Packet Collision Probability Research Articles

ACTOR: Adaptive Control of Transmission Power in RPL.

RPL-Routing Protocol for Low-Power and Lossy Networks (usually pronounced "ripple")-is the de facto standard for IoT networks. However, it neglects to exploit IoT devices' full capacity to optimize their transmission power, mainly because it is quite challenging to do so in parallel with the routing strategy, given the dynamic nature of wireless links and the typically constrained resources of IoT devices. Adapting the transmission power requires dynamically assessing many parameters, such as the probability of packet collisions, energy consumption, the number of hops, and interference. This paper introduces Adaptive Control of Transmission Power for RPL (ACTOR) for the dynamic optimization of transmission power. ACTOR aims to improve throughput in dense networks by passively exploring different transmission power levels. The classic solutions of bandit theory, including the Upper Confidence Bound (UCB) and Discounted UCB, accelerate the convergence of the exploration and guarantee its optimality. ACTOR is also enhanced via mechanisms to blacklist undesirable transmission power levels and stabilize the topology of parent-child negotiations. The results of the experiments conducted on our 40-node, 12-node testbed demonstrate that ACTOR achieves a higher packet delivery ratio by almost 20%, reduces the transmission power of nodes by up to 10 dBm, and maintains a stable topology with significantly fewer parent switches compared to the standard RPL and the selected benchmarks. These findings are consistent with simulations conducted across 7 different scenarios, where improvements in end-to-end delay, packet delivery, and energy consumption were observed by up to 50%.

Packet Collision Probability of Direct-to-Satellite IoT Systems

Packet Collision Probability of Direct-to-Satellite IoT Systems

Focusing on information context for ITS using a spatial age of information model

New technologies for sensing and communication act as enablers for cooperative driving applications. Sensors are able to detect objects in the surrounding environment and information such as their current location is exchanged among vehicles. In order to cope with the vehicles’ mobility, such information is required to be as fresh as possible for proper operation of cooperative driving applications. The age of information (AoI) has been proposed as a metric for evaluating freshness of information; recently also within the context of intelligent transportation systems (ITS). We investigate mechanisms to reduce the AoI of data transported in form of beacon messages while controlling their emission rate. We aim to balance packet collision probability and beacon frequency using the average peak age of information (PAoI) as a metric. This metric, however, only accounts for the generation time of the data but not for application-specific aspects, such as the location of the transmitting vehicle. We thus propose a new way of interpreting the AoI by considering information context, thereby incorporating vehicles’ locations. As an example, we characterize such importance using the orientation and the distance of the involved vehicles. In particular, we introduce a weighting coefficient used in combination with the PAoI to evaluate the information freshness, thus emphasizing on information from more important neighbors. We further design the beaconing approach in a way to meet a given AoI requirement, thus, saving resources on the wireless channel while keeping the AoI minimal. We illustrate the effectiveness of our approach in Manhattan-like urban scenarios, reaching pre-specified targets for the AoI of beacon messages.

Resource Allocation in 5G Platoon Communication: Modeling, Analysis and Optimization

New features brought by 5 G New Radio V2X (NR-V2X) support multiple vehicular communication types (unicast, groupcast, and broadcast) to coexist in road scenarios. However, the current standard does not specify the resource scheduling approach for groupcast to support such a new feature, which may severely degrade its packet delivery performance impacted by other communication types. In this paper, we investigate the scheduling and resource allocation approaches for a groupcast-based application, vehicle platooning, under the environment characterizing this new feature. We first analyze two baseline resource allocation approaches, i.e., Semi-persistent Scheduling (SPS) stated in the 3 rd generation partnership project (3GPP) and Random Selection (RS), based on the metric of packet collision probability. Subsequently, considering the issues from baseline approaches, we develop an Improved Random Selection (IRS) scheme to decrease the collision probability. We further propose to employ Deep Deterministic Policy Gradient (DDPG) algorithm to overcome the impact of inter-vehicle collaboration in the platoon based on local information. A Monte Carlo simulator is then used to verify the analytical models' results. The numerical results show that IRS significantly mitigates the packet collision probability compared with the baselines. Meanwhile, DDPG outperforms IRS in terms of the packet collision probability as well as average scheduled delay and is more robust to the change in the environment.

