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Wireless local area networks (WLANs) play a crucial role in the internet of things (IoT) landscape, facilitating constant data exchange among devices. However, the inherent security vulnerabilities in these networks, stemming from limited computational resources, pose significant challenges to deploying robust security measures. This research addresses the security concerns surrounding IoT devices within the IEEE 802.11ah WLAN environment by introducing the SecureScanML algorithm, a novel machine learning (ML) approach designed to optimize Internet-wide port scans (IWPS) for enhanced device security while preserving network performance. The SecureScanML algorithm leverages Q-learning, a reinforcement learning technique, to dynamically adjust the scan rates of IoT devices adaptively. Through this approach, the algorithm effectively reduces vulnerabilities, achieving a notable 35.7% reduction, while maintaining key network performance metrics. With a throughput of 2.8 Mbps, a packet delivery ratio of 97.3%, an adaptability index of 0.91, a convergence speed of 420 s, and a low latency of 42 ms, the proposed algorithm surpasses existing methods such as TA, RA, SSR, CNN-LSTM, RLA, and RSR. Simulation results corroborate the efficacy of SecureScanML in mitigating vulnerabilities without compromising network efficiency. The algorithm strikes a fine balance between proactive vulnerability management and network performance preservation. Moreover, the study explores the impact of security-performance weight parameters on the algorithm's behavior, providing valuable insights for fine-tuning the system to achieve specific security and performance objectives. Notably, for a security-performance weight of 0.5, the algorithm demonstrates high throughput and vulnerability reduction alongside low latency. [ABSTRACT FROM AUTHOR]

We consider the problem of energy efficiency aware dynamic adaptation of data transmission rate and transmission power of the users in carrier sensing based Wireless Local Area Networks (WLANs) in the presence of path loss, Rayleigh fading and log-normal shadowing. For a data packet transmission, we formulate an optimization problem, solve the problem, and propose a rate and transmission power adaptation scheme with a restriction methodology of data packet transmission for achieving the optimal energy efficiency. In the restriction methodology of data packet transmission, a user does not transmit a data packet if the instantaneous channel gain of the user is lower than a threshold. To evaluate the performance of the proposed scheme, we develop analytical models for computing the throughput and energy efficiency of WLANs under the proposed scheme considering a saturation traffic condition. We then validate the analytical models via simulation. We find that the proposed scheme provides better throughput and energy efficiency with acceptable throughput fairness if the restriction methodology of data packet transmission is included. By means of the analytical models and simulations, we demonstrate that the proposed scheme provides significantly higher throughput, energy efficiency and fairness index than a traditional non-adaptive scheme and an existing most relevant adaptive scheme. Throughput and energy efficiency gains obtained by the proposed scheme with respect to the existing adapting scheme are about 75% and 103%, respectively, for a fairness index of 0.8. We also study the effect of various system parameters on throughput and energy efficiency and provide various engineering insights.

Microstrip patch antennas are becoming increasingly popular because they are small, have low profiles, are easy to integrate, are very cheap, and work well. For this reason, this antenna could be used for wireless communication systems. This research paper reviews and studies 28 GHz microstrip patch antenna for wireless applications. Different substrate materials have been used to make these antennas, such as FR-4 (loss), FR-4 Epoxy, Rogers RT/droid 5880, TLC-30, Rogers RT/droid 5880 LZ, and others. Different substrate materials and shapes were used to make microstrip patch antennas with a frequency of 28 GHz. This article discusses the different sizes of antennas, the other geometric shapes antennas can take, the different ways antennas' properties can be analyzed, and the different types of antennas. It will also talk about the material, thickness, loss tangent, return loss, bandwidth, voltage standing wave ratio (VSWR), gain, efficiency, and directivity of the substrate. This antenna is used for super-high-frequency (SHF), radars, commercial wireless local area networks (LANs), cell phones, and other wireless communications systems. [ABSTRACT FROM AUTHOR]

This study realizes firmware-agnostic line-of-sight (LOS) identification to extend the range of WiFi-sensing applications. We developed a beamforming feedback (BFF)-based LOS identification algorithm. BFF frames are transmitted for multiple-input multiple-output (MIMO) communications. They can be obtained by capturing frames without custom firmware or specific chipsets and contain a beamforming feedback matrix (BFM) and subcarrier-averaged stream gain (SSG). These provide partial channel state information (CSI), and there are two major calculation steps involved from the CSI to the BFF: unquantized BFF (UQBFF) calculation and quantization. Focusing on the relationship between singular value decomposition and principal component analysis, we numerically demonstrated that the first column vectors of the BFM reflect the LOS/NLOS conditions. Therefore, the proposed BFF-based method extracts features from the first-column vectors of the BFM. In addition, SSGs were leveraged to improve the accuracy. To demonstrate the feasibility of the proposed method, we conducted experiments using commodity off-the-shelf devices compliant with the IEEE 802.11ac standard. In the experimental evaluation, the proposed BFF-based method achieved an identification accuracy of 75.0%, whereas the CSI-based method achieved an accuracy of 81.2%. Accuracy comparisons revealed that the accuracy degradation of the BFF-based identification from the CSI-based identification was primarily caused by UQBFF calculations rather than quantization.

