Mean Packet Research Articles

Analysis of 4G/LTE Network Performance in North-Central Nigeria: A Comprehensive Drive Test Approach

The proliferation of mobile devices and escalating demand for data services have resulted in a substantial increase in data traffic across Nigeria, especially in the North Central region due to heavy migration of individuals and organizations towards Abuja, the federal capital. However, despite the growing adoption of 4G/LTE networks in North Central Nigeria, users encounter persistent challenges in accessing high-speed internet and poor service network. This study investigates the performance of 4G/LTE networks in North-Central Nigeria using a comprehensive drive test methodology carried out in Abuja, Lafia and Makurdi. It covered a duration of 3hrs (12.00noon to 15.00pm) for 3days (3rd - 6th January, 2024). For each test day, drive tests covered a period of data measurements divided into 3,600 time-steps, with each time-step sized at 1sec; and scaled to 1:150 units. Key metrics including network speed, latency, uptime, coverage, and signal power were evaluated across major Mobile Network Operators. Result shows that D-NGN has the highest mean speed (9.543Mbps), packet loss (2.007%), uplink percentage (97.714%), and Network coverage (87.514%). It has the least latency (25.921) but high packet loss (2.007%). However, C-NGN shows lowest mean speed (6.638Mbps), uplink percentage (38.706%) and Signal power (-78.057dBm) but lowest mean packet loss (0.121%). A-NGN has the highest mean signal power (-61.867dBm) while B-NGN has highest latency (44.070ms) and lowest Network coverage (60.731%). This reveals that D-NGN has dominance in network performance, outperforming A-NGN, B-NGN, and C-NGN. It is recommended that MNOs in North-Central Nigeria should strategically enhance their network infrastructure to improve service delivery, particularly in suburban and rural areas where performance lags. D-NGN, the frontrunner in network speed and coverage, could further solidify its market leadership by addressing identified latency and packet loss issues especially in Makurdi. Moreover, MNOs with lower performance metrics could invest in expanding coverage and optimizing network configurations to meet user demands, thereby increasing competitiveness and customer satisfaction across the region.

Modeling and Performance Analysis of LBT-Based RF-Powered NR-U Network for IoT.

Energy harvesting combined with spectrum sharing offers a promising solution to the growing demand for spectrum while keeping energy costs low. New Radio Unlicensed (NR-U) technology enables telecom operators to utilize unlicensed spectrum in addition to the licensed spectrum already in use. Along with this, the energy demands for the Internet of Things (IoT) can be met through energy harvesting. In this regard, the ubiquity and ease of implementation make the RF-powered NR-U network a sustainable solution for cellular IoT. Using a Markov chain, we model the NR-U network with nodes powered by the base station (BS). We derive closed-form expressions for the normalized saturated throughput of nodes and the BS, along with the mean packet delay at the node. Additionally, we compute the transmit outage probability of the node. These quality of service (QoS) parameters are analyzed for different values of congestion window size, TXOP parameter, maximum energy level, and energy threshold of the node. Additionally, the effect of network density on collision, transmission, and energy harvesting probabilities is observed. We validate our model through simulations.

Explainable Learning-Based Timeout Optimization for Accurate and Efficient Elephant Flow Prediction in SDNs

Accurately and efficiently predicting elephant flows (elephants) is crucial for optimizing network performance and resource utilization. Current prediction approaches for software-defined networks (SDNs) typically rely on complete traffic and statistics moving from switches to controllers. This leads to an extra control channel bandwidth occupation and network delay. To address this issue, this paper proposes a prediction strategy based on incomplete traffic that is sampled by the timeouts for the installation or reactivation of flow entries. The strategy involves assigning a very short hard timeout (Tinitial) to flow entries and then increasing it at a rate of r until flows are identified as elephants or out of their lifespans. Predicted elephants are switched to an idle timeout of 5 s. Logistic regression is used to model elephants based on a complete dataset. Bayesian optimization is then used to tune the trained model Tinitial and r over the incomplete dataset. The process of feature selection, model learning, and optimization is explained. An extensive evaluation shows that the proposed approach can achieve over 90% generalization accuracy over 7 different datasets, including campus, backbone, and the Internet of Things (IoT). Elephants can be correctly predicted for about half of their lifetime. The proposed approach can significantly reduce the controller–switch interaction in campus and IoT networks, although packet completion approaches may need to be applied in networks with a short mean packet inter-arrival time.

