporal fluctuation trends in data, respectively, via a new combination of convolutional gated recurrent unit (ConvGRU) and 3-dimensional convolutional neural network (3D-CNN). For the latter, each task is performed for predicting service-specific traffic data based on a fully connected network. On the real-world Telecom Italia dataset, simulation results demonstrate the effectiveness of our proposal through prediction performance measure, spatial pattern comparison and statistical distribution verification. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 441-453. Spatio-Temporal Cellular Network Traffic Prediction Using Multi-Task Deep Learning for AI-Enabled 6G Xiaochuan Sun, Biao Wei, Jiahui Gao, Difei Cao, Zhigang Li, Yingqi Li 2022-10-31 Personal use only, all commercial or other reuse prohibited JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 441-453. article doi:10.15918/j.jbit1004-0579.2022.065 10.15918/j.jbit1004-0579.2022.065 JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY 31 5 2022-10-31 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.065?pageType=en 441 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.023?pageType=en Hao Wang Robots have important applications in industrial production, transportation, environmental monitoring and other fields, and multi-robot collaboration is a research hotspot in recent years. Multi-robot autonomous collaborative tasks are limited by communication, and there are problems such as poor resource allocation balance, slow response of the system to dynamic changes in the environment, and limited collaborative operation capabilities. The combination of 5G and beyond communication and edge computing can effectively reduce the transmission delay of task offloading and improve task processing efficiency. First, this paper designs a robot autonomous collaborative computing architecture based on 5G and beyond and mobile edge computing(MEC). Then, the robot cooperative computing optimization problem is studied according to the task characteristics of the robot swarm. Then, a reinforcement learning task offloading scheme based on Q-learning is further proposed, so that the overall energy consumption and delay of the robot cluster can be minimized. Finally, simulation experiments demonstrate that the method has significant performance advantages. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 454-463. Hao Wang Robots have important applications in industrial production, transportation, environmental monitoring and other fields, and multi-robot collaboration is a research hotspot in recent years. Multi-robot autonomous collaborative tasks are limited by communication, and there are problems such as poor resource allocation balance, slow response of the system to dynamic changes in the environment, and limited collaborative operation capabilities. The combination of 5G and beyond communication and edge computing can effectively reduce the transmission delay of task offloading and improve task processing efficiency. First, this paper designs a robot autonomous collaborative computing architecture based on 5G and beyond and mobile edge computing(MEC). Then, the robot cooperative computing optimization problem is studied according to the task characteristics of the robot swarm. Then, a reinforcement learning task offloading scheme based on Q-learning is further proposed, so that the overall energy consumption and delay of the robot cluster can be minimized. Finally, simulation experiments demonstrate that the method has significant performance advantages. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 454-463. Optimization and Design of Cloud-Edge-End Collaboration Computing for Autonomous Robot Control Using 5G and Beyond Hao Wang 2022-10-31 Personal use only, all commercial or other reuse prohibited JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 454-463. article doi:10.15918/j.jbit1004-0579.2022.023 10.15918/j.jbit1004-0579.2022.023 JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY 31 5 2022-10-31 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.023?pageType=en 454 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.029?pageType=en Jiaqi Wang, Lina Wang The global navigation satellite system (GNSS) is currently being used extensively in the navigation system of vehicles. However, the GNSS signal will be faded or blocked in complex road environments, which will lead to a decrease in positioning accuracy. Owing to the higher-precision synchronization provided in the sixth generation (6G) network, the errors of ranging-based positioning technologies can be effectively reduced. At the same time, the use of terahertz in 6G allows excellent resolution of range and angle, which offers unique opportunities for multi-vehicle cooperative localization in a GNSS denied environment. This paper introduces a multi-vehicle cooperative localization method. In the proposed method, the location estimations of vehicles are derived by utilizing inertial measurement and then corrected by exchanging the beliefs with adjacent vehicles and roadside units. The multi-vehicle cooperative localization problem is represented using a factor graph. An iterative algorithm based on belief propagation is applied to perform the inference over the factor graph. The results demonstrate that our proposed method can offer a considerable capability enhancement on localization accuracy. