Inter-link Interference Research Articles

HITLinQ: Improving path capacity through hybrid information-theoretic link scheduling in multi-hop wireless networks

By taking advantage of full-duplex radios, a one-sided interference channel model in the case of co-directional transmission on two links having a common node is introduced. Analysis of this model shows that asymmetric increase of transmitter power or decrease of distance will change the path capacity. When the signal noise ratio is high in this channel, using full-duplex radios for simultaneous co-directional transmission will worsen the path capacity, while direct transmission is better. On this basis, a scheduling strategy, called the hybrid information-theoretic link scheduling (HITLinQ) algorithm, which combines self-interference and inter-link interference management with link reconstruction, is proposed. The simulation results show that HITLinQ can provide capacity of not less than several baseline algorithms on a long multi-hop path under given setting.

Evolutionary generative adversarial network based end-to-end learning for MIMO molecular communication with drift system

Molecular communication (MC) is a novel paradigm for nano-communication networks. Compared with diffusion-based single-input single-out (SISO) systems, multiple-input multiple-output (MIMO) MC with drift systems can effectively mitigate the negative effects of inter symbol interference (ISI), inter link interference (ILI) and noise, further improving transmission efficiency. The modeling complexity of MIMO MC systems inspires the application of deep learning (DL) techniques to establish end-to-end architectures for signal recovery. However, training of the entire end-to-end system is limited by the unknown channel and small training sample size. In this paper, aiming at signal recovery of the newly developed mathematical MIMO MC with drift system model, a Kullback–Leibler divergence (KLD) evolutionary generative adversarial network (EGAN)-based end-to-end learning method is proposed. The end-to-end architecture can be trained offline with both the sampled and fake signals generated by KLD EGAN, even with a small training sample size, and then used to recover online transmitted signals directly. Besides, two traditional detection algorithms denoted as the maximum a posterior (MAP) detector and fixed threshold (FT) detector, are proposed as well for theoretical comparison. Experiments of the effect of different model parameters on the system performance have been carried out. Results validate the effectiveness and robustness of our proposed method compared to other DL-based methods, including the deep neural networks (DNN)-based, the original GAN-based, and the original EGAN-based, in terms of transmission accuracy.

A generalized space shift keying modulation for molecular MIMO systems

AbstractIndex modulation utilizes spatial dimensions for transmission of information in multiple‐input multiple‐output (MIMO) molecular communication systems. Molecular space shift keying (MSSK) is an IM‐based technique that modulates information in the antenna index and efficiently combats both intersymbol interference and interlink interference in molecular MIMO systems. In this paper, generalized form of the MSSK scheme, that is, generalized MSSK (GMSSK) is proposed which activates a fixed number of antennas for information transmission. The antenna constellation is selected judiciously to minimize the chances of errors in the proposed GMSSK strategy. Design guidelines are provided for the GMSSK antenna constellation for the case of two activated antennas at the transmitter side. Exploiting an additional degree of freedom, the presented GMSSK scheme is shown to achieve reasonably close or better error performance with a smaller antenna array size as compared to the traditional MSSK scheme.

Molecular index modulation using convolutional neural networks

As the potential of molecular communication via diffusion (MCvD) systems at nano-scale communication increases, designing molecular schemes robust to the inevitable effects of molecular interference has become of vital importance. There are numerous molecular approaches in literature aiming to mitigate the effects of interference, namely inter-symbol interference. Moreover, for molecular multiple-input–multiple-output systems, interference among antennas, namely inter-link interference, becomes of significance. Inspired by the state-of-the-art performances of machine learning algorithms on making decisions, we propose a novel approach of a convolutional neural network (CNN)-based architecture. The proposed approach is for a uniquely-designed molecular multiple-input–single-output topology in order to alleviate the damaging effects of molecular interference. In this study, we compare the performance of the proposed network with that of an index modulation approach and a symbol-by-symbol maximum likelihood estimation and show that the proposed method yields better performance.

A Pulse Position-Based Spatio-Temporal Coded Modulation for Molecular MIMO Systems

Multiple-input multiple-output (MIMO) technology is helpful with improving the communication throughput and performance of molecular communication (MC) systems. Though index modulation (IM) approaches aid to alleviate intersymbol interference (ISI) and interlink interference (ILI) issues in molecular MIMO systems by encoding the information in the antenna index, ISI and ILI problems still exist in such environments. Coded modulation strategies show promising results in terms of system error performance due to their better ISI and ILI combating capability. In this letter, a novel coded modulation scheme is proposed where the pulse position constellation is incorporated with the coded antenna indices. The proposed scheme is shown to yield an improved error performance owing to its better ILI mitigating strength.