An Optimal Resource Allocation Scheme with Carrier Aggregation in 5G Network under Unlicensed Band

Carrier aggregation (CA) technology in the Fifth-Generation (5G) network can be considered as a major feature for high-rate data services, which can be combined with the concept of 5G in unlicensed band (5G-U) for data offloading to further enhance the efficiency of the scarce licensed spectral resource. However, the introduction of cellular services in an unlicensed spectrum can force unlicensed band users to silent mode. Meanwhile, the coexistence among different radio access technologies operating on the same frequency band is a complex issue, especially considering the requirement diversity of quality of service (QoS) in networking. In this paper, we propose an optimal resource allocation mechanism to maximize system performance satisfaction for multiple types of services with different QoS requirements in the 5G-U network with a CA feature to address the challenge. Additionally, the performance of services in Wi-Fi system is protected by reserving the minimum spectrum resource when offloading for the 5G-U network. Analytical results on the mean ergodic achievable rate of Wi-Fi services and the mean packet delay of 5G services are provided to maximize the system performance satisfaction. Numerical results demonstrate the effectiveness of the proposed algorithm, wherein optimal spectrum and power allocation can contribute to the maximum system satisfaction in a 5G-U network with a CA feature.

Maximizing the stable throughput of heterogeneous nodes under airtime fairness in a CSMA environment

The stability region of non-persistent CSMA is analyzed in a general heterogeneous network, where stations have different mean packet arrival rates, packet transmission times probability distributions and transmission probabilities. The considered model of CSMA captures the behavior of the well known CSMA/CA, at least as far as stability and throughput evaluation are concerned. The analysis is done both with and without collision detection. Given the characterization of the stability region, throughput-optimal transmission probabilities are identified under airtime fairness, establishing asymptotic upper and lower bounds of the maximum achievable stable throughput. The bounds turn out to be insensitive to the probability distribution of packet transmission times. Numerical results highlight that the obtained bounds are tight not only asymptotically, but also for essentially all values of the number of stations. The insight gained leads to the definition of a distributed adaptive algorithm to adjust the transmission probabilities of stations so as to attain the maximum stable throughput.

Packet-Level Throughput Analysis and Energy Efficiency Optimization for UAV-Assisted IAB Heterogeneous Cellular Networks

In this paper, we investigate the packet-level throughput and energy efficiency of millimeter-wave unmanned aerial vehicle (UAV)-assisted integrated access and backhaul (IAB) heterogeneous cellular networks with spatiotemporal traffic. Specifically, we develop a theoretical framework to analyze the mean packet throughput and energy efficiency of the network based on stochastic geometry and queueing theory, whereby the spatial randomness of network deployment and the temporal randomness of network traffic can be appropriately characterized. Different from the traditional network performance metrics emphasizing transmission and resource consumption, the packet-level performance helps to better understand the impact of not only packet transmission but also packet waiting time in a multihop network. Simulation results demonstrate that the assistance of IAB-based UAVs can efficiently relieve the load of terrestrial macro- and small-cell networks, and the appropriate network deployment parameters play pivotal roles in improving both the packet-level throughput and energy efficiency performance. By jointly optimizing the key network parameters, the packet energy efficiency can be significantly improved while ensuring the required mean packet throughput of the network.

An Analysis of the Mixed IEEE 802.11ax Wireless Networks in the 5 GHz Band.

