|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Scheduling Fairness of Real-Time Scheduling Algorithms in Wireless Multimedia Application显示文摘 | XU Binyang LI Shaoqian PU Heping TANG Wanbin | 2007 | Chinese Journal of Electronics2007,16,2: | 3 |
| 2 | Joint optimal sensing time and power allocation for multi-channel cognitive radio networks considering sensing-channel selection显示文摘In this paper,we consider a multi-channel cognitive radio network(CRN)where each secondary user(SU)can only choose to sense a subset of channels.We formulate a joint optimization problem of sensingchannel selection,sensing time and power allocation under the constraints of average transmit power budget and average interference power budget,which maximizes the CRN’s total throughput.We propose a greedy algorithm to solve the joint optimization problem,which has much less computational complexity.Moreover,it is shown that the search space of the greedy algorithm can be further pruned.Finally,numerical results demonstrate that the greedy algorithm has comparable performance to the exhaustive search algorithm. | YU HuoGen TANG WanBin LI ShaoQian | 2014 | Science China(Information Sciences)2014,57,4: | 2 |
| 3 | SPECTRUM HANDOFF IN COGNITIVE RADIO WITH FUZZY LOGIC CONTROL显示文摘The secondary usage of spectrum has been investigated in Cognitive Radio(CR) network to resolving the spectrum scarcity issue in wireless communication.When Primary Users(PU) who own the spectrum appear,spectrum handoff is needed to maintain the communications of Secondary Users.But the decision making of spectrum handoff is a challenge issue for CR network,because the input of decision making,which obtain through spectrum sensing,is heterogeneous and inexact.In this paper we will use fuzzy logic control theory to solve this issue and make use of new information for handoff operation:the probability of PU's occupancy at a certain channel.Our new algorithm can make more intelligent decision compared to simple traditional spectrum handoff decision making and reduce the probability of spectrum handoff,also the performance of SU's communication can be enhanced. | Tang Wanbin Peng Dong | 2010 | Journal of Electronics(China)2010,27,5: | 2 |
| 4 | An analytical perfor- mance model considering access strategy of an opportunistic spectrum sharing system 显示文摘 | Tang Wanbin Yu Huogen Han Yanfeng | 2012 | Concurrency and Computation: Practice and Experience2012,24,11: | 1 |
| 5 | Directional modulation with distributed receiver selection for secure wireless communications显示文摘In this paper, a novel directional modulation with distributed receiver selection(DM-DRS)scheme is proposed for secure wireless communications. In DM-DRS, a particular subset of receivers is activated and part of the information bits are modulated by the index of the activation pattern, in addition to traditional digital modulation. Especially, the scrambling matrix is introduced for the sake of preventing the eavesdropping. Moreover, the performances of bit error rate(BER) in terms of the union bound for both the legitimate user and eavesdropper are respectively derived in the context of an optimal joint maximum likelihood(ML) detector, and the theoretical BER upper bounds are demonstrated to be tight by the numerical results. In the context of the discrete-input and continuous-output system, the ergodic secrecy rates of the legitimate user and the eavesdropper are obtained, the secrecy rate is also quantified. Furthermore,our numerical results exhibit that DM-DRS can achieve an increased transmission rate compared to its traditional directional modulation with cooperative receivers(DM-CR) and spatial and direction modulation(SDM) counterparts, while guaranteeing an improved BER performance. | Hongyan ZHANG Yue XIAO Wanbin TANG Gang WU Hong NIU Xiaotian ZHOU | 2021 | Science China(Information Sciences)2021,64,12: | 0 |
| 6 | Model-Driven Deep Learning for Massive Space-Domain Index Modulation MIMO Detection显示文摘In this paper,a powerful model-driven deep learning framework is exploited to overcome the challenge of multi-domain signal detection in spacedomain index modulation(SDIM)based multiple input multiple output(MIMO)systems.Specifically,we use orthogonal approximate message passing(OAMP)technique to develop OAMPNet,which is a novel signal recovery mechanism in the field of compressed sensing that effectively uses the sparse property from the training SDIM samples.For OAMPNet,the prior probability of the transmit signal has a significant impact on the obtainable performance.For this reason,in our design,we first derive the prior probability of transmitting signals on each antenna for SDIMMIMO systems,which is different from the conventional massive MIMO systems.Then,for massive MIMO scenarios,we propose two novel algorithms to avoid pre-storing all active antenna combinations,thus considerably improving the memory efficiency and reducing the related overhead.Our simulation results show that the proposed framework outperforms the conventional optimization-driven based detection algorithms and has strong robustness under different antenna scales. | Ping Yang Qin Yi Yiqian Huang Jialiang Fu Yue Xiao Wanbin Tang | 2023 | China Communications2023,20,10: | 0 |
| 7 | OPTIMIZATION OF MULTIPLE-CHANNEL COOPERATIVE SPECTRUM SENSING WITH DATA FUSION RULE IN COGNITIVE RADIO NETWORKS显示文摘This paper focuses on multi-channel Cooperative Spectrum Sensing (CSS) where Secondary Users (SUs) are assigned to cooperatively sense multiple channels simultaneously. A multi-channel CSS optimization problem of joint spectrum sensing and SU assignment based on data fusion rule is formulated, which maximizes the total throughput of the Cognitive Radio Network (CRN) subject to the constraints of probabilities of detection and false alarm. To address the optimization problem, a Branch and Bound (BnB) algorithm and a greedy algorithm are proposed to obtain the optimal solutions. Simulation results are presented to demonstrate the effectiveness of our proposed algorithms and show that the throughput improvement is achieved through the joint design. It is also shown that the greedy algorithm with a low complexity achieves the comparable performance to the exhaustive algorithm. | Yu Huogen Tang Wanbin Li Shaoqian | 2012 | Journal of Electronics(China)2012,29,6: | 0 |