Performance Analysis and Receiver Design of Spatio-Temporal Coded Modulation Scheme for Diffusion-Based Molecular MIMO Systems

Diffusion-based molecular communication (DBMC) systems allow messenger molecules to reach the intended receiver using laws of diffusion. The Brownian motion of messenger molecules introduces delay in the system causing the problem of inter-symbol interference (ISI). Along with ISI, the problem of inter-link interference (ILI) comes into picture in the diffusion-based molecular multiple-input multiple-output (DB-MoMIMO) systems. To combat against ISI and ILI issues, index modulation (IM) approaches are recently proposed in the literature for improving the performance of DB-MoMIMO systems. Despite the existence of IM approaches, problems of ISI and ILI still persist due to the slow random motion of molecules in DB-MoMIMO channels. Motivated by this, a novel coded modulation approach called molecular spatio-temporal coded modulation (MSTCM) is proposed in this paper which shows promising improvement in the performance of DB-MoMIMO systems by encoding the information both in space and time axes. Further, if system has access to two types of molecules, the dual-type modulation schemes are discussed for the same. Moreover, the encoder and decoder designs for the proposed mapping strategy are provided. In addition, a theoretical bit error rate expression for the MSTCM scheme is derived and simulation results are shown to corroborate the theoretical ones.

Modeling and Design of IRS-Assisted Multilink FSO Systems

In this paper, we investigate the modeling and design of intelligent reflecting surface (IRS)-assisted optical communication systems, which can circumvent the line-of-sight (LOS) requirement in multi-link free space optical (FSO) systems. The FSO laser beams incident on the optical IRSs have a Gaussian power intensity profile and a nonlinear phase profile, whereas the plane waves in radio frequency (RF) systems have a uniform power intensity profile and a linear phase profile. Given these substantial differences, the results available for IRS-assisted RF systems are not applicable to IRS-assisted FSO systems. Therefore, we develop a new analytical channel model for point-to-point IRS-assisted FSO systems based on the Huygens-Fresnel principle. Our analytical model captures the impact of the size, position, and orientation of the IRS as well as its phase shift profile on the end-to-end channel. To allow the sharing of the optical IRS by multiple FSO links, we propose three different protocols, namely the time division (TD), IRS-division (IRSD), and IRS homogenization (IRSH) protocols. The proposed protocols address the specific characteristics of FSO systems including the non-uniformity and possible misalignment of the laser beams. Furthermore, to compare the proposed IRS sharing protocols, we analyze the bit error rate (BER) and the outage probability of IRS-assisted multi-link FSO systems in the presence of inter-link interference. Our simulation results validate the accuracy of the proposed analytical channel model for IRS-assisted FSO systems and confirm that this model is applicable for both large and intermediate IRS-receiver lens distances. Furthermore, we show that for the proposed IRSD and IRSH protocols, inter-link interference becomes negligible if the laser beams are properly centered on the IRS and the transceivers are carefully positioned, respectively. Moreover, in the absence of misalignment errors, the IRSD protocol outperforms the other protocols, whereas in the presence of misalignment errors, the IRSH protocol performs significantly better than the IRSD protocol.

Distributed and Scalable Radio Resource Management for mmWave V2V Relays towards Safe Automated Driving.

The millimeter-wave (mmWave) Vehicle-to-Vehicle (V2V) communication system has drawn attention as a critical technology to extend the restricted perception of onboard sensors and upgrade the level of vehicular safety that requires a high data rate. However, co-channel inter-link interference presents significant challenges for scalable V2V communications. To overcome such limitations, this paper firstly analyzes the required data rate ensuring maneuver safety via mmWave V2V relays in an overtaking traffic scenario. Based on these preparations, we propose a distributed radio resource management scheme that integrates spatial, frequency, and power domains for two transmission ranges (short/long). In the spatial domain, ZigZag antenna configuration is utilized to mitigate the interference, which plays a decisive role in the short inter-vehicle distance. In frequency and power domains, two resource blocks are allocated alternately, and transmit power is controlled to suppress the interference, which has a decisive impact on interference mitigation in the long inter-vehicle distance. Simulation results reveal that the achievable End-to-End (E2E) throughput maintains consistently higher than the required data rate for all vehicles. Most importantly, it works effectively in scalable mmWave V2V topology.