This paper presents an analysis of the IEEE 802.11ax networks' coexistence with legacy stations, namely IEEE 802.11ac, IEEE 802.11n, and IEEE 802.11a. The IEEE 802.11ax standard introduces several new features that can enhance network performance and capacity. The legacy devices that do not support these features will continue to coexist with newer devices, creating a mixed network environment. This usually leads to a deterioration in the overall performance of such networks; therefore, in the paper, we want to show how we can reduce the negative impact of legacy devices. In this study, we investigate the performance of mixed networks by applying various parameters to both the MAC and PHY layers. We focus on evaluating the impact of the BSS coloring mechanism introduced to the IEEE 802.11ax standard on network performance. We also examine the impact of A-MPDU and A-MSDU aggregations on network efficiency. Through simulations, we analyze the typical performance metrics such as throughput, mean packet delay, and packet loss of mixed networks with different topologies and configurations. Our findings indicate that implementing the BSS coloring mechanism in dense networks can increase throughput by up to 43%. We also show that the presence of legacy devices in the network disrupts the functioning of this mechanism. To address this, we recommend using an aggregation technique, which can improve throughput by up to 79%. The presented research revealed that it is possible to optimize the performance of mixed IEEE 802.11ax networks.

The effect of transverse wavefront width on specular neutron reflection.

In the analysis of neutron scattering measurements of condensed matter structure, it normally suffices to treat the incident and scattered neutron beams as if composed of incoherent distributions of plane waves with wavevectors of different magnitudes and directions that are taken to define an instrumental resolution. However, despite the wide-ranging applicability of this conventional treatment, there are cases, such as specular neutron reflectometry, in which the structural length scales of the scattering object require that the wavefunction of an individual neutron in the beam be described by a spatially localized packet - in particular with respect to the transverse extent of its wavefronts (i.e. normal to the packet's mean direction of propagation). It is shown in the present work that neutron diffraction patterns observed for periodic transmission phase gratings, as well as specular reflection measurements from patterned thin films with repeat units of the order of micrometres, can be accurately described by associating an individual neutron with a wave packet and treating a beam as a collection of independent packets. In these cases, accurate analysis requires that the transverse spatial extent of a neutron packet wavefront be accounted for in addition to the angular divergence of the beam that is characterized by a distribution of packet mean wavevector directions. It is shown how a measure of the effective transverse spatial extent of the neutron packet - over which its wavefronts are of sufficient uniformity to produce coherent scattering - can be determined by employing reference diffraction gratings and patterned thin films of known structure and composition.

Multi Swarm Optimization Based Clustering with Tabu Search in Wireless Sensor Network.

Wireless Sensor Networks (WSNs) can be defined as a cluster of sensors with a restricted power supply deployed in a specific area to gather environmental data. One of the most challenging areas of research is to design energy-efficient data gathering algorithms in large-scale WSNs, as each sensor node, in general, has limited energy resources. Literature review shows that with regards to energy saving, clustering-based techniques for data gathering are quite effective. Moreover, cluster head (CH) optimization is a non-deterministic polynomial (NP) hard problem. Both the lifespan of the network and its energy efficiency are improved by choosing the optimal path in routing. The technique put forth in this paper is based on multi swarm optimization (MSO) (i.e., multi-PSO) together with Tabu search (TS) techniques. Efficient CHs are chosen by the proposed system, which increases the optimization of routing and life of the network. The obtained results show that the MSO-Tabu approach has a 14%, 5%, 11%, and 4% higher number of clusters and a 20%, 6%, 14%, and 6% lesser average packet loss rate as compared to a genetic algorithm (GA), differential evolution (DE), Tabu, and MSO based clustering, respectively. Moreover, the MSO-Tabu approach has 136%, 36%, 136%, and 38% higher lifetime computation, and 22%, 16%, 51%, and 12% higher average dissipated energy. Thus, the study’s outcome shows that the proposed MSO-Tabu is efficient, as it enhances the number of clusters formed, average energy dissipated, lifetime computation, and there is a decrease in mean packet loss and end-to-end delay.

