Hidden Terminal Problem Research Articles

Learning-Based Autonomous Channel Access in the Presence of Hidden Terminals

We consider the problem of autonomous channel access (AutoCA), where a group of terminals tries to discover a communication strategy with an access point (AP) via a common wireless channel in a distributed fashion. Due to the irregular topology and the limited communication range of terminals, a practical challenge for AutoCA is the hidden terminal problem, which is notorious in wireless networks for deteriorating throughput and delay performances. To meet the challenge, this paper presents a new multi-agent deep reinforcement learning paradigm, dubbed MADRL-HT, tailored for AutoCA in the presence of hidden terminals. MADRL-HT exploits topological insights and transforms the observation space of each terminal into a scalable form independent of the number of terminals. To compensate for the partial observability, we put forth a look-back mechanism such that the terminals can infer behaviors of their hidden terminals from the carrier-sensed channel states as well as feedback from the AP. A window-based global reward function is proposed, whereby the terminals are instructed to maximize the system throughput while balancing the terminals' transmission opportunities over the course of learning. Considering short-packet machine-type communications, extensive numerical experiments verified the superior performance of our solution benchmarked against the legacy carrier-sense multiple access with collision avoidance (CSMA/CA) protocol.

MVR Delay: A Queueing Based Routing Model for C-V2X Mode 4 in VANET’s

During the last few years, the demand for vehicular ad-hoc networks (VANET) has gained great attraction in the intelligent transport system. The VANET architecture includes several critical features, such as distributed networking and the rapidly changing network topology. Due to the significant characteristics of road safety, it has gained a great deal of interest in industry and academia to enhance the safety of the road transport system. Efficient message exchange between vehicles and roadside units is a tedious task in VANET. Several techniques have been introduced to improve communication, but efficient packet delivery and delay reduction are challenging issues. Currently, the VANET technique has evolved as a “vehicle-to-everything (V2X)” communication standard. In addition, the 3GPP standards have introduced a new communication standard as an alternative to the IEEE 802.11p system. In this new release of 3GPP, two new communication modes are introduced, mode 3 and mode 4. Mode 3 requires a cellular infrastructure, whereas mode 4 can operate without cellular coverage. In this work, we focus on C-V2X mode 4 communications and present a novel routing scheme to deal with hidden terminal problems. The proposed approach generates a virtual queueing model in which efficient channel selection is performed so that packet collision and interference can be reduced by maximizing the distance in the virtual queue model. The experimental results demonstrate that the average performance of the proposed approach is obtained as 0.9383, 0.09 s, and 0.0617 in terms of packet delivery, end-to-end delay, and packet drop rate, respectively.

Adaptive Channel Detection for Full-Duplex IAB Systems on Unlicensed Bands

The integration of integrated access and backhaul (IAB) and full-duplex communications on unlicensed bands can improve the spectrum efficiency and mitigate the spectrum resource shortage. To guarantee fair coexistence on unlicensed spectrum, the listen-before-talk mechanism needs to be executed at the IAB nodes, where the clear channel assessment (CCA) is applied before transmission. However, the residual self-interference (RSI) brought by the full-duplex communication may degrade the CCA detection performance tremendously. Therefore, in this paper we propose an adaptive channel detection scheme for the full-duplex IAB network to minimize the impact of RSI on the CCA detection, which can enhance the spectrum efficiency. In particular, the closed-form expressions of false alarm probability and detection probability are derived. Accordingly, the energy detection (ED) threshold applied in CCA is adjusted adaptively to improve the system throughput. Then, a novel timing sequence with respect to the self-interference cancellation and CCA detection is proposed. The corresponding optimal initial threshold is also derived to realize the adaptive ED threshold. Furthermore, an enhanced request to send/clear to send mechanism is proposed to solve the hidden terminal problem. Simulation results demonstrate that the proposed schemes can effectively reduce the impact of RSI on the CCA detection accuracy and significantly improve the system throughput.

Cooperative Time-Frequency Localization for Wideband Spectrum Sensing With A Lightweight Detector

With the ability to solve the hidden terminal problem, cooperative spectrum sensing (CSS) in cognitive radio networks has attracted much attention. However, existing CSS mainly focuses on detecting the spectrum usage status of primary users (PUs) in time dimension under the premise of known center frequency and bandwidth of PU, which is limited in practical scenarios. For the emerging time-frequency localization based two-dimensional wideband spectrum sensing (SS), how to incorporate cooperation into secondary users (SUs) to enhance sensing performance is still a challenging problem. In this letter, considering the limited storage and computation capacity of SUs, we first propose a lightweight detector for time-frequency localization. Then, through analyzing the characteristics of the sensed spectrogram, we propose a non-maximum suppression based fusion algorithm. Finally, simulation results validate the advantages of the proposed lightweight detector compared with existing detectors, and show the recognition performance of CSS is superior to that of the individual SUs.