Semi-Blind Channel Estimation for MIMO Diffusive Molecular Communication

Multiple-input multiple-output (MIMO) molecular communication (MC) systems can provide significantly better data rates than single-input single-output (SISO) systems. A major challenge in MIMO MC systems is the presence of inter-link interference, in addition to inter-symbol interference. Accurate estimation of all the channel information is thus essential for interference mitigation in MIMO MC systems. The pilot-based estimators proposed in existing works impose a heavy training overhead. In contrast, we address this problem using semi-blind estimation strategies. In particular, we propose one semi-blind estimator based on the expectation-maximization (EM) criterion. Moreover, as alternatives to the iterative EM estimator, we develop two other estimators that are based on the decision-directed criterion. As a benchmark on estimation accuracy, we derive the semi-blind Cramer-Rao bound. Through simulation studies, we demonstrate that our proposed estimators outperform the previously proposed pilot-based estimators. Moreover, they can be used to considerably reduce the number of transmitted pilot symbols, while maintaining high estimation accuracy.

Performance Analysis of Simultaneous Collision-Free Duplexing Method in Point-to-Multipoint Environment

In this letter, we have studied how to use simultaneous collision-free duplexing (SCD) in point-to-multipoint environment. SCD is a method exchanging uplink and downlink signals simultaneously using the same resource for each link and has the advantages in that it does not need complicated self-interference cancellation unlike full duplexing. In addition, SCD is different from dynamic time division duplexing (D-TDD) in which interlink interference can be completely avoided. Therefore, to analyze the effect of interlink interference on SCD, we have derived the upper bound of link capacity and the required value of interlink isolation level for better SCD performance than D-TDD. We have verified the analyzed isolation level and confirmed that SCD has good performance even in practical point-to-multipoint environment through simulation.

Modeling and Dual Threshold Algorithm for Diffusion-Based Molecular MIMO Communications.

Molecular communication, as an emerging research direction, has emerged in the field of communication, which usually combined with nanotechnology and bio-related knowledge. In the direction of communication channel research, the most widespread model for a molecular communication channel is the diffusion-based channel, where the information-carrying molecules propagate randomly in the medium based on Brownian motion. Multi-input multi-output (MIMO) technology is often used to improve communication quality in the traditional communication field. Compared with the SISO model, which only has inter-symbol interference (ISI) as the interference source, the interference in MIMO communication model includes ISI as well as inter-link interference (ILI), which emerges when receiver receive other transmitters' molecules. In this paper, MIMO communication models are built, based on diffusion channel, CSK, probabilistic theory, considered with ISI and ILI, to establish the calculation formula of related bit error rate, And the influence of relevant parameters in the model on bit error rate is studied. Then, SISO and SIMO models will be built to compare with MIMO models. Last, self-adaptive dual threshold algorithm is proposed to reduce BER of the 2×2 MIMO system. Simulation results show that the proposed algorithm has better performance on reducing BER than other approaches.

Molecular-Type Permutation Shift Keying in Molecular MIMO Communications for IoBNT

Molecular communication (MC) is a bio-inspired communication paradigm, which lays the foundation for the Internet of Bio-NanoThings (IoBNT) in the medical field. As a high energy-efficient information transfer method, MC via diffusion (MCvD) is envisioned as a promising candidate for IoBNT but suffers from low date rates due to the long tail of the channel impulse response (CIR). To this end, the multiple-input–multiple-output (MIMO) technique has been introduced to MCvD. However, the intersymbol interference (ISI) and interlink interference (ILI) deteriorate the bit error rate (BER) performance of MIMO MCvD systems. In this article, molecular type permutation shift keying in the space domain (MTPSK-SD) and time-interleaved MTPSK-SD are proposed for MIMO MCvD systems to improve the BER performance by reducing ILI. The principle of MTPSK-SD is further generalized to the spatiotemporal domain, yielding three spatiotemporal modulation schemes, which can provide desirable BER performance without requiring any CIR information in the communication scenarios affected by different levels of ISI and ILI. Two low-complexity detectors are proposed to obtain different tradeoffs between anti-ILI and anti-ISI performance. Furthermore, a complementary coding scheme, which can effectively reduce the ILI under the considered symmetrical system topology, is designed and applied to all the proposed modulation schemes. Additionally, the BER upper bound is analyzed. Numerical simulations on BER corroborate the analysis and show that the proposed schemes are promising multimolecule modulation alternatives, which outperform the existing MIMO MCvD modulation schemes.