Short-Packet Covert Communication in Interweave Cognitive Radio Networks

In this work, we investigate short-packet covert communication in interweave cognitive radio networks (CRNs), where a secondary transmitter (ST) opportunistically accesses the occasionally idle spectrum under the supervision of a primary transmitter (PT). Considering that PT occupies the spectrum in a random manner, inevitable packet collisions occur when ST is transmitting while PT also starts to occupy its spectrum. To address this issue, we jointly optimize the block-length and the transmit power of ST's transmission to strike a balance between the packet collision and the decoding error subject to a covertness constraint. In particular, we first derive the packet collision probability, the covertness constraint, and the average packet error probability, characterizing the analytical expression for the average effective spectral efficiency (AESE). To further improve the system performance, an optimization problem is formulated to maximize AESE and the corresponding optimal block-length and transmit power are obtained for different kinds of channel information available at ST. Simulation results show that there is an optimal block-length to reduce the packet collision and decoding error in the interweave covert CRN.

Self-Optimizing Bluetooth Low Energy Networks for Industrial IoT Applications

This letter develops an efficient self-optimizing algorithm for Bluetooth Low Energy (BLE) networks in industrial IoT (IIoT) applications. The ultra-dense nature of IIoT applications implies that BLE networks are associated with a high probability of packet collisions, increasing the data collection latency. Determining the optimal packet transmission interval that minimizes the data collection latency is very challenging due to the non-linearity of this problem. We derive an analytic solution by which to realize an optimal advertising interval in a closed-form expression and prove its optimality and uniqueness. Based on a simple closed-form solution, we develop a low-complexity self-optimizing algorithm that minimizes the data collection latency. Simulation results confirm that the analytic results are accurate and that the proposed algorithm autonomously optimizes BLE networks.

Decentralized Power Control for an ALOHA-Type Random Multiple Access System with Short Packet Transmission

Machine to machine communication is an important scenario in a 6G communication network. Random multiple access has recently been revisited and considered a key technology for machine to machine communication scenarios due to many advantages such as without coordination setup time. It is a regret that packet collision probability will be extremely higher for random multiple access when massive devices randomly accessing base station. Decentralized power control is an efficient scheme in random multiple access systems which can support intraslot successive interference cancellation to recover multiple collided packets at receivers. However, existing studies of decentralized power control for random multiple access are with the assumption that blocklength of transmitted packets is infinite, which neglects that machine to machine communication is characterized by finite blocklength transmission (i.e., short packet) in 6G. This paper focuses decentralized power control with short packet transmission in random multiple access systems. First, the closed-form expression of signal to interference plus noise ratio (SINR) threshold for short packets is derived. Then, decentralized transmission power profile is defined based on derived SINR threshold of short packets, which can support intraslot successive interference cancellation deciding at receivers for an ALOHA-type random multiple access system. Further, we propose derivation method to maximize system throughput, which can reduce optimization cost. Theoretical findings in this paper can provide valuable benchmark for short packet transmission with decentralized power control in random multiple access systems.

A Successive Interference Cancellation-based Receiver for Secondary Surveillance Radar

Secondary Surveillance Radar communications, which purpose is to acquire aircrafts critical information, are on the brink of spectrum saturation. This is the result of dense traffic and different waveforms modulation schemes, used in Modes A/C and Mode S communication layers which share the same unscheduled propagation bandwidth. This leads to a significant rise of packet collision probability. In this context, we propose an original single-channel receiver able to process the simultaneous reception of several Mode A/C and S packets. The decoding strategy relies on the successive interference cancellation principle, comprising original detection, decoding and reconstruction processes. The relevance of our proposition is validated by numerical simulation and confirmed through field experiments on Automatic Dependent Surveillance-Broadcast signals reception.

