融合小波的D2D技术在电力应急通信中的应用
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摘要
为在公网盲区建立高效、稳定的应急通信网络,文中首先介绍了D2D自组网通信系统,其次研究并提出一种改进的基于小波变换的图像压缩技术,并应用于D2D自组网络,最后分别进行了对比实验。证明该压缩技术的编解码效率更高、重构图像的质量更好,图像在融合该压缩技术的D2D自组网下传输时延更小,提高了数据传输速率和网络畅通性。利用融合小波变换的D2D技术能够更高效地传输突发事件现场的数据信息,更好满足电力应急通信的实际需求。
In order to establish an efficient and stable emergency communication network in the blind area of the public area,the communication system of D2 D ad hoc network is introduced in this paper.Secondly, an improved image compression technology based on wavelet transform is proposed.Compression technology is fused into D2 D ad hoc network. Finally,a comparative experiment is carried out. Experiment results show that improved compression technology in this paper presents higher efficiency at coding and decoding and better quality in reconstructed images. Moreover,time-delay of image transmission in D2 D ad hoc network fused with this compression technology is smaller,which can improve rate of data transmission and network patency. The D2 D technology based on the fusion of wavelet transform can transmit more efficiently data information of emergency scene,which can better meet actual needs of power emergency communication.
In order to establish an efficient and stable emergency communication network in the blind area of the public area,the communication system of D2 D ad hoc network is introduced in this paper.Secondly, an improved image compression technology based on wavelet transform is proposed.Compression technology is fused into D2 D ad hoc network. Finally,a comparative experiment is carried out. Experiment results show that improved compression technology in this paper presents higher efficiency at coding and decoding and better quality in reconstructed images. Moreover,time-delay of image transmission in D2 D ad hoc network fused with this compression technology is smaller,which can improve rate of data transmission and network patency. The D2 D technology based on the fusion of wavelet transform can transmit more efficiently data information of emergency scene,which can better meet actual needs of power emergency communication.
引文
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[11]周斌,胡宏林.提高蜂窝网络中数据分发效率的D2D协作转发算法[J].电子与信息学报,2012,34(3):704-709.
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[13]Marco B,Gabor,Demiad P,et al. Benchmarking practical RRM algorithms for D2D communications in LTE advanced[J]. Wireless Personal Communications,2015,82(2):883-910.
[14]谢小军,梁本仁.基于4G的应急通信在安徽电力的应用[J].通信技术,2013,46(4):84-86.
[15]詹为,段先华,於跃成.基于小波变换的图像压缩编码方法研究[J].计算机技术与发展,2018,28(6):21-25.
[16]Goldberg M A,Pivovarov M,Mayo-Smith W W,et al. Application of wavelet compression to digitized radiographs[J]. American Journal of Roentgenology,1994,163(2):463-468.
[17] Zhang Ning,Zhu Jin-fu. Study on image compression and fusion based on the wavelet transform technology[J]. International Journal on Smart Sensing&Intelligent Systems,2015,8(1):480-496.
[2]方祥雷,方显业,李亚雷,等.浙江电力应急通信系统建设[J].电力信息与通信技术,2015,13(5):97-100.
[3]王俊义,巩志帅,符杰林,等. D2D通信技术综述[J].桂林电子科技大学学报,2014,34(2):114-119.
[4]王继业,孟坤,曹军威,等.能源互联网信息技术研究综述[J].计算机研究与发展,2015,52(5):1109-1126.
[5]陈望勇.移动通信基站常见故障处理方法与实践[J].江苏科技信息,2016(32):58-59.
[6]樊昌信,詹道庸,徐炳祥,等.通信原理第四版[M].北京:国防工业出版社,1999:22-42.
[7]颜学文,董超,屈毓锛.基于D2D通信的流量卸载技术综述[J].计算机科学,2018,45(11):45-51.
[8]陈耀华,贾鸿. D2D技术应用于地铁控制系统中的方案研究[J].铁道通信信号,2018,54(8):12-14.
[9]文凯,卢彦博,刘敏,等. D2D通信系统中一种资源分配算法的研究[J].南京邮电大学学报:自然科学版,2015,35(6):31-38.
[10]陈洪军,苏爱国. COFDM技术及其典型应用[J].移动通信,2012,36(3):50-53.
[11]周斌,胡宏林.提高蜂窝网络中数据分发效率的D2D协作转发算法[J].电子与信息学报,2012,34(3):704-709.
[12]Asadi A,Wang Q,Mancuso V. A survey on Device-to-Device communication in cellular networks[J]. Communications Surveys&Tutorials,2014,16(4):1801-1819.
[13]Marco B,Gabor,Demiad P,et al. Benchmarking practical RRM algorithms for D2D communications in LTE advanced[J]. Wireless Personal Communications,2015,82(2):883-910.
[14]谢小军,梁本仁.基于4G的应急通信在安徽电力的应用[J].通信技术,2013,46(4):84-86.
[15]詹为,段先华,於跃成.基于小波变换的图像压缩编码方法研究[J].计算机技术与发展,2018,28(6):21-25.
[16]Goldberg M A,Pivovarov M,Mayo-Smith W W,et al. Application of wavelet compression to digitized radiographs[J]. American Journal of Roentgenology,1994,163(2):463-468.
[17] Zhang Ning,Zhu Jin-fu. Study on image compression and fusion based on the wavelet transform technology[J]. International Journal on Smart Sensing&Intelligent Systems,2015,8(1):480-496.