Nowadays, the rising demand for digital communication technologies has contributed to the increase in the volume of traffic. This continuous trend of internet traffic has led to the deterioration of the quality of service (QoS) with reduced throughput and increased latency. This also is due to the proliferation of new broadband applications which require low latency and high throughput such as virtual reality and real-time gaming. Therefore, considering the aforementioned challenge in QoS of wireless networks, a link adaptation method is suggested in this study, in order to enhance the performance of the QoS in IEEE 802.11ac amendment wireless local-area network (WLAN). The proposed technique adaptively changes the transmission data rate by increasing or decreasing the modulation and coding scheme (MCS) level according to the traffic conditions. With the use of an OMNeT++ computer-aided design (CAD)-based simulation model, the effectiveness of the suggested approach is examined. Simulated findings were compared with the link adaptation approach of the default condition. The results of the simulation demonstrate that the proposed technique significantly increases throughput (36.48%) and decreases latency in comparison to the default situation. These findings demonstrate the technique's potential to improve WLAN QoS efficiency, notably in regard to throughput and latency. [ABSTRACT FROM AUTHOR]

The design, simulation, and analysis of a 3.5 GHz rectangular microstrip patch antenna (RMPA) have been carried out for this research article. The substrate material employed for the design is a lossy form of FR-4, which has a thickness of 0.5 mm, a dielectric permittivity of 4.3, and a loss tangent of 0.0005, respectively. The antenna receives power through a feeding line with an impedance of 50 Ω. The simulation was ultimately finished off with the help of some computer simulation tools. Following completion of the simulation, the findings revealed a directivity gain of 6.05 dBi, a voltage standing wave ratio (VSWR) of 1.0607, and a bandwidth of 144.1 MHz. The return loss was determined to be -30.611 dB. The suggested antenna's primary purpose was to attain a standard value for the VSWR while lowering the return loss. This antenna improves directivity gain and bandwidth and has applications in radars, mobile phones, and wireless local area networks (WLANs). The results of this proposed antenna were superior to those of a variety of studies that had been published in the past. [ABSTRACT FROM AUTHOR]

The use of channels in WLANs affects data communication. RTS Fragmentation Threshold (RTSFT), Fragmentation Threshold (FT), and Buffer Size (BS) input values; Receiver Channel Utilization% (RCU%) and Transmitter Channel Utilization% (TCU%) affect the output values. To use the communication channel most efficiently, RTSFT, FT, and BS input variable values, which give the best RCU% and TCU% values, were obtained using the Riverbed Modeler simulation tool. Bandwidth, which is an important parameter for increasing the QoS of Wireless Local Area Networks, provides only physical performance efficiency. The efficiency at which the bandwidth is used is extremely important for the pre-design of network topology. The channel utilization rate increases the efficient use of bandwidth in WLANs. RTSFT, FT, and BS, which affect the service quality in the MAC layer in WLANs, directly affect the quality of service. In this study, the Prediction of Receiver Channel Utilization% (RCU%) and Prediction of Transmitter Channel Utilization% (TCU%) performance criteria were predicted by using ANN algorithms. Using the Riverbed Modeler simulation tool, 125 different input variables with 11 nodes were selected and channel utilization was obtained. Used ANN data was obtained from real Riverbed Modeler simulation. Input variables (RTSFT, FT, and BS) against the output parameters (RCU% and TCU%) were obtained from ANN model prediction. It is concluded that the estimated RCU% and TCU% output values are revealed the affected directly proportional by the BS input and inversely proportional to the RTSFT and FT input values. [ABSTRACT FROM AUTHOR]