Sliding Group Window with Rebacking off for Collision Avoidance in High-Efficiency Wireless Networks

It is difficult for wireless local area networks (WLANs), IEEE 802.11ax high-efficiency WLAN (HEW), to join next-generation innovations such as 5th generation (5G) and Internet of Things (IoT) because they still have their conventional channel access mechanism as their essential medium access control (MAC) protocol. The MAC protocol uses a traditional binary exponential backoff (BEB) algorithm to access channel resources that depend on the noncognitive increment of contention parameters for collision avoidance. In BEB, the collision issue increases with the increase in connected devices in the network due to a fixed contention window size. The larger the size of the network, the larger the collision in the network. To avoid such a circumstance, in this paper, we propose a sliding group window (sGW) mechanism dependent on collision-point assessment in order to improve the performance of MAC protocol for HEW. The proposed algorithm additionally presents a rebacking off for collision avoidance (ReBOCA) system for sGW, which combines the uniform dispersion of the contention parameters. This variation of an ordinary backoff algorithm permits the reasonable sliding of the user groups in the case of collision. The algorithm explicitly accounts for the peculiarities of dense environments and backward compatibility. Key aspects of the proposed solution include collision-point estimation, rebacking off for collision distribution convergence for fair treatment, and adaptive sliding of group windows to mitigate contention unfairness. We further formulated a closed-form Markov chain model for the performance analysis of our proposed sGW with ReBOCA scheme. Theoretical and practical results prove that our proposed scheme achieved maximal efficiency, even under dense environments. An increase in throughput with a lower packet collision probability was achieved with the proposed mechanism, and the efficiency increased as the number of contending stations increased than compared to traditional BEB performance. Our proposed ReBOCA mechanism enhanced network throughput by 38.18% than compared to the conventional BEB mechanism.

Design of Packet Collision Probability Reduction Algorithm on VANET

The IEEE 802.11p standard supporting the vehicular ad-hoc network (VANET) is based on the 802.11 MAC protocol, which allows equal opportunities for channel acquisition from all nodes in the network. Further, the nodes are leveled downward, and the probability of collision increases as the number of nodes increases. In this study, we observe the effects of reducing the collision probability when the algorithm where the current node of channel acquisition maintains competitive advantage for a certain period of time and OBA algorithm to appropriately determine the continuous transmission limit according to the transmission rate are applied together.

A TDMA-Based Data Gathering Protocol for Molecular Communication via Diffusion-Based Nano-Sensor Networks

This paper explores the application of molecular communication via diffusion-based nano-sensor networks (MCSNs) for data gathering applications in in-body medical systems. For MCSNs, the large and varying propagation delay in the channel presents a fundamental challenge for channel access, leading to packet collisions. Although packet collisions are well-studied for traditional wireless sensor networks, to date, there are no such studies conducted for MCSNs. Another fundamental challenge is the limited capabilities of the nano-sensors, rendering the existing solutions inefficient. Therefore, a novel light-weight time-division multiple access (TDMA)-based data gathering multiple access control (MAC) protocol is proposed. Light-weight here implies that long information, such as timestamps, is not exchanged. TDMA-based here implies that each nano-sensor is designated an exclusive time-slot. The lack of a channel model for spherical transmitters impairs theoretical analysis of the probability of packet collisions. To overcome this, the propagation delay is approximated as a Normal distribution. The model is validated using the widely popular particle-based simulation, which is also used to determine the packet duration considering ON-OFF shift keying. Building upon these analyses, a system-level simulator is developed to evaluate the proposed MAC protocol. For the first time, the packet collision probability is characterized under varied distances and diffusion coefficients. A key finding is the correlation between the channel utilization and the time-slot occupancy ratio, which can be used as a tool to optimize the performance of an MCSN. Finally, comparisons with conventional TDMA reveals that the proposed protocol can offer better performance.

Design of energy‐efficient intermittently connected sensor networks

This paper introduces the concept of intermittently connected sensor networks where sensors are sleep most of time and become active randomly and rarely. In the networks, packet collision probability and power consumption can be reduced. Meanwhile, the delivery delay increases with the use of the low activation values. In this paper, we design the energy‐efficient intermittently connected sensor networks, considering this trade‐off of activation control. We first provide the algorithm that computes the optimal packet forwarding rule achieving the minimum delivery delay, which can be calculated using the activation rates. We then propose the activation rate control methods, which control the activation rates of the sensors based on the density of the sensors and/or the number of wake‐ups of sensors having relay packets. By doing this, we can improve the delay performance, while suppressing the increase in the packet collision probability and the power consumption of sensors. Through simulation experiments, we demonstrate the effectiveness of our activation control methods in the intermittently connected sensor networks. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