Joint Optimization of Fractional Frequency Reuse and Cell Clustering for Dynamic TDD Small Cell Networks

In dense small cell networks, dynamic time-division duplex (D-TDD) technology has emerged as a promising solution to accommodate the fast variants of volatile traffic conditions because it allows each cell to dynamically configure the uplink and downlink transmission directions. However, the flexibility of traffic configuration introduces additional inter-cell interference, which largely deteriorates network throughput. This paper proposes an interference coordination technology for D-TDD small cell networks by integrating fractional frequency reuse (FFR) with cell clustering. To evaluate the system performance, we develop a theoretical framework to analytically characterize the mean packet throughput (MPT) performance by considering the impact of spatio-temporal traffic. The analytical model can be extended to further study the FFR-based D-TDD, clustered D-TDD, and traditional D-TDD networks. We verify the accuracy of our analysis through simulations and whereby explore the effect of different network parameters. Numerical results demonstrate that the proposed scheme outperforms clustered D-TDD and traditional D-TDD for both the downlink and uplink spatially averaged MPT, and can significantly improve the performance in uplink while slightly decreasing that in downlink compared with FFR-based D-TDD. Furthermore, by jointly optimizing network parameters, the spatially averaged MPT can be maximized while enduring MPT per user.

5G Infrastructure Network Slicing: E2E Mean Delay Model and Effectiveness Assessment to Reduce Downtimes in Industry 4.0

Fifth Generation (5G) is expected to meet stringent performance network requisites of the Industry 4.0. Moreover, its built-in network slicing capabilities allow for the support of the traffic heterogeneity in Industry 4.0 over the same physical network infrastructure. However, 5G network slicing capabilities might not be enough in terms of degree of isolation for many private 5G networks use cases, such as multi-tenancy in Industry 4.0. In this vein, infrastructure network slicing, which refers to the use of dedicated and well isolated resources for each network slice at every network domain, fits the necessities of those use cases. In this article, we evaluate the effectiveness of infrastructure slicing to provide isolation among production lines (PLs) in an industrial private 5G network. To that end, we develop a queuing theory-based model to estimate the end-to-end (E2E) mean packet delay of the infrastructure slices. Then, we use this model to compare the E2E mean delay for two configurations, i.e., dedicated infrastructure slices with segregated resources for each PL against the use of a single shared infrastructure slice to serve the performance-sensitive traffic from PLs. Also we evaluate the use of Time-Sensitive Networking (TSN) against bare Ethernet to provide layer 2 connectivity among the 5G system components. We use a complete and realistic setup based on experimental and simulation data of the scenario considered. Our results support the effectiveness of infrastructure slicing to provide isolation in performance among the different slices. Then, using dedicated slices with segregated resources for each PL might reduce the number of the production downtimes and associated costs as the malfunctioning of a PL will not affect the network performance perceived by the performance-sensitive traffic from other PLs. Last, our results show that, besides the improvement in performance, TSN technology truly provides full isolation in the transport network compared to standard Ethernet thanks to traffic prioritization, traffic regulation, and bandwidth reservation capabilities.

Buffer-loss estimation to address congestion in 6LoWPAN based resource-restricted ‘Internet of Healthcare Things’ network