A compact, robust Koch fractal combined triangular monopole antenna incorporated with a Sierpinski fractal EBG unit cell array is proposed for integral solutions of wearable devices in WLAN standards. The fractal enabled EBG-Antenna has a modified triangular microstrip that acts as a radiator and a 2X2 array of Sierpinski square EBG unit cells as a reflective surface to enhance the performance also as a shield linking the antenna and human body. The proposed antenna demonstrations and impedance match bandwidth of 32 MHz, a gain of 7.86 dBi, Front to back ratio of 13 dB, Radiation Efficiency of 90.35 % at 2.45 GHz in free space. The EBG-Antenna performs well under different bending conditions and human tissue loading as verified by measurements. The specific absorption rate (SAR) is also evaluated and found within limits as per standards. The computed results accomplished the SAR of 0.302 W/Kg, 0.1423 W/Kg for 1 g, 10 g of tissue, respectively, which demonstrates about a 95 % drop associated with the antenna without EBG. Furthermore, the fractal loading makes the antenna compact; EBG introduced at the underside of the monopole antenna gives a high gain-bandwidth product and disengages the human body and the antenna, making the realized antenna a potential candidate with possible seamless incorporation of specified wearable applications in WLAN standards. [ABSTRACT FROM AUTHOR]

In this paper, the joint access point (AP) association and transmission time allocation problem in densely deployed multirate WLANs based on time sharing medium access control (MAC) is considered. In our study, the centralized coordinated joint AP association and transmission time allocation problem with heterogeneous station (STA) throughput demands is first formulated as an NP-hard single non-zero programming (SNZP) optimization problem with proportionally fair (PF) throughput based objective function. To solve the NP-hard SNZP problem, two novel algorithms, the SNZP relaxation (SNZPR) algorithm and the iterative SNZPR (iSNZPR) algorithm, are proposed. The property and complexity of the proposed algorithms are analyzed. In addition, for dynamic network scenarios where there are new STAs arriving at and trying to join the network, a distributed joint admission, AP association and transmission time allocation (DAAA) algorithm is proposed to determine whether to admit a new STA arriving at the network or not. The performance of the proposed algorithms is then investigated and compared with that of some existing algorithms based on numerical results.

The developing interest in mobile services increases the demand for well-planned and cautiously managed wireless local area networks (WLAN) deployment. In WLAN, a station can access services of the network through an access point (AP) after associating with it. Any number of access points can be accessed by the station whose signal strength is available from among the APs. But practically, a WLAN station (STA) always associates with the access point with higher signal strength among the APs. In WLAN, mobile stations continuously change their location, which results in an uneven network load allocation. This uneven load dissemination prompts an extensive performance degradation of WLAN. This paper presents mathematical modeling to characterize the WLAN performance by balancing the network load and enhancing network throughput. Riverbed Modeler simulator was used to investigate the performance parameters as network load and throughput of the network. [ABSTRACT FROM AUTHOR]

High-dense deployment scenario is supposed to be the killer scenario of the future wireless networks. The next generation high efficiency wireless local area networks (WLANs) standard - IEEE 802.11ax, which will be released in the year 2019, directly faces to the high-dense deployment scenario. IEEE 802.11ax is one milestone of WLAN standardization. Thus, a series of media access control technologies are introduced in IEEE 802.11ax such as multi-user MAC (MU-MAC) enhancements, spatial reuse (SR) technology, and target wake-up time (TWT) based power saving mechanism. This paper comprehensively surveys the key technologies proposes a tutorial for IEEE 802.11ax. Some valuable insights are presented in this paper. To the best of our knowledge, this is the first work to directly investigate and analyze the latest stable version (Draft 4.0) of IEEE 802.11ax. [ABSTRACT FROM AUTHOR]

Radio over fiber (RoF) technique has revolutionized communication industry with its high data transmission rate and ability to carry the radio signal with speed of light. It finds its application in wireless local area networks (WLANs) due to easy of deployment and low cost. This paper utilizes alternate mark inversion (AMI) technique in wave length division multiplexing (WDM) scheme to further enhance data carrying capacity of the system. It is observed that proposed AMI-WDM scheme is better technique for providing high data rates and is confirmed via SNR, Q factor and eye diagrams. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) provides extremely high throughput owing to their high bandwidth utilization over higher frequencies. To compensate for the severe loss and attenuation, beamforming training is used to determine the optimal beam direction and thereby improve directional transmission power. However, the training overhead will be significantly increased with narrower beams, particularly under conventional exhaustive schemes. Therefore, we propose a learning-based adjustable beam number training (LABNT) scheme to intelligently and flexibly select beam training candidates considering different user mobility and hybrid line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. In LABNT, several deep learning networks are parallelly constructed and connected to a reinforcement learning network to determine training candidates dynamically based on performance rewards. A novel enhanced feature selection method, that is, uniformly distributed mutual information, is developed based on the correlation of historical results to select the beam inputs for each deep learning network. In simulations, the proposed LABNT outperforms other existing schemes in terms of beam alignment accuracy, training latency, and system throughput. Moreover, following the IEEE 802.11ad/ay protocols, we implement realistic mmWave beamforming training on a programmable hardware platform with integrated 60 GHz wireless-gigabit (WiGig) transceiver devices. The experimental results on the WiGig platform demonstrate that the proposed LABNT scheme can achieve real-time performance with approximately Gbps transmission throughput and millisecond-level training overhead. [ABSTRACT FROM AUTHOR]

