Cooperative for Nanonetwork

Liang Hong 1, Wei Chen 2 Feng Liu 1Department of Electrical and Computer Engineering Department of Electronic Engineering 2Department of Computer Science College of Information Engineering Tennessee State University, Nashville, TN 37209, USA Shanghai Maritime University, Shanghai, 201306, China

Abstract — Molecular communication is the most promising In this paper, we propose and evaluate a novel cooperative approach for the communication in nanonetwork. However, the molecular communication solution to improve system reliability of existing system degrades rapidly when the distance reliability. Each node is a nano-machine with molecule tankage between transmitter and receiver increases. In this paper, we as that in [3]. The signals are repeated by the nano-machines propose and evaluate a cooperative molecular communication located between the transmitter and receiver. There is no need solution that uses signal repeating to improve system reliability. of grouping and coordination. Therefore, the system has low The system has low complexity. Simulation results show that the complexity and is easy to implement. Moreover, simulation bit error rate is much lower than non-cooperative scheme. results show that in the cooperative relay due to the distance between each pair of transmitter and receiver is shorter, the Keywords—Cooperative; molecular communication; relay; nanonetwork communication reliability is largely improved. The remainder of this paper is organized as follows. In Section II, the cooperative communication model is presented.

I. INTRODUCTION In Section III, the decode-and-forward relay scheme is enables the development of devices in a elaborated. In Section IV, simulation results are presented. scale ranging from one to a few hundred nanometers. At nano scale, the most basic functional unit is a nano-machine, which II. COOPERATIVE COMMUNICATION SYSTEM MODEL is able to perform simple tasks such as , data storing, Fig. 1 illustrates the proposed system model for cooperative sensing or actuation [1]. Communication among nano- communication system with two-hop communication. The machines will expand the capabilities and applications of number of hops will be larger with more relay nano-machines. individual nano-devices in terms of both complexity and range In each hop, the unguided diffusion-based molecular of operation. Nanonetwork, a new network paradigm, is communication is used for realizing wireless communication formed with the interconnection of nano-machines to cover between nano-machines. larger areas, perform additional in-network processing, and fulfill complex tasks. It promises new solutions for many applications in biomedical, industrial, and military fields [2]. Molecular communication is the most promising approach for the communication between nano-machines [1]. Currently, extensive studies have been conducted for the molecular communication in physical channel model [3], forward error correction codes [4], bit error rate performance [5], and channel capacity [6]. However, as shown in Section III, the reliability of one transmitter and one receiver communication system degrades rapidly when the distance between transmitter and receiver increases. Recently, cooperation-based approaches that using multiple-input multiple-output (MIMO) technique Fig. 1. Molecular Communication and Network Model [7], multi-hop communication [8], and collaborative relay [9] have been reported in the literature. However, The MIMO The system is composed of components functioning as scheme classified the nano-machines in nanonetwork into two information molecules that represent the information to be groups, the transmitting cluster and receiving cluster. To use transmitted, transmitter nano-machines that release the the MIMO diversity gain, all randomly located nano-machines information molecules, receiver nano-machines that detect in the transmitting cluster must have the same information and information molecules, relay nano-machines that have the be perfectly coordinated. It is not practical for real molecular capability of molecule emission and reception, and the communication. On the other hand, the multi-hop and environment in which the information molecules propagate collaborative relay schemes required that each node in from the transmitter nano-machine to the receiver nano- nanonetwork was a cluster of large amount of nano-machines machine. It is assumed that each nano-machine has a self- (genetically engineered bacteria agents). This assumption is identifying label that can be attached to the transmitted also not practical because the need of grouping and molecules to providing addressing scheme. The information coordination will significantly increase system complexity. molecule includes the sender address, information and the receiver address. The processes of communication in each hop and the receiver nano-machine is 2000nm. When cooperation include: encode information into an information molecule by is used, relays are located evenly between the transmitter nano- the transmitter nano-machine, send the information molecule machine and the receiver nano-machine, that is, the distance into the environment, propagation of the information molecule between adjacent nano-machine is 500nm. Relay selection through the environment, receive the information molecule by scheme will be reported in future work. Fig. 4 shows the bit the receiver nano-machine, and finally decode the information error rate comparison with and without cooperation. It is clear molecule into a chemical reaction at the receiver nano- that the bit error rate is much lower when the cooperative machine. technique (relay) is used.