Cooperative Multiband Spectrum Sensing Using Radio Environment Maps and Neural Networks.

Cogitive radio networks (CRNs) require high capacity and accuracy to detect the presence of licensed or primary users (PUs) in the sensed spectrum. In addition, they must correctly locate the spectral opportunities (holes) in order to be available to nonlicensed or secondary users (SUs). In this research, a centralized network of cognitive radios for monitoring a multiband spectrum in real time is proposed and implemented in a real wireless communication environment through generic communication devices such as software-defined radios (SDRs). Locally, each SU uses a monitoring technique based on sample entropy to determine spectrum occupancy. The determined features (power, bandwidth, and central frequency) of detected PUs are uploaded to a database. The uploaded data are then processed by a central entity. The objective of this work was to determine the number of PUs, their carrier frequency, bandwidth, and the spectral gaps in the sensed spectrum in a specific area through the construction of radioelectric environment maps (REMs). To this end, we compared the results of classical digital signal processing methods and neural networks performed by the central entity. Results show that both proposed cognitive networks (one working with a central entity using typical signal processing and one performing with neural networks) accurately locate PUs and give information to SUs to transmit, avoiding the hidden terminal problem. However, the best-performing cognitive radio network was the one working with neural networks to accurately detect PUs on both carrier frequency and bandwidth.

Design of NULLMAC Protocol for Mobile Ad Hoc Network Using Adaptive Antenna Array

Usually, omnidirectional radiation pattern antenna is used in the mobile ad hoc network (MANET) which causes neighbor node interference, consumes more power, and supports only limited range of transmission. To overcome these problems, smart antennas are used. A lot of medium access control (MAC) protocols are proposed using smart antennas. Existing works addressed various problems such as hidden terminal problem, hidden beam problem, deafness of nodes, and head of line blocking problem. However, certain factors including determination of weight vector and conveying it to the neighbor nodes for distortion-free transmission are not considered. In this study, nullifying MAC (NULLMAC) framework is proposed using an adaptive antenna array (AAA) for improving network performance in MANET. NULLMAC framework uses channel information for achieving high throughput and spatial reuse through integrated physical and MAC layer. Before the transfer of data packets, the receiver initially determines its weight vector and conveys it to the transmitter through control packets. Then, the transmitter computes its weight to nullify the dynamic receivers present in the neighborhood region to find the desired receiver. Beamformer weights are determined through channel coefficients between a transmitter-receiver pair to establish distortion-free transmission. Extensive simulations are performed using OPNET integrated with MATLAB. NULLMAC framework achieves 27.22% more throughput and 40.46% increase in signal-to-noise ratio.

Robust spectrum sensing against malicious users using particle swarm optimization

The different issues in the wireless channel, such as multipath fading, shadowing, and hidden terminal problems, limit the sensing abilities of the single user in a cognitive radio network (CRN). In this connection, it is more suitable to follow cooperative spectrum sensing (CSS). However, the various categories of malicious users (MUs) pose threats to the performance of CSS. These MUs are eager to report false sensing data to the fusion center (FC) to deceive its decision. This work considered the CSS performance in the presence of always yes MU (AYMU), opposite MU (OMU), and always no MU (ANMU). Moreover, the considered particle swarm optimization (PSO) algorithm takes out reports of the MUs using one to many sensing distances (OTMSD) and z-score outlier detection techniques before the final decision. Simulation results validate the effectiveness of the proposed scheme in the presence of MUs.

CSMA/PJ: A Protective Jamming Based MAC Protocol to Harmonize the Long and Short Links

WiFi-based Long Distance (WiLD) networks are promising to cover the rural and remote regions. But the explosive short-range WiFi deployments result in the long-short coexistence. Due to CSMA is ignorance of propagation delay, its carrier sensing is too short to detect long links, leading to the temporal hidden terminal problem that causes serious performance degradation and even starvation of long links. Existing methods for traditional hidden terminal problem are inefficient to cope with this problem because of the different causes. In this paper, we propose CSMA with Protective Jamming (CSMA/PJ), a new WiLD MAC protocol that solves the temporal hidden terminal problem with the minimized influence on uncontrollable short links. The key is generating protective jamming at the WiLD receiver that is sensible to the short links. By leveraging the asymmetric propagation delay of the WiLD transmitter and receiver, we make the jamming protective rather than destructive. We precisely control the jamming right before the arrivals of WiLD packets to set aside channel time for short links. We implement and evaluate CSMA/PJ on commercial devices. The experimental results show that CSMA/PJ can improve the throughput of the WiLD link by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6\times $ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5 \times $ </tex-math></inline-formula> compared with the CSMA/CA and RTS/CTS methods.