The Internet of Healthcare Things (IoHT) consists of a wide variety of resource-restricted, heterogeneous, IoT-enabled, wearable/non-wearable medical equipment (things) that connect over the internet to transform traditional healthcare into a smart, connected, proactive, patient-centric healthcare system. The pivotal functions of the 6LoWPAN protocol stack enable comprehensive integration of such networks from wearable wireless sensor networks (W-WSN) to IoHT, as TCP/IP does not suffice the requirements of IoHT networks. As a result, the congestion in the IoHT network increases with a growing number of devices, resulting in loss of critical medical information due to buffer loss and channel loss, which is unacceptable. In this paper, we explored different applications of patient-centric IoHT architectures to draw a realistic resource-limited topological layout of IoHT for congestion estimation. After critically reviewing existing congestion schemes for 6LoWPANs, we proposed an effective buffer-loss estimation model based on the Queuing Theory to determine the number of packets lost at the node’s buffer. The buffer is modeled as an M/M/1/K Markov Chain Queue. The M/M/1/K Queue equilibrium equation is used to establish a relationship between the probabilities of the buffer being empty or completely filled. We derived the expressions for total buffer-loss probability and expected mean packet delay for the resource-constraint IoHT network. Furthermore, to validate the buffer-loss estimation, an analytical model is used to compare buffer-loss probabilities, the number of packets dropped at leaf/intermediate nodes and the number of packets successfully received at the local sink node. The results show a close correlation between both the models on varying values of the number of leaf nodes, buffer size, offered packet load and available channel capacity. Thus, in resource-restrictive IoHT, the proposed model performs better than two related works.

Secure Global Positioning System For Vehicle To Vehicle (V2V) Communication

In this paper, we first focused on the developing a secure global positioning system for vehicle-to-vehicle (V2V) communication which adopts the secure transmission with respect to vehicle location. In literature, different existing positioning and wireless communication technologies have been presented with their detailed comparison with the global positioning system. In methodology we proposed a GPS-based model of Contention Intensity Control with Rate Control (CICRC) for efficient and secure V2V communication. We deduced the PDR and mean packet delay between heavy and low vehicle load scenarios under fully-connected vehicle network case and a hidden terminal participation case. We also presented the PDR and mean packet delay of safety messages generated with deterministic inter-arrival time and exponential inter-arrival time, respectively. Our GPS-based CICRC model provides a good match with simulation results on well-known MATLAB tool with wireless and networking toolbox. We also verified the model by showing our simulation provides good match with analytical results. Finally, comparing PDR, mean delay and PCR with proposed CICRC by some metrics, we can verify that CICRC improves V2V communication performance compared to existing communication methods. The simulation results we obtained show the packet delivery ratio under CICRC increases nearly 10% compared with that under CSMA [8] in heavy vehicle load scenarios for secure communication undermining the vehicle location. We have also found that if packet collisions occur in some vehicles at the during V2V communication, the collision probability between those vehicles in deterministic inter-arrival time will be always higher than that in exponential inter-arrival time. Average successful packet reception time under CICRC is around 20ms lower than CSMA in heavy vehicle loads, which verifies that CICRC improves on CSMA for the GPS performance especially in heavy vehicle load scenarios for secure communication

A new load balancing clustering method for the RPL protocol

Internet of things (IoT) is a network of different interconnected objects that are capable to collect and exchange data without human interaction. IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) is the common IoT routing protocol. One of the main drawbacks of the RPL protocol is lack of support of load balancing leads to unfair distribution of traffic load in the network which may decrease network efficiency. In this paper for load balancing, we proposed a new method called C-Balance based on cluster ranking to increase the network lifetime. In this method, two ranks are calculated for each node. The first rank is used to identify clusters and cluster heads and the second rank is used to select parents of each cluster head to forward packets towards the destination. To calculate these ranks, several metrics are used including Expected Transmission Count, hop count, residual energy and number of children. To investigate the performance of the proposed method, it has been simulated with Cooja simulator in the form of nodes with mobility and non-mobility scenarios plus using a random topology network with 20, 40 and 60 nodes experiments. The results are compared with OF0 and MRHOF standard objective functions as well as the QU-RPL method. The final results in both scenarios show that the proposed method in the field of energy consumption, network lifetime and load balancing has improved compared to the other methods. In terms of end-to-end delay, the proposed method has more delay compared to the standard objective functions and QU-RPL method. The calculation of the mean packet delivery ratio (PDR) of these four methods also shows that the proposed method has an acceptable performance. Final results indicate that on average, there is a 30–45% improvement in energy consumption, 15–23% reduction in average number of children and 22–48% improvement in network lifetime are obtained compared to the other methods. Finally, there is about 12% progress for PDR compared to the OF0.

