For nano-scale communications, there must be cooperation and simultaneous communication between nano devices. To this end, in this paper, we investigate two-way (a.k.a. bi-directional) molecular communications between nano devices. If different types of molecules are used for the communication links, the two-way system eliminates the need to consider self-interference. However, in many systems, it is not feasible to use a different type of molecule for each communication link. Thus, we propose a two-way molecular communication system that uses a single type of molecule. We derive a channel model for this system and use it to analyze the proposed system's bit error rate, throughput, and self-interference. Moreover, we propose analog- and digital- self-interference cancellation techniques. The enhancement of link-level performance using these techniques is confirmed with both particle-based simulations and analytical results.

In this paper, we address the symbol synchronization issue in molecular communication via diffusion (MCvD). Symbol synchronization among chemical sensors and nanomachines is one of the critical challenges to manage complex tasks in the nanonetworks with molecular communication (MC). As in diffusion-based MC, most of the molecules arrive at the receptor closer to the start of the symbol duration, the wrong estimation of the start of the symbol interval leads to high symbol detection error. By utilizing two types of molecules with different diffusion coefficients we propose a synchronization technique for MCvD. Moreover, we evaluate the symbol-error-rate performance under the proposed symbol synchronization scheme for equal and non-equal symbol duration in MCvD systems.

Molecular communication underpins biological system coordination across multiple spatial and temporal scales. Whilst significant research has focused on micro-scale diffusion dominated channels, far less is understood of macro-scale flow dominated channels. The latter introduces complex fluid dynamic forces, one of which is turbulent diffusion. Molecular Communication via Turbulent Diffusion (MCvTD) more accurately reflects realistic molecular channels in both pheromone signaling and chemical engineering. Current literature assumes linear combining between sequential molecular signals, but this assumption may not hold when turbulence is introduced. Here, we use computational fluid dynamics (CFD) simulation to show that sequential MCvTD signals do indeed linearly combine. This is a non-trivial and non-intuitive result and our conclusion allows the research field to leverage on existing linear combining signal analysis. To ensure robustness of our results, we test for the received signal strength and Inter-Symbol-Interference (ISI) under different concentrations, co-flow rate, and the information sequence. Also, we introduce a basis for the channel model in a way that for any k sequential signals in which k ≥ 4, by understanding the 1 ≤ k ≤ 3 signals and the last signal, we can represent the other signals. We expect these results to be useful to both molecular communication and biological signaling researchers.

In this paper, we propose a low complexity direction of arrival (DoA) estimation algorithm that operates in radio frequency (RF) lens-embedded millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. In mmWave system, to compute the beamforming weighting coefficients in real-time, precise DoA estimation with low complexity is essential. We first investigate the conventional DoA estimation algorithms in mmWave MIMO systems and evaluate its performance. Then we introduce the Power pROfile Based Estimation (PROBE) algorithm for DoA estimation that operates in the RF lens-embedded system. We elaborate on the computational complexity of each algorithm in terms of the number of multiplication operations. We show that the proposed algorithm has a significant performance advantage in terms of estimation accuracy over other conventional algorithms in a complexity-constrained environment.

Inspired by the eye diagram in classical radio frequency (RF) based communications, the MOL-Eye diagram is proposed for the performance evaluation of a molecular signal within the context of molecular communication. Utilizing various features of this diagram, three new metrics for the performance evaluation of a molecular signal, namely the maximum eye height, standard deviation of received molecules, and counting SNR (CSNR) are introduced. The applicability of these performance metrics in this domain is verified by comparing the performance of binary concentration shift keying (BCSK) and BCSK with consecutive power adjustment (BCSK-CPA) modulation techniques in a vessel-like environment with laminar flow. The results show that, in addition to classical performance metrics such as biterror rate and channel capacity, these performance metrics can also be used to show the advantage of an efficient modulation technique over a simpler one.

This paper presents spatial diversity techniques applied to multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC). Two types of spatial coding techniques, namely Alamouti-type coding and repetition MIMO coding are suggested and analyzed. In addition, we consider receiver-side equal-gain combining, which is equivalent to maximum-ratio combining in symmetrical scenarios. For numerical analysis, the channel impulse responses of a symmetrical 2 × 2 MIMO-DBMC system are acquired by a trained artificial neural network. It is demonstrated that spatial diversity has the potential to improve the system performance and that repetition MIMO coding outperforms Alamouti-type coding.