Graph coloring-based multichannel MAC protocol in distributed underwater acoustic sensor networks

In this paper, the multichannel medium access control (MAC) problem in distributed underwater acoustic sensor networks (UASNs) were investigated. Compared with single-channel MAC protocols in terrestrial radio networks, there exist multichannel hidden terminal problem and long-delay hidden terminal problem in multichannel MAC protocol due to long propagation delay in UASNs. In addition, energy constraint makes channel allocation a challenging problem in distributed UASNs. To solve these aforementioned problems, a new multichannel MAC protocol, called graph coloring-based multichannel MAC protocol (GCMAC) is present. The protocol GCMAC is a synchronized MAC protocol which splits the time into three phases, namely, channel negotiation phase, channel selecting phase and data transmission phase. Specially, the rule for selecting channel is carefully designed based on graph coloring theory to avoid collision and maximize the utilization rate of channels in channel selecting phase. Simulation results show that GCMAC can greatly improve the system throughput and energy efficiency by effectively solving the hidden terminal problems and channel allocation problem.

A Reliable Merging Link Scheme Using Weighted Markov Chain Model in Vehicular Ad Hoc Networks.

The vehicular ad hoc network (VANET) is a potential technology for intelligent transportation systems (ITS) that aims to improve safety by allowing vehicles to communicate quickly and reliably. The rates of merging collision and hidden terminal problems, as well as the problems of picking the best match cluster head (CH) in a merged cluster, may emerge when two or more clusters are merged in the design of a clustering and cluster management scheme. In this paper, we propose an enhanced cluster-based multi-access channel protocol (ECMA) for high-throughput and effective access channel transmissions while minimizing access delay and preventing collisions during cluster merging. We devised an aperiodic and acceptable merge cluster head selection (MCHS) algorithm for selecting the optimal merge cluster head (MCH) in centralized clusters where all nodes are one-hop nodes during the merging window. We also applied a weighted Markov chain mathematical model to improve accuracy while lowering ECMA channel data access transmission delay during the cluster merger window. We presented extensive simulation data to demonstrate the superiority of the suggested approach over existing state-of-the-arts. The implementation of a MCHS algorithm and a weight chain Markov model reveal that ECMA is distinct and more efficient by 64.20–69.49% in terms of average network throughput, end-to-end delay, and access transmission probability.

Countermeasure to hidden terminal problem considering data rate shift algorithm in wireless LAN

Countermeasure to hidden terminal problem considering data rate shift algorithm in wireless LAN

Hidden terminal aware grouping scheme for IEEE 802.11ah based dense IoT networks

IEEE 802.11ah, a prevalent standard for the Internet of Things, introduces major enhancements to PHY and MAC layer of the legacy standard. One of the significant improvements in IEEE 802.11ah is the restricted access window (RAW) mechanism. The RAW mechanism is a group-based contention technique that limits the contention among the devices by partitioning them into several groups, dividing the channel time into various time slots and assigning each group with a RAW slot. Although the grouping schemes reduce contention among the devices, it eventually leads to hidden terminals in the dense networks. In this article, we propose a hidden terminal aware grouping (HTAG) mechanism to alleviate the hidden terminal problem. The proposed scheme groups the devices based on the SINR and implements a hidden terminal avoidance algorithm to ensure each group with a minimum number of hidden terminals. We present a simple yet accurate analytical model to evaluate the performance of the RAW mechanism with the proposed HTAG scheme in terms of throughput, delay and energy consumption. Results show significant improvement in the performance of the RAW mechanism using the HTAG scheme compared to the state-of-the-art schemes. Finally, all the analytical findings are validated using extensive simulations in ns-3.

Colored scheduling scheme for fast and reliable beacon safety messages broadcast in vehicular ad‐hoc networks

SummaryThe beacon transmission method in vehicular networks has to consider the mobility feature of vehicles and use the wireless channel more efficiently in order to broadcast safety‐related beacons with high reliability while respecting strict deadlines. The time division multiple access (TDMA) scheme has been proposed to improve the effectiveness of the IEEE 802.11p CSMA MAC protocol, but it is challenged with access and merging collisions caused by inefficient strategies in allocating time slots and mobile hidden terminal problems. In this paper, we propose colored velocity‐based TDMA (CVTDMA), an original colored scheduling scheme for the broadcast of safety beacons on the control channel. Based on vehicles speed and colors that it assigns to time slots according to their occupation statuses, it mitigates the mobility effect and maximizes the reuse of slots while avoiding collisions. The simulation results show that our protocol uses the wireless channel much more effectively than the default one defined in IEEE 802.11p.

