Recent years have shown a rapid increase in the amount of study devoted to communication systems where molecules are information carriers. The reasons for such interest are varied, from seeking to understand the ubiquity of molecular communication in biology to the search for communication methods in media where electromagnetic and acoustic methods are inappropriate, to exploring the energy efficiency of methods where some delivery latency can be allowed. With this tutorial on recent discrete molecular communication research, we seek to organize the work into broad categories and thence under the umbrella of what can be called “inscribed matter communication,” where information is conveyed through assemblage, release, and capture of matter as opposed to the transmission of photons or phonons. We will begin by considering discrete passage of molecules between senders and receivers, and argue that matter emission and detection, even at Avogadrian levels, are a subset of the discrete problem, all with a focus on point-to-point communication. In this way, we hope to contextualize current work within a larger fundamental framework, illuminate the hard boundaries of what is known, and then stimulate further research on this fascinating topic.

We consider data transfer between a chemical vapor emitter and photoionization detectors (PIDs) under constant velocity gas flow in a constrained environment (flow tube). We show that the system, though stochastic owing to flow unsteadiness, is (on average) linear and then characterize the channel using a Karhunen-Loeve (KL) expansion. We measure bit error rates using straightforward detection methods in the KL-produced signal space. Data rates of 20bps are easily achieved at ≈ 10-3error rate and we suspect that similarly low error rates are achievable at much higher bit rates using suitable adaptive equalization methods.

In this paper, we consider a downlink multiuser network operating with finite blocklength codes under statistical quality of service (QoS) constraints. An optimal power allocation algorithm is studied to maximize the normalized sum throughput under QoS constraints. We first determine the finite blocklength (FBL) throughput formulations and subsequently state optimization problems. We show the convexity of the power allocation problem under certain conditions and propose an optimal algorithm to solve the problem. Via numerical analysis, we demonstrate the performance improvements with the optimal power allocation. In addition, we provide interesting insights on the system behavior by characterizing the impact of the error probability, the QoS-exponent and blocklength on the performance.

In this paper, energy-efficient and secure communication over wireless fading channels is investigated when data arrivals are modeled as Markovian processes (e.g., discrete Markov and Markov fluid processes) in the presence of limitations on buffer overflow probabilities. It is assumed that the transmitter knows only the distributions of the fading coefficients in both the eavesdropper's and legitimate user's channels. Consequently, data transmissions occur at fixed rates, with secrecy outage happening when the instantaneous secrecy capacity is less than the fixed rate. In this setting, by employing the effective bandwidth and effective capacity formulations, throughput expressions are derived, and energy efficiency metrics, namely minimum energy per bit and wideband slope, are determined. Overall, the impact of source and channel variations as well as the delay quality of service (QoS) requirements on the energy efficiency of secure communications is identified.

In this paper, we consider a downlink multiuser network operating with finite blocklength (FBL) codes under statistical quality of service (QoS) constraints. Optimal power allocation algorithms are studied to maximize the normalized sum throughput under QoS constraints, while considering different types of data arrivals, namely, constant-rate, Markov, and Markov-modulated Poisson arrivals. We first determine the FBL throughput formulations and subsequently state optimization problems. We show the convexity of the power allocation problem under certain conditions and propose optimal algorithms (for scenarios with different data arrivals). In addition, the FBL performance of equal power allocation and a sub-optimal power allocation algorithm is discussed. Via numerical analysis, we demonstrate the performance improvements with the optimal power allocation. In addition, we provide interesting insights on the system behavior by characterizing the impact of the error probability, the QoS exponent, the blocklength, the number of users, and the source burstiness on the performance.