III. DECODE -AND -FORWARD RELAY SCHEME Similar to any other communication system, modulation is an indispensable process in the transmitter. The demodulation is the corresponding reverse process to the modulation process in the receiver. Four different modulation techniques, concentration shift keying (CSK) [4], pulse position modulation (PPM) [3], molecule shift keying (MoSK) [3], and Zebra-CSK [10], have been reported in the literature for M-ary molecular communication. Due to the channel memory, CSK is shown to be better than PPM with less inter-symbol interference and less average amount of released molecules per message [2]. On the other hand, the complexity of transmitter and receiver nano-machines using MoSK and Zebra-CSK is much higher than that using CSK, which is not practical. Fig. 4. Bit error rate comparison Therefore, we use CSK modulation in physical layer. As shown in Fig. 2, simulations with N3Sim [11], a AKNOWLEDGEMENT simulation framework for the general case of diffusion-based This work was paritially supported by the National Natural Science molecular communication, indicate that the propagation time Foundation of China (61271283), the Innovation Program of Shanghai of molecules increases with the square of distance, the number Municipal Education Commission (14YZ113), and the Science & Technology of received molecules decreases with distance. Therefore, Program of Shanghai Maritime University (20120107). using cooperative technique where some nano-machines repeat REFERENCES the transmitted signal can help information reach the receiver much faster and more reliable. Fig. 3 shows the proposed relay [1] I. F. Akyildiz and J. M. Jornet, “The of nano-things,” IEEE Wireless Communications, vol. 17, no. 6, pp. 58–63, Dec. 2010. scheme, where Tx stands for transmitter nano-machine, Relay [2] N. Garralda, I. Llatser, A. Cabellos-Aparicio and M. Pierobon, repeats the signal, and Rx stands for receiver nano-machine. “Simulation-based evaluation of the diffusion-based physical channel in Decode and forward strategy is used for relay. molecular nanonetworks,” in Proc. IEEE Intl. Workshop on Molecular and Nano Scale Communication (MoNaCom), INFOCOM, Shanghai, China, Apr. 2011, pp. 443-448. [3] H. ShahMohammadian, G. G. Messier and S. Magierowski, “Optimum receiver for molecule shift keying modulation in diffusion-based molecular communication channels,” Nano Communication Networks, vol. 3, no. 3, pp. 183-195, Sep. 2012. [4] M. S. Leeson and M. D. Higgins, “Forward error correction for molecular communications, ” Nano Communication Networks, vol. 3, no. 3, pp. 161-167, Sep. 2012. [5] M. H. Kabir and K. S. Kwak, “Effect of memory on BER in molecular communication,” Electronics Letters, vol. 50, no. 2, pp. 71-72, Jan. Fig. 2. Impact of transmitter-receiver distance on the number of 2014. received information molecules. [6] B. Atakan and O. B. Akan, “Deterministic capacity of information flow in molecular nanonetworks,” Nano Communication Networks, vol. 1, no. 1, pp. 31-42, Mar. 2010. [7] L. Meng, P. Yeh, K. Chen and I. F. Akyildiz, “MIMO communications based on molecular diffusion,” in Proc. IEEE Globecom, pp. 5380-5385, Fig. 3. Decode-and-forward relay scheme Dec. 2012, Anaheim, CA. [8] A. Einolghozati, M. Sardari, A. Beirami and F. Fekri, “Data Gathering in networks of bacteria colonies: Collective sensing and relaying using IV. SIMULATION RESULTS molecular communication,” in Proc. IEEE INFOCOM, pp. 256-261, Mar. 2012, Orlando, FL. In order to evaluate the performance of the proposed [9] A. Einolghozati, M. Sardari and F. Fekri, “Relaying in diffusion-based cooperative molecular communication scheme, computer molecular communication,” in Proc. IEEE International Symposium on simulations were conducted. The signal propagation model in Information Theory, pp. 1844-1848, Jul. 2013, Istanbul, Turkey. [4] was used in simulation with one sample per symbol. The [10] S. Pudasaini, S. Shin and K. S. Kwak, “Robust modulation technique for coefficients for the residual noise in this model were obtained diffusio –based molecular communication in nanonetworks,” arXiv:1401.3938. using Matlab curve-fitting tool on the N3Sim results. In [11] N3Sim, http://www.n3cat.upc.edu/n3sim. simulations, the distance between the transmitter nano-machine