In molecular communication, the heavy tail nature of molecular signals causes inter-symbol interference (ISI). Because of this, it is difficult to decrease symbol periods and achieve high data rate. As a probable solution for ISI mitigation, enzymes were proposed to be used since they are capable of degrading ISI molecules without deteriorating the molecular communication. While most prior work has assumed an infinite amount of enzymes deployed around the channel, from a resource perspective, it is more efficient to deploy a limited amount of enzymes at particular locations and structures. This paper considers carrying out such deployment at two structures-around the receiver (Rx) and/or the transmitter (Tx) site. For both of the deployment scenarios, channels with different system environment parameters, Tx-to-Rx distance, size of enzyme area, and symbol period, are compared with each other for analyzing an optimized system environment for ISI mitigation when a limited amount of enzymes are available. \n

In active transport molecular communication (ATMC), information particles are actively transported from a transmitter to a receiver using special proteins. Prior work has demonstrated that ATMC can be an attractive and viable solution for on-chip applications. The energy consumption of an ATMC system plays a central role in its design and engineering. In this work, an energy model is presented for ATMC and this model is used to provide guidelines for designing energy efficient systems. The channel capacity per unit energy is analyzed and maximized. It is shown that based on the size of the symbol set and the symbol duration, there is a vesicle size that maximizes the rate per unit energy. It is also demonstrated that maximizing the rate per unit energy yields very different system parameters compared to maximizing the rate only.

Due to the limited environments of radio frequency resources, the frequency assignment problem (FAP) is a crucial issue. We especially focus on the system that requires re-assignment of the frequencies often, so that the operation time is a limited resource as well as the radio resource. The FAP is closely related to the graph coloring problem, which is NP-hard problem. In this paper, we investigate a frequency assignment problem from a graph theory perspective for those limited system. We propose an effective algorithm based on the graph coloring theory and randomization incorporation into greedy heuristics. Main concern of the frequency assignments to clustered nodes is to reduce the number of used frequencies and the range. This paper has its another novelty in considering realistic interference constraints by considering net filter discrimination and measurement data from the field. Performance analysis is done by synthetic and measured data, and we observe a significant improvements by employing proposed algorithms in both cases.

In diffusion-based molecular communication, information transport is governed by diffusion through a fluid medium. The achievable data rates for these channels are very low compared to the radio-based communication system, since diffusion can be a slow process. To improve the data rate, a novel multiple-input multiple-output (MIMO) design for molecular communication is proposed that utilizes multiple molecular emitters at the transmitter and multiple molecular detectors at the receiver (in RF communication these all correspond to antennas). Using particle-based simulators, the channel's impulse response is obtained and mathematically modeled. These models are then used to determine interlink interference (ILI) and intersymbol interference (ISI). It is assumed that when the receiver has incomplete information regarding the system and the channel state, low complexity symbol detection methods are preferred since the receiver is small and simple. Thus, four detection algorithms are proposed-adaptive thresholding, practical zero forcing with channel models excluding/including the ILI and ISI, and Genie-aided zero forcing. The proposed algorithms are evaluated extensively using numerical and analytical evaluations.

In this paper, we propose a novel design for molecular communication in which both the transmitter and the receiver have, in a 3-dimensional environment, multiple bulges (in RF communication this corresponds to antenna). The proposed system consists of a fluid medium, information molecules, a transmitter, and a receiver. We simulate the system with a one-shot signal to obtain the channel's finite impulse response. We then incorporate this result within our mathematical analysis to determine interference. Molecular communication has a great need for low complexity, hence, the receiver may have incomplete information regarding the system and the channel state. Thus, for the cases of limited information set at the receiver, we propose three detection algorithms, namely adaptive thresholding, practical zero forcing, and Genie-aided zero forcing.

In molecular communication information is transferred with the use of molecules. Molecular multiple-input multiple- output (MIMO) system with drift (positive velocity) at macro- scale will be presented and the improvement against single- input single-output (SISO) molecular communication systems will be verified via our testbed. Until now it was unclear whether MIMO techniques, which are extensively used in modern radio frequency (RF) communications, could be applied to molecular communication. In the demonstration, using our MIMO testbed we will show that we can achieve nearly 1.7 times higher data rate than SISO molecular communication systems. Moreover, signal-to-inter-link-interfeence metric for one-shot signal will be depicted for a given symbol duration.

Latest regulations on TV white space communications and trend toward spectrum access through geolocation databases relax the regulatory constraints on cognitive radios. Radio environment map REM is a kind of improved geolocation database and an emerging topic with the latest regulations on TV white space communications. It constructs a comprehensive temperature map of the cognitive radio network operation area by utilizing multi-domain information from geolocation databases, characteristics of spectrum use, geographical terrain models, propagation environment, and regulations. REMs act as cognition engines by building long-term knowledge via processing spectrum measurements collected from sensors to estimate the state of locations without any measurement data. Active transmitter LocatIon Estimation based REM construction technique is proposed and compared with the well-known REM construction techniques such as Kriging and inverse distance weighted interpolation in shadow and multipath fading channels. The simulation results suggest that the LocatIon Estimation based REM construction outperforms the compared methods in terms of RMSE and correct detection zone ratio by utilizing additional information about channel parameters that can be estimated by classical least squares method easily.Copyright © 2013 John Wiley & Sons, Ltd.