Throughput Analysis of Small Cell Networks Under D-TDD and FFR

Dynamic time-division duplex (D-TDD) has emerged as an effective solution to accommodate the unaligned downlink and uplink traffic in small cell networks. However, the flexibility of traffic configuration also introduces additional inter-cell interference. In this letter, we study the effectiveness of applying fractional frequency reuse (FFR) as an interference coordination technique for D-TDD small cell networks. We derive the analytical expressions of downlink and uplink mean packet throughput (MPT), then study a network parameter optimization problem to maximize MPT while guaranteeing each user's throughput. Numerical results corroborate the benefits of the proposed FFR-based D-TDD in terms of improving throughput.

Spatiotemporal Modeling of Massive MIMO Systems With Mixed-Type IoT Devices: Scheduling Optimization With Delay Constraints

In this article, we develop a framework for the analysis of massive multiple-input-multiple-output (MIMO) systems where multiple types of devices with different configurations and requirements co-exist, by taking into account the randomness of spatial locations and temporal traffic. A tight closed-form approximation of the spatial mean packet throughput, which denotes the average number of packets that are successfully transmitted at any unit time slot and area is derived, by using tools from the stochastic geometry and queuing theory, which captures all the key features of the devices in the Internet of Things (IoT). Based on the analysis, we investigate the optimal scheduling number for each type of devices that maximizes the spatial mean packet throughput while meeting devices' delay constraints. It is found that when the base station (BS) has excessive number of antennas ( M), the BS should schedule all devices under its coverage, regardless of devices' variances on spatiotemporal configurations and demands. However, when M is limited, the BS should have a bias on scheduling devices with heavier traffic, lower decoding threshold, or higher transmit power. On this basis, if the delay constraint of one device becomes stricter, it will be scheduled more often to access the radio channel, which acts more significantly when the ratio of M to the deployment density of devices gets smaller.

Applying a Dwell Time-Based 5G V2X Cell Selection Strategy in the City of Los Angeles, California

The fifth generation of wireless networks is expected to provide high capacity, low latency, high reliability, and massive connectivity services. Ultra-dense network (UDN) is a clear trend for enhancing capacity, coverage, and load balancing. In UDNs, the cell selection issue for moving vehicles should be addressed. In this paper, a cell selection strategy known as a dwell time estimation (DTE) scheme is proposed, which is based on Vehicle-to-Everything (V2X) communications. It selects small cells that have the longest dwell time in a vehicle’s direction to decrease handover (HO) rate. The proposed DTE scheme is evaluated using two datasets, which are 5G small cells and vehicles datasets, that were collected in the city of Los Angeles in California. The simulation result shows that our DTE algorithm outperforms other recent related schemes in terms of the mean number of HOs by up to 36.26% because it prolongs the dwell time of the vehicle within the serving small cell. Consequently, it reduces the average number of HO failures and unnecessary HOs. In addition, it gives improvements in terms of the average achievable downlink throughput and network energy efficiency. Furthermore, it has superiority over the other schemes in terms of the mean packet delay by up to 16.49%.