A Collision-aware MAC Protocol for Efficient Performance in Wireless Sensor Networks

Both IEEE 802.11 and IEEE 802.15.4 standards adopt the CSMA-CA algorithm to manage contending nodes’ access to the wireless medium. CSMA-CA utilizes the Binary Exponential Backoff (BEB) scheme to reduce the probability of packet collisions over the communication channel. However, BEB suffers from unfairness and degraded channel utilization, as it usually favors the last node that succeeded in capturing the medium to send its packets. Also, BEB updates the size of the contention window in a deterministic fashion, without taking into consideration the level of collisions over the channel. The latter factor has a direct impact on the channel utilization and therefore incorporating it in the computation of the contention window’s size can have positive impacts on the overall performance of the backoff algorithm. In this paper, we propose a new adaptive backoff algorithm that overcomes the shortcomings of BEB and outperforms it in terms of channel utilization, power conservation, and reliability, while preserving the fairness among nodes. We model our algorithm using Markov chain and validate our system through extensive simulations. Our results show a promising performance for an efficient backoff algorithm.

Joint Power Control and Scheduling for High-Dynamic Multi-Hop UAV Communication: A Robust Mean Field Game

As an extensive prospect in communication technology, multi-hop unmanned aerial vehicle (UAV) faces some challenges as well. How to ensure the availability of time slots in high dynamic scenarios and the rationality and robustness of power allocation in massive scenarios remains to be resolved. In this paper, we propose a robust mean field game (MFG) framework to manage time slot resources and power resources. On the one hand, this framework can predict the potential conflicts of time slots and avoid them in time. On the other hand, it can well adapt to the massive scenarios with complex interference, in order to realize power control. The simulation results show that the robust MFG-based resource management scheme can not only reduce the probability of packet collision and packet loss, but also improve communication energy efficiency (EE) with better robustness.

Uplink NOMA Using Power Allocation for UAV-Aided CSMA/CA Networks

One of the most attractive applications of unmanned aerial vehicles (UAVs) is deploying wireless communication systems. We consider a UAV-based low-altitude platform (LAP) to deploy an aerial hotspot to provide Wi-Fi coverage without infrastructure and severe shadowing by urban or mountainous terrain. To address the performance degradation of carrier sense multiple access with collision avoidance (CSMA/CA) by increasing packet collisions with the number of clients, we exploit nonorthogonal multiple access (NOMA). To the best of authors' knowledge, there are no previous studies on uplink NOMA in CSMA/CA networks. In the considered system, owing to the distributed architecture and small channel difference of stations, conventional NOMA methods in cellular systems are not suitable. In this paper, we propose a power allocation scheme for uplink transmissions using predetermined power levels with a stochastic power selection to reduce the probability of packet collisions. A new medium access control procedure for uplink NOMA with CSMA/CA is also presented. The analytic results demonstrate that the proposed scheme achieves better saturation throughput and average packet delay than conventional CSMA/CA.

On improving throughput of multichannel ALOHA using preamble-based exploration

Machine-type communication (MTC) has been extensively studied to provide connectivity for devices and sensors in the Internet-of-thing (IoT). Thanks to the sparse activity, random access, e.g., ALOHA, is employed for MTC to lower signaling overhead. In this paper, we propose to adopt exploration for multichannel ALOHA by transmitting preambles before transmitting data packets in MTC, and show that the maximum throughput can be improved by a factor of 2 − e−1 ≈ 1.632, In the proposed approach, a base station (BS) needs to send the feedback information to active users to inform the numbers of transmitted preambles in multiple channels, which can be reliably estimated as in compres-sive random access. A steady-state analysis is also performed with fast retrial, which shows that the probability of packet collision becomes lower and, as a result, the delay outage probability is greatly reduced for a lightly loaded system. Simulation results also confirm the results from analysis.