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 464-472. Jiaqi Wang, Lina Wang The global navigation satellite system (GNSS) is currently being used extensively in the navigation system of vehicles. However, the GNSS signal will be faded or blocked in complex road environments, which will lead to a decrease in positioning accuracy. Owing to the higher-precision synchronization provided in the sixth generation (6G) network, the errors of ranging-based positioning technologies can be effectively reduced. At the same time, the use of terahertz in 6G allows excellent resolution of range and angle, which offers unique opportunities for multi-vehicle cooperative localization in a GNSS denied environment. This paper introduces a multi-vehicle cooperative localization method. In the proposed method, the location estimations of vehicles are derived by utilizing inertial measurement and then corrected by exchanging the beliefs with adjacent vehicles and roadside units. The multi-vehicle cooperative localization problem is represented using a factor graph. An iterative algorithm based on belief propagation is applied to perform the inference over the factor graph. The results demonstrate that our proposed method can offer a considerable capability enhancement on localization accuracy. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 464-472. A Multi-Vehicle Cooperative Localization Method Based on Belief Propagation in Satellite Denied Environment Jiaqi Wang, Lina Wang 2022-10-31 Personal use only, all commercial or other reuse prohibited JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 464-472. article doi:10.15918/j.jbit1004-0579.2022.029 10.15918/j.jbit1004-0579.2022.029 JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY 31 5 2022-10-31 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.029?pageType=en 464 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2021.101?pageType=en Shiqi Zhang, Guoxin Yu, Shanping Yu, Yanjun Zhang, Yu Zhang Satellite communication develops rapidly due to its global coverage and is unrestricted to the ground environment. However, compared with the traditional ground TCP/IP network, a satellite-to-ground link has a more extensive round trip time (RTT) and a higher packet loss rate, which takes more time in error recovery and wastes precious channel resources. Forward error correction (FEC) is a coding method that can alleviate bit error and packet loss, but how to achieve high throughput in the dynamic network environment is still a significant challenge. Inspired by the deep learning technique, this paper proposes a signal-to-noise ratio (SNR) based adaptive coding modulation method. This method can maximize channel utilization while ensuring communication quality and is suitable for satellite-to-ground communication scenarios where the channel state changes rapidly. We predict the SNR using the long short-term memory (LSTM) network that considers the past channel status and real-time global weather. Finally, we use the optimal matching rate (OMR) to evaluate the pros and cons of each method quantitatively. Extensive simulation results demonstrate that our proposed LSTM-based method outperforms the state-of-the-art prediction algorithms significantly in mean absolute error (MAE). Moreover, it leads to the least spectrum waste. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 473-482. Shiqi Zhang, Guoxin Yu, Shanping Yu, Yanjun Zhang, Yu Zhang Satellite communication develops rapidly due to its global coverage and is unrestricted to the ground environment. However, compared with the traditional ground TCP/IP network, a satellite-to-ground link has a more extensive round trip time (RTT) and a higher packet loss rate, which takes more time in error recovery and wastes precious channel resources. Forward error correction (FEC) is a coding method that can alleviate bit error and packet loss, but how to achieve high throughput in the dynamic network environment is still a significant challenge. Inspired by the deep learning technique, this paper proposes a signal-to-noise ratio (SNR) based adaptive coding modulation method. This method can maximize channel utilization while ensuring communication quality and is suitable for satellite-to-ground communication scenarios where the channel state changes rapidly. We predict the SNR using the long short-term memory (LSTM) network that considers the past channel status and real-time global weather. Finally, we use the optimal matching rate (OMR) to evaluate the pros and cons of each method quantitatively. Extensive simulation results demonstrate that our proposed LSTM-based method outperforms the state-of-the-art prediction algorithms significantly in mean absolute error (MAE). Moreover, it leads to the least spectrum waste. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 473-482. LSTM-Based Adaptive Modulation and Coding for Satellite-to-Ground Communications Shiqi Zhang, Guoxin Yu, Shanping Yu, Yanjun Zhang, Yu Zhang 2022-10-31 Personal use only, all commercial or other reuse prohibited JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 473-482. article doi:10.15918/j.jbit1004-0579.2021.101 10.15918/j.jbit1004-0579.2021.101 JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY 31 5 2022-10-31 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2021.101?pageType=en 473 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.075?pageType=en Hui Ma, Wei Li, Lei Sun The performance of symbiotic radio (SR) networks can be improved by equipping secondary transmitters (STs) with intelligent reflecting surfaces (IRSs). Since the IRS power consumption is a non-negligible issue for STs, we consider an IRS assisted SR system where the IRS operates under power splitting (PS) mode. We aim at minimizing the IRS power consumption for the ST under the quality of service constraints for both primary and secondary transmissions by optimizing the transmit beamforming, the reflect beamforming and the PS factor. The optimization problem is non-convex. To tackle it, an algorithm is proposed by employing the block coordinate descent, semidefinite relaxation and alternating direction method of multipliers techniques. Simulation results demonstrate the efficiency and effectiveness of the proposed algorithm. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 483-491. Hui Ma, Wei Li, Lei Sun The performance of symbiotic radio (SR) networks can be improved by equipping secondary transmitters (STs) with intelligent reflecting surfaces (IRSs). Since the IRS power consumption is a non-negligible issue for STs, we consider an IRS assisted SR system where the IRS operates under power splitting (PS) mode. We aim at minimizing the IRS power consumption for the ST under the quality of service constraints for both primary and secondary transmissions by optimizing the transmit beamforming, the reflect beamforming and the PS factor. The optimization problem is non-convex. To tackle it, an algorithm is proposed by employing the block coordinate descent, semidefinite relaxation and alternating direction method of multipliers techniques. Simulation results demonstrate the efficiency and effectiveness of the proposed algorithm. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 483-491. Intelligent Reflecting Surface with Power Splitting Aided Symbiotic Radio Networks Hui Ma, Wei Li, Lei Sun 2022-10-31 Personal use only, all commercial or other reuse prohibited JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 483-491. article doi:10.15918/j.jbit1004-0579.2022.075 10.15918/j.jbit1004-0579.2022.075 JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY 31 5 2022-10-31 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.075?pageType=en 483 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2021.091?pageType=en Shili Wang, Ruihao Song, Dongfang Hu An efficient single-carrier symbol synchronization method is proposed in this paper, which can work under a very low oversampling rate. This method is based on the frequency aliasing squared timing recovery assisted by pilot symbols and time domain filter. With frequency aliasing squared timing recovery with pilots, it is accessible to estimate timing error under oversampling rate less than 2. The time domain filter simultaneously performs matched-filtering and arbitrary interpolation. Because of pilot assisting, timing error estimation can be free from alias and self noise, so our method has good performance. Compared with traditional time-domain methods requiring oversampling rate above 2, this method can be adapted to any rational oversampling rate including less than 2. Moreover, compared with symbol synchronization in frequency domain which can operate under low oversampling rate, our method saves the complicated operation of conversion between time domain and frequency domain. By low oversampling rate and resource saving filter, this method is suitable for ultra-high-speed communication systems under resource-restricted hardware. The paper carries on the simulation and realization under 64QAM system. The simulation result shows that the loss is very low (less than 0.5 dB), and the real-time implementation on field programmable gate array (FPGA) also works fine. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 492-504. Shili Wang, Ruihao Song, Dongfang Hu An efficient single-carrier symbol synchronization method is proposed in this paper, which can work under a very low oversampling rate. This method is based on the frequency aliasing squared timing recovery assisted by pilot symbols and time domain filter. With frequency aliasing squared timing recovery with pilots, it is accessible to estimate timing error under oversampling rate less than 2. The time domain filter simultaneously performs matched-filtering and arbitrary interpolation. Because of pilot assisting, timing error estimation can be free from alias and self noise, so our method has good performance. Compared with traditional time-domain methods requiring oversampling rate above 2, this method can be adapted to any rational oversampling rate including less than 2. Moreover, compared with symbol synchronization in frequency domain which can operate under low oversampling rate, our method saves the complicated operation of conversion between time domain and frequency domain. By low oversampling rate and resource saving filter, this method is suitable for ultra-high-speed communication systems under resource-restricted hardware. The paper carries on the simulation and realization under 64QAM system. The simulation result shows that the loss is very low (less than 0.5 dB), and the real-time implementation on field programmable gate array (FPGA) also works fine. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 492-504. Symbol Synchronization of Single-Carrier Signal with Ultra-Low Oversampling Rate Based on Polyphase Filter Shili Wang, Ruihao Song, Dongfang Hu 2022-10-31 Personal use only, all commercial or other reuse prohibited JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 492-504. article doi:10.15918/j.jbit1004-0579.2021.091 10.15918/j.jbit1004-0579.2021.091 JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY 31 5 2022-10-31 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2021.091?pageType=en 492 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.044?pageType=en Wei Huang, Lin Guo, Kai Sun Dual connectivity (DC) is regarded as a promising technology to increase users’ throughput, provide radio link robustness, and improve load-balancing among base stations (BSs). However, since the introduction of DC makes the mobility of network more complex and diversified, especially the mobility management of heterogeneous networks (HetNets) based on DC faces great challenges. Taking event-A3-based measurement report as the trigger condition for handover (HO), this paper compares and evaluates the influences of HO of master nodes (MNs) and secondary nodes (SNs) on link reliability in different bearing modes. Particularly, hybrid automatic repeat request (HARQ), throughput, channel quality indicators (CQIs), and data packets queuing time are taken as link reliability analysis indicators. Besides, we study how DC utilizes the traffic split ratio between MNs and SNs to maximize the superiority of throughput. Simulation results show that DC can effectively reduce the impact of HO on the number of HARQ and increase the throughput of users. When the data traffic is tilted to the secondary nodes, the superiority of throughput is more obvious. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 505-512. Wei Huang, Lin Guo, Kai Sun Dual connectivity (DC) is regarded as a promising technology to increase users’ throughput, provide radio link robustness, and improve load-balancing among base stations (BSs). However, since the introduction of DC makes the mobility of network more complex and diversified, especially the mobility management of heterogeneous networks (HetNets) based on DC faces great challenges. Taking event-A3-based measurement report as the trigger condition for handover (HO), this paper compares and evaluates the influences of HO of master nodes (MNs) and secondary nodes (SNs) on link reliability in different bearing modes. Particularly, hybrid automatic repeat request (HARQ), throughput, channel quality indicators (CQIs), and data packets queuing time are taken as link reliability analysis indicators. Besides, we study how DC utilizes the traffic split ratio between MNs and SNs to maximize the superiority of throughput. Simulation results show that DC can effectively reduce the impact of HO on the number of HARQ and increase the throughput of users. When the data traffic is tilted to the secondary nodes, the superiority of throughput is more obvious. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 505-512. Performance Analysis for Mobility Management of Dual Connectivity in HetNet Wei Huang, Lin Guo, Kai Sun 2022-10-31 Personal use only, all commercial or other reuse prohibited JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 505-512. article doi:10.15918/j.jbit1004-0579.2022.044 10.15918/j.jbit1004-0579.2022.044 JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY 31 5 2022-10-31 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.044?pageType=en 505 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.106?pageType=en Ying Chang, Hongxue Yang, Qinghua Zhu Due to the development of network technology, the number of users is increasing rapidly, and the demand for emerging multicast services is becoming more and more abundant, traffic data is increasing day by day, network nodes are becoming denser, network topology is becoming more complex, and operators’ equipment operation and maintenance costs are increasing. Network functions virtualization multicast issues include building a traffic forwarding topology, deploying the required functions, and directing traffic. Combining the two is still a problem to be studied in depth at present, and this paper proposes a two-stage solution where the decisions of these two stages are interdependent. Specifically, this paper decouples multicast traffic forwarding and function delivery. The minimum spanning tree of traffic forwarding is constructed by Steiner tree, and the traffic forwarding is realized by Viterbi-algorithm. Use a general topology network to examine network cost and service performance. Simulation results show that this method can reduce overhead and delay and optimize user experience. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 513-523. Ying Chang, Hongxue Yang, Qinghua Zhu Due to the development of network technology, the number of users is increasing rapidly, and the demand for emerging multicast services is becoming more and more abundant, traffic data is increasing day by day, network nodes are becoming denser, network topology is becoming more complex, and operators’ equipment operation and maintenance costs are increasing. Network functions virtualization multicast issues include building a traffic forwarding topology, deploying the required functions, and directing traffic. Combining the two is still a problem to be studied in depth at present, and this paper proposes a two-stage solution where the decisions of these two stages are interdependent. Specifically, this paper decouples multicast traffic forwarding and function delivery. The minimum spanning tree of traffic forwarding is constructed by Steiner tree, and the traffic forwarding is realized by Viterbi-algorithm. Use a general topology network to examine network cost and service performance. Simulation results show that this method can reduce overhead and delay and optimize user experience. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 513-523. Optimize the Deployment and Integration for Multicast-Oriented Virtual Network Function Tree Ying Chang, Hongxue Yang, Qinghua Zhu 2022-10-31 Personal use only, all commercial or other reuse prohibited JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 513-523. article doi:10.15918/j.jbit1004-0579.2022.106 10.15918/j.jbit1004-0579.2022.106 JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY 31 5 2022-10-31 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.106?pageType=en 513 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.110?pageType=en Yifei Li, Jilei Yan, Yan Long, Xuming Fang, Rong He Sensing in wireless local area network (WLAN) gains great interests recently. In this paper we focus on the multi-user WLAN sensing problem under the existing 802.11 standards. Multiple stations perform sensing with the access point and transmit channel state information (CSI) report simultaneously on the basis of uplink-orthogonal frequency division multiple access (OFDMA). Considering the transmission resource consumed in CSI report and the padding wastage in OFDMA based CSI report, we optimize the CSI simplification and uplink resource unit (RU) allocation jointly, aiming to balance the sensing accuracy and padding wastage performances in WLAN sensing. We propose the minimize padding maximize efficiency (MPME) algorithm to solve the problem and evaluate the performance of the proposed algorithm through extensive simulations. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 524-534. Yifei Li, Jilei Yan, Yan Long, Xuming Fang, Rong He Sensing in wireless local area network (WLAN) gains great interests recently. In this paper we focus on the multi-user WLAN sensing problem under the existing 802.11 standards. Multiple stations perform sensing with the access point and transmit channel state information (CSI) report simultaneously on the basis of uplink-orthogonal frequency division multiple access (OFDMA). Considering the transmission resource consumed in CSI report and the padding wastage in OFDMA based CSI report, we optimize the CSI simplification and uplink resource unit (RU) allocation jointly, aiming to balance the sensing accuracy and padding wastage performances in WLAN sensing. We propose the minimize padding maximize efficiency (MPME) algorithm to solve the problem and evaluate the performance of the proposed algorithm through extensive simulations. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 524-534. Resource Allocation for Uplink CSI Sensing Report in Multi-User WLAN Sensing Yifei Li, Jilei Yan, Yan Long, Xuming Fang, Rong He 2022-10-31 Personal use only, all commercial or other reuse prohibited JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY. 2022 31(5): 524-534. article doi:10.15918/j.jbit1004-0579.2022.110 10.15918/j.jbit1004-0579.2022.110 JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY 31 5 2022-10-31 http://journal.bit.edu.cn/jbit/article/doi/10.15918/j.jbit1004-0579.2022.110?pageType=en 524

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