TCP-FLASH - A Fast Reacting TCP for Modern Networks

The Transmission Control Protocol (TCP) plays a critical role in the Internet as it is the protocol used for data transport by most Internet services and applications. With rapid advances in broadband Internet and mobile/wireless networks, current TCPs are increasingly becoming the bottleneck. This work tackles this challenge by developing a novel TCP design called Fast Launch with Agile congeStion Handling (FLASH) that not only achieves improved performance for long TCP flows but also significantly raises the performance of short to medium TCP flows that are far more common in the Internet. We evaluated its long-term and short-term performance over a wide range of network environments, using two emulation platforms (Pantheon and DummyNet) as well as Internet experiments. Compared to two of the leading TCP designs deployed in the Internet, i.e., Cubic and BBR, FLASH consistently achieved higher long-term and short-term bandwidth efficiency. For example, in trace-driven emulated experiments using Poisson traffic with a mean flow size of 1 MB operating at medium link utilization of 27%, FLASH can reduce the flow completion time (FCT) by 36% (vs. Cubic) and 26% (vs. BBR), with mean packet queueing delay of 11.7 ms compared to 3.4 ms (Cubic) and 8.8 ms (BBR). It also maintained good fairness with itself and is competitive against Cubic and BBR sharing the same bottleneck. In addition, FLASH has been tested in two real-world Internet environments. In the cloud-to-cloud experiment, it reduced FCT by 52.9% (vs. Cubic) and 46.6% (vs. BBR), while in the cloud-to-client experiment, it reduced FCT by 31.3% (vs. Cubic) and 12.7% (vs. BBR). FLASH is entirely sender-based and is compatible with current TCP receivers, thereby readily deployable in current Internet servers.

Toward lower-diameter large-scale HPC and data center networks with co-packaged optics

We investigate the advantages of using co-packaged optics for building low-diameter, large-scale high-performance computing (HPC) and data center networks. The increased escape bandwidth offered by co-packaged optics can enable high-radix switch implementations of more than 150 switch ports, which can be combined with data rates of up to 400 Gb/s per port. From the network architecture perspective, the key benefits of using co-packaged optics in future fat-tree networks include (a) the ability to implement large-scale topologies of > --> 11 , 000 end points by eliminating the need for a third switching layer and (b) the ability to provide up to 4 × higher bisection bandwidth compared to existing solutions, reducing at the same time the number of required switch application-specific integrated circuits by > --> 80 % . From the network operation perspective, both reduced energy consumption and lower packet delays can be achieved since fewer hops are required; i.e., packets need to traverse fewer serializer/deserializer lanes and fewer switch buffers, which reduces the probability of contending with other packets and improves the tolerance of network congestion. The performance of the proposed architecture is evaluated via discrete-event simulations for a wide range of representative HPC synthetic-traffic cases that include both hotspot and non-hotspot scenarios. The simulation results suggest that co-packaged optics form a promising solution to keep up with bandwidth scaling in future networks, while the reduced number of switching layers can lead to significant mean packet delay improvements that start from 30% and reach up to 74% for high-load conditions.

Modeling and delay performance analysis of wireless regional area networks under incumbent coexistence and self‐coexistence with multichannel operations

SummaryIncumbent coexistence and self‐coexistence are common among wireless regional area networks (WRANs) using TV white space (TVWS) due to their large coverages and opportunistic spectrum access. Among incumbents of WRANs are wireless microphones (WMs) whose frequent ON–OFF activities result in intermittent availability of transmission channels. In this work, WRANs under self‐coexistence in addition to incumbent coexistence are modeled for queueing analysis using two‐dimensional (2D) Markov chains taking into account intermittent channel availability for multichannel operations. The proposed models are created based on the widely used ON–OFF Markov chain model for an individual transmission channel. The Markov chain structures depend on the number of WRANs under self‐coexistence as well as the number of transmission channels. In order to reduce the computational complexity associated with a large number of channels, truncated Markov chain models are proposed so that the scenarios with more channels than WRANs can be analyzed with the same complexity as the scenarios with the same number of channels and WRANs. The matrix geometric method is used to numerically compute steady‐state probabilities of the Markov chain, which are then used to evaluate the mean packet delay performance. These results are then used to quantify the mean packet delay obtained from channel sharing among WRANs under self‐coexistence with multichannel operations. Finally, the impact of varying the number of channels as well as varying the ON‐OFF durations of each channel on the delay performance is observed.