This paper presents the design and implementation of access controller used for Ethernet passive optical network （ EPON）. As a first step to develop an ASIC product, the entire system is designed on a field programm...This paper presents the design and implementation of access controller used for Ethernet passive optical network （ EPON）. As a first step to develop an ASIC product, the entire system is designed on a field programmable gate array （FPGA） with an embedded CPU. To reduce working frequency of the FPGA, the byte-to-word conversion is proposed. Propagation delays are equalized by ranging procedure so as to avoid data collision. Implementations of synchronization, classification, as well as Linux porting are illustrated in detail. The interface between the FPGA and CPU are also presented. Experimental results show that the proposed system can properly function in a relatively low cost FPGA.展开更多
As a promising paradigm of the fifth generation networks,fog radio access network(F-RAN)has attracted lots of attention nowadays.To fully utilize the promising gain of F-RANs,the acquisition of accurate channel state ...As a promising paradigm of the fifth generation networks,fog radio access network(F-RAN)has attracted lots of attention nowadays.To fully utilize the promising gain of F-RANs,the acquisition of accurate channel state information is significant.However,conventional channel estimation approaches are not suitable in F-RANs due to the large training and feedback overhead.In this paper,we consider the channel estimation in F-RANs with fog access point(F-AP)equipped with massive antennas.Thanks to the computing ability of F-AP and the sparsity of channel matrices in angular domain,Gated Recurrent Unit(GRU),a data-driven based channel estimation is proposed at F-AP to reduce the training and feedback overhead.The GRU-based method can capture the hidden sparsity structure automatically through the network training.Moreover,to further improve the channel estimation,a bidirectional GRU based method is proposed,whose target channel structure is decided by previous and subsequent structures.We compare the performance of our proposed channel estimation with traditional methods(Orthogonal Matching Pursuit(OMP)and Simultaneous OMP(SOMP)).Simulation results show that the proposed approaches have better performance compared with the traditional OMP and SOMP methods.展开更多
基金Project supported by Science Foundation of Shanghai Municipal Commission of Science and Technology (Grant No .04dz12045)
文摘This paper presents the design and implementation of access controller used for Ethernet passive optical network （ EPON）. As a first step to develop an ASIC product, the entire system is designed on a field programmable gate array （FPGA） with an embedded CPU. To reduce working frequency of the FPGA, the byte-to-word conversion is proposed. Propagation delays are equalized by ranging procedure so as to avoid data collision. Implementations of synchronization, classification, as well as Linux porting are illustrated in detail. The interface between the FPGA and CPU are also presented. Experimental results show that the proposed system can properly function in a relatively low cost FPGA.
基金supported in part by the State Major Science and Technology Special Project(Grant No.2018ZX03001023)the National Natural Science Foundation of China under No.61831002+1 种基金the National Science Foundation for Postdoctoral Scientists of China(Grant No.2018M641279)FundamentalResearch Funds for the Central Universities under Grant No.2018XKJC01
文摘As a promising paradigm of the fifth generation networks,fog radio access network(F-RAN)has attracted lots of attention nowadays.To fully utilize the promising gain of F-RANs,the acquisition of accurate channel state information is significant.However,conventional channel estimation approaches are not suitable in F-RANs due to the large training and feedback overhead.In this paper,we consider the channel estimation in F-RANs with fog access point(F-AP)equipped with massive antennas.Thanks to the computing ability of F-AP and the sparsity of channel matrices in angular domain,Gated Recurrent Unit(GRU),a data-driven based channel estimation is proposed at F-AP to reduce the training and feedback overhead.The GRU-based method can capture the hidden sparsity structure automatically through the network training.Moreover,to further improve the channel estimation,a bidirectional GRU based method is proposed,whose target channel structure is decided by previous and subsequent structures.We compare the performance of our proposed channel estimation with traditional methods(Orthogonal Matching Pursuit(OMP)and Simultaneous OMP(SOMP)).Simulation results show that the proposed approaches have better performance compared with the traditional OMP and SOMP methods.