In cognitive radio, current trend is to utilize geolocation database for TV bands. Considering more dynamic bands in terms of primary user activity, however, necessitates the use of Radio Environment Map (REM), which is an advanced knowledge base that stores live multidomain information on the entities in the network and the environment. In Cognitive Radio Networks (CRNs), mobile nodes that are capable of measuring the energy of the frequency bands are less capable compared to dedicated sensing nodes in the network. Therefore, deployment algorithm of the dedicated sensor nodes is of great importance and affects the constructed REM interference map quality. We propose a novel deployment algorithm for CRNs that considers user distribution probabilities. Numerical results confirm that the proposed deployment algorithm significantly improves the REM performance. The proposed algorithm is compared with random deployments and it is applied on Kriging and LIvE REM construction techniques.

Dynamic access to spectrum requires detecting the free spaces in close proximity. Since non-cooperative sensing methods cannot satisfy most of the basic requirements, different cooperative sensing algorithms have been proposed to overcome this problem. In the previous works, multiple secondary users cooperate to achieve better primary user detection. However, taking into account the measurements from distant users actually aggravates the detection decision. In this paper, we propose the Zone-based Sensing (ZoneS) method, which is a distributed cooperative sensing method that circumvents the problems that arise from the cooperation between distant nodes. The simulations are performed with different parameters and with majority cooperation rule for the users in each zone. The false alarm, missed detection, blocking and dropping probabilities, and channel utilization are examined to assess the effectiveness of ZoneS. The proposed method enables the utilization of spectrum bands that would be left unused otherwise, while keeping the probabilities of missed detection and false alarm bounded. Furthermore, the coordination among secondary users is achieved without any overhead.

Cooperative spectrum sensing is a key feature to increase sensing probability in Cognitive Radio. However, sensing observations may still be received in error when overhead due to error correction is avoided in bandwidth-limited imperfect reporting channels. This paper presents how decision logics are affected by the imperfect reporting channel. Firstly, we present performance analysis of three hard decision logics, which are Or Logic, 3/N Logic and Majority Logic. Our second analysis focuses on effect of probability of error between the Fusion Center and the Cognitive Radio Nodes. In this analysis, we also analyze two different error recovery methods. Analysis is done under three different channel models, which are Additive White Gaussian Noise Channel, flat fading Rayleigh Channel, and Nakagami Channel.

Abstract Cognitive radio heralds the next step in the evolution of wireless communications. In this paper, an analytical model for infrastructure based cognitive radio systems is proposed, and its performance is evaluated under bursty traffic scenarios in a multiple cell environment. Performance metrics like probabilities of dropping and blocking for primary and secondary users as well as forced termination and forced frequency handoff for secondary users are investigated, and the analytical model is verified with simulations. In addition to the analytical model, a new resource planning method is proposed to compensate for uneven traffic load distribution. The proposed method considers offered traffic, hop count to the heavily loaded cell, and velocity of mobile users during resource planning and performs better in terms of probability of blocking, dropping, and forced termination. The proposed method is promising in balancing the system performance measures, yet there is room for further improvement for finding a closed formula for the proposed analytical model. Copyright © 2010 John Wiley & Sons, Ltd.

Communication via diffusion of molecules is an effective method for transporting information in nanonetworks. In this paper, novel modulation techniques called Concentration Shift Keying (CSK) and Molecule Shift Keying (MSK) are proposed for coding and decoding information of the so-called messenger molecule concentration waves in nanonetworks. The first technique, CSK, modulates the information via the variation in the concentration of the messenger molecules whereas MSK utilizes different types of messenger molecules to represent the information. Using simulation, the performance of these modulation techniques is evaluated in terms of susceptibility to noise and transmission power requirements. The new techniques achieve high channel capacity values, in particular, the MSK technique exhibits more robustness against noise and requires less power.

Cooperative spectrum sensing for dynamic spectrum access to unused licensed spectrum has been proposed as a solution to the spectrum scarcity problem. In this paper, a novel sensing algorithm, Cooperative Sensing with Decision Vector (CSDV), that employs uniform quantizer and a weight vector for global decision logic, is proposed. CSDV method is based on energy detection and performs better than conventional hard decision algorithms such as MAJORITY and M/N in terms of probability of detection and false alarm at the cost of a marginal increase in overhead bits. Probability of detection is maximized for a given probability of false alarm by proposed method via convex optimization. For detailed analysis, CSDV is compared with equal gain combiner scheme, which performs far better than hard decision algorithms, via highest bandwidth requirement. Moreover, robustness of CSDV method to sensing error is analyzed when some nodes always report false decisions to the fusion center.