A Novel Spread Spectrum and Clustering Mixed Approach with Network Coding for Enhanced Narrowband IoT (NB-IoT) Scalability

The Narrowband Internet of Things (NB-IoT) is a very promising licensed Internet of things (IoT) technology for accommodating massive device connections in 5G and beyond. To enable network scalability, this study proposes a two-layers novel mixed approach that aims not only to create an efficient spectrum sharing among the many NB-IoT devices but also provides an energy-efficient network. On one layer, the approach uses an Adaptive Frequency Hopping Spread Spectrum (AFHSS) technique that uses a lightweight and secure pseudo-random sequence to exploit the channel diversity, to mitigate inter-link and cross-technology interference. On the second layer, the approach consists of a clustering and network coding (data aggregation) approach based on an energy-signal strength mixed gradient. The second layer contributes to offload the BS, allows for energy-efficient network scalability, helps balance the energy consumption of the network, and enhances the overall network lifetime. The proposed mixed strategy algorithm is modelled and simulated using the Matrix Laboratory (MATLAB) Long Term Evolution (LTE) toolbox. The obtained results reveal that the proposed mixed approach enhances network scalability while improving energy efficiency, transmission reliability, and network lifetime when compared to the existing spread spectrum only, nodes clustering only, and mixed approach with no network coding approaches.

Optimization for Signal Transmission and Reception in a Macrocell of Heterogeneous Uplinks and Downlinks

Internet-of-things (IoT) applications continue to drive advancements in serving as many heterogeneous low-latency downlinks and uplinks as possible within a constrained communication bandwidth. Full-duplexing (FD) transceivers have been introduced to implement simultaneous signal transmission and reception (STR) over the entire available frequency band. However, both inter-link interference and FD loop-interference are hardly suppressed to a necessary level for the effectiveness of FD-based STR even for microcells. This paper proposes an alternative STR technique per one time-slot for macrocells, where a fraction of a time-slot is used for downlinks and the remaining complementary fraction of the time-slot is used for uplinks. Thus, STR over the entire available bandwidth can be implemented in a way with no loop interference. Furthermore, another approach of using a fraction of the available bandwidth for downlinks and the remaining complementary fraction of the bandwidth for uplinks over the whole time-slot is also proposed. The problem of both downlink and uplink beamforming to maximize the energy efficiency of such heterogeneous networks subject to the quality-of-service in terms of downlink and uplink throughput is examined for all three possible STRs. Numerical results demonstrate the advantages of the time-fraction-wise STR and bandwidth-fraction-wise STR over the FD-based STR, where the time-fraction-wise STR is not only the best in serving the same numbers of downlinks and uplinks but also is capable of serving many more downlinks and uplinks with a higher energy efficiency.

Signal Detection for Molecular MIMO Communications With Asymmetrical Topology

Molecular communication (MC) has attracted people's attention due to its potential applications at the micro- to nano-scale. In MC, the transmission rate is usually very low due to the slow diffusion of information molecules and therefore multiple-input multiple-output (MIMO) system is introduced. However, severe interference occurs when the same types of information molecules are used at different transmission antennas. Up to now, most literature focuses on MIMO systems with symmetrical topology. In this paper, a molecular MIMO communication system with asymmetrical topology, where the number of transmission antennas is not equal to that of the reception antennas, is investigated. The zero-forcing (ZF) detection approach is proposed and discussed for three cases, i.e., the number of transmission antennas is smaller than, equal to and larger than the number of the reception antennas. Considering the inter-link interference (ILI) and the inter-symbol interference (ISI), the error probability of ZF detection is derived and comparisons are made with existing molecular MIMO detection method. Besides, the adaptive observation time for each reception antenna is derived for better performance. Numerical results show that ZF detection performs better than the existing molecular MIMO detection method when the ILI is large.