Composite Interference Mapping Model to Determine Interference-Fault Free Schedule in WSN

The primary focus of most approaches that model interference in WSN is to understand the conditions under which the signals received by a destination node are interfered by the transmissions of other source nodes. While these models support the basic understanding of interference phenomenon between two nodes; models that attempt to map the nodes whose transmissions can potentially interfere with other nodes is highly desirable. To this end, the Composite Interference Mapping (CIM) model presented in this paper, provides a holistic frame-work for determining a comprehensive map of all potential interferers, for each and every node in the WSN. Based on CIM model, we have developed Interference-Fault Free Transmission (IFFT) scheduling algorithms for (i) topology-free, and (ii) tree-structured WSNs. In addition to determining IFFT schedules, the algorithms also address the Exposed Station (ES) and Hidden Terminal (HT) problems. We present the analytical studies developed to support the models developed in the paper. The results of the simulation experiments have shown that the CIM-based IFFT algorithms perform much better compared to some of the existing algorithms in performance metrics such as: number of time slots, packet drop, number of dead nodes, honouring precedence relations, and addressing ES and HT problems.

Analytical Models of the Performance of IEEE 802.11p Vehicle to Vehicle Communications

The critical nature of vehicular communications requires their extensive testing and evaluation. Analytical models can represent an attractive and cost-effective approach for such evaluation if they can adequately model all underlying effects that impact the performance of vehicular communications. Several analytical models have been proposed to date to model vehicular communications based on the IEEE 802.11p (or DSRC) standard. However, existing models normally model in detail the MAC (Medium Access Control), and generally simplify the propagation and interference effects. This reduces their value as an alternative to evaluate the performance of vehicular communications. This paper addresses this gap, and presents new analytical models that accurately model the performance of vehicle-to-vehicle communications based on the IEEE 802.11p standard. The models jointly account for a detailed modeling of the propagation and interference effects, as well as the impact of the hidden terminal problem. The model quantifies the PDR (Packet Delivery Ratio) as a function of the distance between transmitter and receiver. The paper also presents new analytical models to quantify the probability of the four different types of packet errors in IEEE 802.11p. In addition, the paper presents the first analytical model capable to accurately estimate the Channel Busy Ratio (CBR) metric even under high channel load levels. All the analytical models are validated by means of simulation for a wide range of parameters, including traffic densities, packet transmission frequencies, transmission power levels, data rates and packet sizes. An implementation of the models is provided openly to facilitate their use by the community.

A comparison study of chi-square and uniform distributions of mesh clients for different router replacement methods using WMN-PSODGA hybrid intelligent simulation system

Wireless Mesh Networks (WMNs) are gaining a lot of attention from researchers due to their advantages such as easy maintenance, low upfront cost and high robustness. Connectivity and stability directly affect the performance of WMNs. However, WMNs have some problems such as node placement problem, hidden terminal problem and so on. In our previous work, we implemented a simulation system to solve the node placement problem in WMNs considering Particle Swarm Optimization (PSO) and Distributed Genetic Algorithm (DGA), called WMN-PSODGA. In this paper, we compare chi-square and uniform distributions of mesh clients for different router replacement methods. The router replacement methods considered are Constriction Method (CM), Random Inertia Weight Method (RIWM), Linearly Decreasing Inertia Weight Method (LDIWM), Linearly Decreasing Vmax Method (LDVM) and Rational Decrement of Vmax Method (RDVM). The simulation results show that for chi-square distribution the mesh routers cover all mesh clients for all router replacement methods. In terms of load balancing, the method that achieves the best performance is RDVM. When using the uniform distribution, the mesh routers do not cover all mesh clients, but this distribution shows good load balancing for four router replacement methods, with RIWM showing the best performance. The only method that shows poor performance for this distribution is LDIWM. However, since not all mesh clients are covered when using uniform distribution, the best scenario is chi-square distribution of mesh clients with RDVM as a router replacement method.