Effects of Retransmission Limit on the Performance of Centralized Random Backoff

Previous studies showed that the packet collision probability in the 802.11 Distributed Coordination Function (DCF) can approach zero by adopting Centralized Random Backoff (CRB), which improves the total throughput performance. Moreover, it was reported that wireless networks using CRB maintain a high level of compatibility to legacy wireless local area networks (WLANs) when they coexist. However, little attention has been paid to relations between the performance of CRB and the retransmission limit, although the number of retransmission limit is an essential parameter that must be carefully chosen when implementing CRB for efficient WLANs. This article presents more realistic Markov chain models, and studies the impact of retransmission limit on the performance of CRB. These relations are also investigated by Monte Carlo simulation in more practical scenarios. Results show the trade-off that the total throughput increases with the retransmission limit when the number of nodes is larger than 15; whereas, the channel access opportunities in the mixed network scenario are more unevenly distributed between nodes as the retransmission limit increases. It is also shown in the simulation results that the throughput degradation caused by the hidden node problem is alleviated as the retransmission limit increases.

Impact of Big Vehicle Shadowing on Vehicle-to-Vehicle Communications

Vehicle to vehicle (V2V) communications using dedicated short-range communications (DSRC) are considered a promising technology for enhancing road safety. However, in V2V communications, passenger cars suffer from obstruction of bigger vehicles such as buses or trucks. Based on our measurement, a big vehicle can cause a signal loss from 10 to 15 dB due to shadowing. This results in a shorter communication range and reduces the safety message dissemination capability. In this paper, we analyze the impact of shadowing caused by multiple big vehicles on the V2V communication of passenger cars. We propose a model that takes into account both geometric and stochastic shadowing of multiple big vehicles. In order to cope with the physical size of vehicles and safety distance between them in the real world, we propose to use a repulsive point process called hardcore repulsive Poisson point process (PPP) to model the locations of vehicles. Generating procedure and some basic properties of this process are introduced. Based on the proposed model, we derive the average length of the shadow region and the shadowing loss caused by multiple big vehicles. We show that when the number of big vehicles increases from 10% to 80% of total vehicles in one lane, the shadow region increases from 50 m to 450 m on the road. Furthermore, the shadowing loss causes the relative number of cars within communication range of a typical car to reduce from 90% to between 15% and 50%, depending on whether the big vehicles are in the same or the adjacent lane of the consider car. We analyse the packet collision probability while taking into consideration the big vehicle shadow region and observe significant packet collisions without dedicated bus lanes.

An Enhanced Receiver to Decode Superposed LoRa-Like Signals

To cope with the exponential rise of emerging technology, there have been significant developments in intelligent communication systems aimed at low-power and long-range wireless Internet-of-Things (IoT) communication. Among the various number of leading low-power wide-area network (LPWAN) technologies, long range (LoRa) has emerged to be an attractive solution to connect devices in free bands. Operating in unlicensed bands requires connected objects to reduce their energy consumption. To this end, one of the adopted techniques is random access to the radio channel, which leads to an increase in the probability of packet collisions. In this article, we propose a new receiver capable to decode several IoT LoRa-like signals simultaneously received with the same spreading factor which leads to destructive collisions. Based on the particular structure of the received signals and the successive interference cancellation (SIC) algorithm, we propose a novel approach to decode superposed LoRa-like signals iteratively. Simulations and real LoRa deployments are presented to validate the efficiency of our receiver.

Resource Allocation to Massive Internet of Things in LoRaWANs.

A long-range wide area network (LoRaWAN) adapts the ALOHA network concept for channel access, resulting in packet collisions caused by intra- and inter-spreading factor (SF) interference. This leads to a high packet loss ratio. In LoRaWAN, each end device (ED) increments the SF after every two consecutive failed retransmissions, thus forcing the EDs to use a high SF. When numerous EDs switch to the highest SF, the network loses its advantage of orthogonality. Thus, the collision probability of the ED packets increases drastically. In this study, we propose two SF allocation schemes to enhance the packet success ratio by lowering the impact of interference. The first scheme, called the channel-adaptive SF recovery algorithm, increments or decrements the SF based on the retransmission of the ED packets, indicating the channel status in the network. The second approach allocates SF to EDs based on ED sensitivity during the initial deployment. These schemes are validated through extensive simulations by considering the channel interference in both confirmed and unconfirmed modes of LoRaWAN. Through simulation results, we show that the SFs have been adaptively applied to each ED, and the proposed schemes enhance the packet success delivery ratio as compared to the typical SF allocation schemes.