In this paper, throughput and energy efficiency of secure wireless transmission of delay sensitive data generated by random sources is studied. A fading broadcast model in which the transmitter sends confidential and common messages to two receivers is considered. It is assumed that the common and confidential data, generated from Markovian sources, are stored in buffers prior to transmission, and the transmitter operates under constraints on buffer/delay violation probability. Under such statistical quality-of-service constraints, effective capacity of time-varying wireless transmissions and effective bandwidth of Markovian sources are employed to determine the throughput. In particular, secrecy capacity is used to describe the service rate of buffers containing confidential messages. Moreover, energy per bit is used as the energy efficiency metric and energy efficiency is studied in the low signal-to-noise regime. Specifically, minimum energy per bit required for the reliable communication of common and confidential messages is determined and wideband slope expressions are identified. The impact of buffer/delay constraints, correlation between channels, source characteristics/burstiness, channel knowledge at the transmitter, power allocation, and secrecy requirements on the throughput and energy efficiency of common and confidential message transmissions is identified.

This paper studies energy-efficiency (EE) and throughput optimization in the presence of randomly arriving data and quality of service (QoS) constraints. For this purpose, maximum average arrival rates supported by transmitting signals with arbitrary input distributions are initially characterized in closed form by employing the effective bandwidth of time-varying sources (e.g., discrete-time Markov and Markov fluid sources, and discrete-time and continuous-time Markov modulated Poisson sources) and effective capacity of the time-varying wireless channel. Subsequently, EE is formulated as the ratio of the maximum average arrival rate to the total power consumption, in which circuit power is also taken into account. Following these characterizations, the optimal power control policies maximizing the EE or maximizing the throughput under a minimum EE constraint are obtained. Through numerical results, the performance of the optimal power control policies is evaluated for different signal constellations and is also compared with that of constant power transmission. The impact of QoS constraints, source characteristics, circuit power, input distributions on the EE, and the throughput is analyzed.

Power control policies in the fading multiple-access channels (MAC) with quality of service (QoS) constraints and random arrivals are studied. Perfect channel side information (CSI) is assumed to be available at both the transmitters and the receiver. Two types of Markovian sources, namely discrete Markov source and Markov fluid source, are considered. The maximum average arrival rates that can be supported in the fading multiple-access channel under QoS constraints are identified by incorporating the effective capacity of time-varying wireless transmission channels and effective bandwidth of random arrivals. The average throughput region is shown to be convex. Power control policies that maximize the weighted summation of the average arrival rates are characterized in the two-user case. Specifically, given the decoding order strategy, the conditions that the optimal power control policies must satisfy are determined, and an algorithm for the optimal power control policies is proposed for different source arrival models.

This paper proposes optimal power adaptation schemes that maximize the energy efficiency (EE) in the presence of Markovian sources and finite-alphabet inputs subject to quality of service (QoS) constraints. First, maximum average arrival rates supported by transmitting signals with arbitrary input distributions are characterized in closed-form by employing the effective bandwidth of time-varying sources (e.g., discrete-time Markov and Markov fluid sources) and effective capacity of the time-varying wireless channel. Subsequently, EE is defined as the ratio of the maximum average arrival rate to the total power consumption, in which circuit power is also taken into account. Following these characterizations, an optimization problem is formulated to maximize the EE of the system, and optimal power control schemes are determined. Through numerical results, the performance of the optimal power control policies is evaluated for different signal constellations and is also compared with that of constant power transmission. The impact of QoS constraints, source characteristics, input distributions on the maximum achievable EE and the throughput is analyzed.

In this paper, energy-efficient power adaptation policies in fading channels are analyzed when data arrivals are modeled as Markovian processes (namely, discrete Markov, Markov fluid, and discrete and fluid Markov modulated Poisson processes) and statistical quality of service (QoS) constraints are imposed on buffer overflow probabilities. In the analysis, both transmission and circuit power consumptions are considered. After formulating energy efficiency (EE) as maximum throughput normalized by the total power consumption, optimal power control policies that maximize EE are obtained for different source models. The impact of source randomness on EE is determined. Optimal power control schemes maximizing the throughput under EE or average power constraints are also investigated. With this, tradeoff between throughput and EE is studied. Finally, the analysis is extended to multichannel scenarios. Overall, the influence of source statistics, QoS constraints, and number of subchannels on the optimal power control policies, throughput, and EE performance is identified.