FWDP: A fuzzy logic-based vehicle weighting model for data prioritization in vehicular ad hoc networks

In vehicular ad hoc networks (VANETs), data propagation is quite challenging due to the high mobility of vehicles, the instability of communication links, and the inherent topology changes. This paper presents FWDP, a fuzzy logic-based vehicle weighting model (VWM) for scheduling prioritized data in VANETs. FWDP employs roadside units (RSUs) to dominate the frequent topology changes and manage the data propagation. A Fuzzy C-Mean clustering (FCMC) is used for handling clustered vehicles that compete to utilize the shared channel. RSUs receive prioritized data from cluster heads (CHs) in the proposed model wherein CHs allocate scheduled service channels to weighted vehicles during an interval. FWDP is equipped with a fuzzy inference system (FIS) for vehicle weighting according to the velocity and inter-vehicle distance metrics. In addition, RSUs compute the signal-to-noise and the interference ratio (SINR) to solve the hidden terminal problem to prevent radio interference. The OMNET++ simulator is used to show the performance improvement of FWDP in terms of the packet delivery ratio, interference ratio, suspend data ratio, Throughput, end-to-end delay, channel utilization, and packet loss ratio metrics intended for low, intermediate, and high vehicle densities.

Hidden terminal-aware access point selection for IEEE 802.11ah networks

Connectivity provisioning in large-scale Internet-of-Things (IoT) networks raises several challenges, one of which is the high collision rate among the transmission attempts of IoT devices. Transmission collisions result in prolonged data delivery delay and increased energy consumption of IoT devices. Contention-based wireless communication technologies such as WiFi is particularly vulnerable to this issue. As a remedy, a new standard IEEE 802.11ah is designed and such methods as RAW (Restricted Access Window) grouping is incorporated in order to curb the high collision rate. Meanwhile, in IEEE 802.11ah the transmission range and the number of devices that can be accommodated are also drastically increased. As a result, the impact of the hidden terminal problem is significantly amplified, which causes transmission collisions. In this paper, we propose an approach to avoid the high collision rate at the phase of the AP(Access Point) selection for IEEE 802.11ah networks. The proposed scheme considers the traffic load balancing and the hidden terminal issue simultaneously, without incurring any burden to the IoT devices. No modification of the IEEE 802.11ah standard is needed. Via extensive NS-3 simulations, we have verified that the proposed AP selection scheme outperforms the existing schemes in terms of data delivery delay and energy consumption by reducing transmission collisions.

CQI-Based Interference Detection and Resource Allocation With QoS Provision in LTE-U Systems

Long-Term Evolution in unlicensed spectrum (LTE-U) is a promising solution to address the spectrum scarcity in the cellular networks. However, the LTE-U and WiFi systems may interfere with each other and degrade the performance. Thus, many works have focused on coexistence design and proposed various solutions. Nevertheless, the hidden terminal problem has not been well studied in the LTE-U system. In this paper, we investigate joint interference detection and resource allocation in the LTE-U system to maximize the overall system throughput while guaranteeing each user's quality-of-service (QoS) requirements. Firstly, to solve the hidden terminal problem and avoid the co-channel interference between the WiFi and LTE-U users, we adopt a cluster-based algorithm to find the potential WiFi interference for each LTE-U user according to their channel quality indicator (CQI) feedback and location information. Secondly, we formulate a joint subcarrier and power allocation problem over the licensed and unlicensed bands with each user's QoS provision. To make the original problem more tractable, we separate it into licensed and unlicensed subproblems and then derive the optimal solution. Moreover, we propose a low-complexity resource allocation scheme. The simulation results show that the proposed schemes can significantly improve the system performance and outperform the existing schemes.

Energy Optimization in Wireless Sensor Networks Under Dynamic Spectrum Access Using Adaptive Listening

The efficient use of energy consumption in WSNETs is one of the most promising areas for researchers. In such networks, a considerable amount of bandwidth and energy is wasted for sensing the communication over the common channels. To recognise these complications, WSNETs offers dynamic allocation of the spectrum to optimise the bandwidth utilization. The S-MAC protocol which is based upon Time Division Multiple Access technique has already been proven as a better protocol for the efficient use of energy at MAC Layer. We revised all the patents related to the energy issues in Wireless Sensor Networks. The Hidden terminal problem is a well-known issue in wireless networks due to which the performance of the single-channel medium access protocols is affected. An adaptive listening technique at the MAC Layer was exploited under Dynamic Spectrum Access to address the issue. Adaptive listening proposes a dynamic sleep/idle period based on the data transmission pattern. Thus, the S-MAC protocol further improves the performance in terms of energy consumption and bandwidth utilization at the MAC Layer. The performance of this proposed model is compared with other protocols like IEEE 802.11 and SMAC with periodic sleep. The proposed model offers better network throughput and better energy consumption as seen in these simulation results under various parameters.