Molecular Index Modulation With Space-Time Equalization

Molecular multiple-input-multiple-output (MIMO) techniques are proposed in the literature to improve the overall throughput of molecular communication via diffusion (MCvD) systems. Among these methods, molecular index modulation (molecular-IM) schemes are recently introduced as novel molecular MIMO approaches to provide significant improvements in terms of communication efficiency. However, despite molecular-IM’s strong combating capability against inter-symbol interference (ISI) and inter-link interference (ILI), they are still prone to them due to the characteristics of a molecular MIMO MCvD channel. With the goal of further mitigating ISI and ILI, this letter introduces memory-assisted, linear time and space-time equalization methods for molecular-IM schemes. It is shown that the proposed equalization methods yield significant improvements in error performance while retaining low decoding complexity due to the linear combining.

Spatial Receptor Allocation for a Multiple Access Hub in Nanonetworks

Following the same trends in other communication schemes, design of star network topologies will gain importance in order to communicate with a centralized hub in molecular communications as well. For a molecular communication multiple access network system, interlink interference (ILI) becomes a crucial issue in addition to intersymbol interference (ISI). This letter focuses on spatial allocation of the receptors of a centralized receiver among transmitters by proposing efficient solutions to reduce both ISI and ILI. The spatial allocation scheme has been designed using an optimization problem and verified with Monte Carlo simulations.

Diffusive MIMO Molecular Communications: Channel Estimation, Equalization, and Detection

In diffusion-based communication, for molecular systems, the achievable data rate depends on the stochastic nature of diffusion, which exhibits a severe inter-symbol-interference (ISI). Multiple-input multiple-output (MIMO) multiplexing improves the data rate at the expense of an inter-link interference (ILI). This paper investigates training-based channel estimation schemes for diffusive MIMO (D-MIMO) systems and corresponding equalization methods. Maximum likelihood and least-squares estimators of mean channel are derived, and the training sequence is designed to minimize the mean square error (MSE). The numerical validations in terms of MSE are compared with Cramer–Rao bound derived herein. Equalization is based on decision feedback equalizer (DFE) structure as this is effective in mitigating diffusive ISI/ILI. Zero-forcing, minimum MSE, and least-squares criteria have been paired to DFE, and their performances are evaluated in terms of bit error probability. D-MIMO time interleaving is exploited as an additional countermeasure to mitigate the ILI with remarkable performance improvements. The configuration of nano-transceivers is not static but affected by a Brownian motion. A block-type communication is proposed for D-MIMO channel estimation and equalization, and the corresponding time-varying D-MIMO MC system is numerically evaluated.

Index Modulation for Molecular Communication via Diffusion Systems

Molecular communication via diffusion (MCvD) is a molecular communication method that utilizes the free diffusion of carrier molecules to transfer information at the nano-scale. Due to the random propagation of carrier molecules, inter-symbol interference (ISI) is a major issue in an MCvD system. Alongside ISI, inter-link interference (ILI) is also an issue that increases the total interference for MCvD-based multiple-input-multiple-output (MIMO) approaches. Inspired by the antenna index modulation (IM) concept in traditional communication systems, this paper introduces novel IM-based transmission schemes for MCvD systems. In the paper, molecular space shift keying (MSSK) is proposed as a novel modulation for molecular MIMO systems, and it is found that this method combats ISI and ILI considerably better than existing MIMO approaches. For nano-machines that have access to two different molecules, the direct extension of MSSK, quadrature molecular space shift keying (QMSSK) is also proposed. QMSSK is found to combat ISI considerably well whilst not performing well against ILI-caused errors. In order to combat ILI more effectively, another dual-molecule-based novel modulation scheme called the molecular spatial modulation (MSM) is proposed. Combined with the Gray mapping imposed on the antenna indices, MSM is observed to yield reliable error rates for molecular MIMO systems.

Pulse Position-Based Spatial Modulation for Molecular Communications

Multiple-input-multiple-output (MIMO) approaches have been recently introduced to molecular communications (MC) in order to increase the communication throughput. For MIMO systems, index modulation (IM) suggests encoding information bits using the indices of the available antennas, rather than employing spatial multiplexing or performing other space-time coding schemes. Recent works have shown that utilizing the available MIMO antennas with the IM-based approaches improve the error performance of a molecular MIMO system, courtesy of molecular-IM’s robustness against inter-symbol interference and inter-link interference (ILI). Inspired by IM’s prospects on the MC, this letter proposes a novel family of the IM-based schemes to the MC realm. The proposed schemes combine position-based constellations with antenna indices to encode bits in and yield reliable error performances due to their robustness against the ILI.