基于用户间干扰的分子通信模型的信道容量分析
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摘要
在扩散的多用户分子通信模型中,被释放的分子遵循布朗运动规则,不可避免地存在分子间码间干扰ISI(Inter-Symbol Interference)和用户间干扰IUI(Inter-User Interference)。因此,如何提高该系统的信道容量是目前分子通信模型研究的挑战之一。针对扩散的OOK(On-Off Keying)调制的多用户分子通信模型,分析了ISI和IUI,并通过最小平均错误概率准则得到了接收方纳米机器检测过程中的最优判决阈值,从而优化了信道容量。最后使用MATLAB仿真展示了不同的参数对该分子通信模型的信道容量性能的影响。仿真结果表明,通过设置适当的先验概率、增加扩散系数和时隙持续时间、减少发送方纳米机器和接收方纳米机器之间的距离和用户数,能够提高基于用户间干扰的分子通信模型的信道容量,并降低误码率。
In the diffusive multi-user molecular communication model,the released molecules follow Brownian motion rules,the Inter-Symbol Interference(ISI) and Inter-User Interference(IUI) among the molecules inevitably exist.Therefore,how to increase the channel capacity of system is a challenge in the current research on the molecular communication model.For the diffusive multi-user molecular communication model with On-Off Keying(OOK) modulation,the ISI and IUI were analyzed.The minimum average error probability criterion was used to obtain the optimal decision threshold in the detection process for the receiver nanomachine,and then the channel capacity was optimized.Finally,MATLAB simulations were used to demonstrate the effects of different parameters on the channel capacity performance of this molecular communication model.The simulation results show that by setting appropriate prior probability,increasing the diffusion coefficient and time slot duration,reducing the distance between the transmitter nanomachine and the receiver nanomachine and the number of users,the channel capacity of the molecular communication model based on IUI can be improved,and the bit error rate is reduced.
In the diffusive multi-user molecular communication model,the released molecules follow Brownian motion rules,the Inter-Symbol Interference(ISI) and Inter-User Interference(IUI) among the molecules inevitably exist.Therefore,how to increase the channel capacity of system is a challenge in the current research on the molecular communication model.For the diffusive multi-user molecular communication model with On-Off Keying(OOK) modulation,the ISI and IUI were analyzed.The minimum average error probability criterion was used to obtain the optimal decision threshold in the detection process for the receiver nanomachine,and then the channel capacity was optimized.Finally,MATLAB simulations were used to demonstrate the effects of different parameters on the channel capacity performance of this molecular communication model.The simulation results show that by setting appropriate prior probability,increasing the diffusion coefficient and time slot duration,reducing the distance between the transmitter nanomachine and the receiver nanomachine and the number of users,the channel capacity of the molecular communication model based on IUI can be improved,and the bit error rate is reduced.
引文
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[3] ISLAM M S,VJ L.Nanoscale materials and devices for future communication networks[J].IEEE Communications Magazine,2010,48(6):112-120.
[4] PIEROBON M,AKYILDIZ I F.Fundamentals of diffusion- based molecular communication in nanonetworks[J].Foundations & Trends in Communications & Information Theory,2013,8(1-2):1-147.
[5] LI Z P,ZHANG J,CAI S B,et al.Review on molecular communication[J].Journal on Communications,2013,34(5):152-167.(in Chinese)黎作鹏,张菁,蔡绍滨,等.分子通信研究综述[J].通信学报,2013,34(5):152-167.
[6] NAKANO T,MOORE M,ENOMOTO A,et al.Molecular communication technology as a biological ICT[M].Berlin:Biological Functions for Information and Communication Technologies,2011:49-86.
[7] WANG J X,YIN B,PENG M G.Diffusion based molecular com- munication:principle,key technologies,and challenges[J].China Communications,2017,14(2):1-18.
[8] NAKANO T,MOORE M J,WEI F,et al.Molecular communi- cation and networking:opportunities and challenges[J].IEEE Transactions on Nanobioscience,2012,11(2):135-148.
[9] FARSAD N,YILMAZ H B,ECKFORD A,et al.A comprehensive survey of recent advancements in molecular communication[J].IEEE Communications Surveys & Tutorials,2017,18(3):1887-1919.
[10] PIEROBON M,AKYILDIZ I F.Intersymbol and co-channel interference in diffusion-based molecular communication[C]//IEEE International Conference on Communications.Ottawa:IEEE Press,2012:6126-6131.
[11] NAKANO T,OKAIE Y,LIU J Q.Channel model and capacity analysis of molecular communication with brownian motion[J].IEEE Communications Letters,2012,16(6):797-800.
[12] HSIEH Y P,SHIH P J,LEE Y C,et al.An asynchronous communication scheme for molecular communication[C]//IEEE International Conference on Communications.Ottawa:IEEE Press,2012:6177-6182.
[13] LIU Q,YANG K.Channel capacity analysis of a diffusion-based molecular communication system with ligand receptors[M].Hoboken:John Wiley and Sons Ltd.2015:1508-1520.
[14] PIEROBON M,AKYILDIZ I F.Capacity of a diffusion-based molecular communication system with channel memory and molecular noise[J].IEEE Transactions on Information Theory,2013,59(2):942-954.
[15] MUSTAM S M,SYED-YUSOF S K,ZUBAIR S.Capacity and delay spread in multilayer diffusion-based molecular communication channel[J].IEEE Transactions on Nanobioscience,2016,15(7):599-612.
[16] MENG L S,YEH P C,CHEN K C,et al.Optimal detection for diffusion-based communications in the presence of ISI[C]//Global Communications Conference.Anaheim:IEEE Press,2012:3819-3824.
[17] AWAN H,CHOU C T.Improving the capacity of molecular communication using enzymatic reaction cycles[J].IEEE Transa-ctions on Nanobioscience,2017,16(8):744-754.
[18] BICEN A O,LEHTOMAKI J J,AKYILDIZ I F.Shannon meets Fick on the microfluidic channel:diffusion limit to sum broadcast capacity for molecular communication[J].IEEE Transactions on Nanobioscience,2018,17(1):88-94.
[19] MENG L S,YEH P C,CHEN K C.MIMO communications based on molecular diffusion[C]//Anaheim:Global Communications Conference,2013:5380-5385.
[20] JIANG C,CHEN Y,LIU K J R.Inter-user interference in molecular communication networks[C]//IEEE International Conference on Acoustics.Florence:IEEE Press,2014:5725-5729.
[21] MENG L S,YEH P C,CHEN K C,et al.A diffusion-based binary digital communication system[C]//IEEE International Conference on Communications.Ottawa:IEEE Press,2012:4985-4989.
[22] KEENER R W.Probability and measure[J].Journal of the American Statistical Association,2012,91(433):1-24.
[23] KABIRM H,KWAK K S.Molecularnanonetwork channel model[J].Electronics Letters,2013,49(20):1285-1287.