Throughput and energy efficiency in fading channels are studied in the presence of randomly arriving data and statistical queuing constraints. In particular, Markovian arrival models, including discrete-time Markov, Markov fluid, and Markov-modulated Poisson sources, are considered. Employing the effective bandwidth of time-varying sources and the effective capacity of time-varying wireless transmissions, maximum average arrival rates in the presence of statistical queuing constraints are characterized. For the two-state (ON/OFF) source models, throughput is determined in a closed form as a function of the source statistics, channel characteristics, and quality of service (QoS) constraints. Throughput is further studied in certain asymptotic regimes. Furthermore, energy efficiency is analyzed by determining the minimum energy per bit and a wideband slope in the low signal-to-noise ratio regime. Overall, the impact of source characteristics, QoS requirements, and channel fading correlations on the throughput and energy efficiency of wireless systems is identified.

Energy efficiency in multiple-antenna fading channels is analyzed in the presence of Markov sources and queueing constraints, which are imposed as limitations on buffer overflow probabilities. Two random arrival models, namely discrete Markov and Markov fluid processes, are considered. Employing the notions effective capacity of time-varying channels and effective bandwidth of time-varying sources, maximum average arrival rates of these sources that can be supported by multiple-antenna wireless systems under statistical queueing constraints are determined and the throughput levels are identified. In the low signal-to-noise ratio (SNR) regime, minimum energy per bit and wideband slope expressions are obtained. Performance with both uniform power allocation and low-SNR optimal power allocation across transmit antennas is investigated. It is shown that the minimum energy per bit does not depend on the queueing constraints and source burstiness. On the other hand, wideband slope is shown to decrease as queueing constraints get stricter and/or sources become more bursty, thus resulting in degraded energy efficiency.

Throughput regions of fading broadcast channels with random data arrivals in the presence of quality-of-service (QoS) requirements is studied when power control is employed at the transmitter. Two source models with random arrivals, namely discrete Markov source and Markov fluid source, are considered. It is assumed that superposition coding with power control is performed at the transmitter with interference cancellation at the receivers. By utilizing the effective capacity of time-varying wireless transmission channels and effective bandwidth of random arrivals, the maximum average arrival rates that can be supported in the fading broadcast channel with QoS guarantees are identified and the throughput is characterized. Optimal power control policies that maximize the weighted combination of the average arrival rates are investigated in the two-user case. In particular, optimality conditions are determined and an algorithm for optimal power control is proposed for different source arrival models. Impact of source burstiness, power adaptation, the use of different transmission strategies (e.g., superposition coding and time-division multiplexing) on the throughput regions and sum-rates are investigated.

Transmission over a half-duplex relay channel with secrecy and quality-of-service (QoS) constraints is studied. It is assumed that data is stored in buffers prior to transmission and transmitters operate with a constraint on the buffer overflow probability. Using the effective capacity formulation, secrecy throughput is derived for the half duplex two-hop fading relay system operating in the presence of an eavesdropper. The scenario without security considerations is also addressed. For both scenarios, minimum energy per bit is obtained. The impact of QoS exponents and channel correlation on the throughput is investigated via numerical analysis. Taking into account the path loss effect, the effect of the relay and eavesdropper locations on the throughput and energy efficiency is studied in a simple linear network.

Energy efficiency in wireless fading channels is studied in the presence of statistical quality of service (QoS) constraints. Energy per bit is employed as the performance metric. Minimum energy per bit and wideband slope expressions are determined to quantify the energy efficiency in the low signal-to-noise ratio (SNR) regime. In particular, the impact of channel and source variations is investigated. A block-fading model in which fading coefficients are arbitrarily correlated in one block before assuming independent realizations in the next one, is considered. Initially, the effect of fading correlation on energy efficiency is analyzed. It is shown that while minimum energy per bit does not depend on the fading correlation, wideband slope decreases as positive correlation increases, resulting in increased energy requirements at low but nonzero SNR levels. Subsequently, an ON-OFF source arrival model is considered. It is shown that while the minimum energy per bit does not get affected by source variations, wideband slope diminishes with increasing source burstiness. (”THIS PAPER IS ELIGIBLE FOR THE STUDENT PAPER AWARD”).