Providing high-bandwidth and fast-speed links, wireless local area networks (WLANs) in the Terahertz (THz) band have huge potential for various bandwidth-intensive indoor applications. However, due to the specific phenomena in the THz band, including severe reflection loss, indoor blockage effects, multi-path fading, the analysis on the interference and coverage probability at a downlink is challenging. In this paper, indoor blockage effects caused by the walls and human bodies are analyzed. Next, a statistical THz channel model is proposed to characterize the THz indoor propagation. In light of these, the moment generating functions of the aggregated interference and theoretical expressions for the mean interference power are derived. As a result, the approximated coverage probability and average network throughput are derived. Extensive numerical results show that for the nearest access point (nearest-AP) user association scheme, the optimal AP density is 0.15/m2, which results in the coverage probability reaches 93% and the average network throughput is 30 Gbps/m2. In addition, by adopting a novel line-of-sight access point (LoS-AP) user association mechanism, the coverage probability and the average network throughput can be further improved by 3 percent and 2 Gbps/m2, respectively. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) systems have attracted considerable attention as a benefit of their Gbps services. Therefore, wireless-gigabit (WiGig) transmission has been developed based on the IEEE 802.11ad and 802.11ay standards of wireless local area networks (WLANs) in the 60-GHz band. To overcome the high path loss of mmWave, beamforming and beam-sector based training protocols are specified in 802.11ad/ay. With the increase in service demand, more WiGig access points (APs) will be deployed, hence the transmission frame structure of beam control should be adjustable for supporting both multiple APs and multiple users. The conventional exhaustive beam search (EBS) scheme has a potentially excessive complexity for high number of beams. Furthermore, assigning fixed training slots for users will lead to high-latency beam training under EBS. Hence, we design an advanced protocol for multiple APs and multiple users. Based on this protocol, we propose coordinated multiple AP multiuser training (CMMBT) including variable length framing and adjustable beam training. Our simulations demonstrate that CMMBT provides flexible training control and achieves the lowest training latency and highest average throughput performance amongst the state-of-the-art solutions in the open literature. [ABSTRACT FROM AUTHOR]

The IEEE 802.11ax for Wireless Local Area Network (WLAN), one of the most important wireless networks, will be released in 2020. In recent years, ultra-high definition video service and real-time applications attract increasing attention. Therefore, the next generation WLAN (beyond IEEE 802.11ax): IEEE 802.11be task group (TGbe) was formally established in 2019, which regards achieving extremely high throughput (EHT) as its core technical objective. This article investigates and analyzes the key technologies of IEEE 802.11be, and further provides our perspectives and insights on it. Specifically, this article gives a brief overview on IEEE 802.11be, including the target scenario and technical objective, key technologies overview, and the standardization process. After that, we further investigate, analyze and provide perspectives on the key technologies of IEEE 802.11be including multi-band operation, multi-AP coordination, enhanced link reliability, and latency & jitter guarantee. To the best of our knowledge, this is the first work to investigate, analyze and provide insights on IEEE 802.11be. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) in the unlicensed 60 GHz band provides extremely large spectrum utilization, which is a promising technique due to the rapid growth of wireless communication services. With wireless devices explosively increasing, the limited number of association and beamforming training (A-BFT) opportunities in conventional protocol leads to high packet collisions. In this paper, we design a novel non-slotted A-BFT frame structure for multi-users in order to alleviate packet collisions providing flexible training slots. To further reduce collision occurrence, we propose two association mechanisms including the time-based distributed coordination function (TDCF) and time-based beam collision avoidance (TBCA) schemes. The theoretical closed-forms of both TDCF and TBCA methods are also derived, and proved to outperform the random association. Furthermore, the adaptive beam search (ABS) and dynamic A-BFT adjustment (DAA) schemes are proposed to consider historical beam training information by adjusting the number of training beams and A-BFT length, respectively. Simulations are conducted to show that our proposed ABS, DAA, and TDCF/TBCA mechanisms outperform existing methods; whereas higher spectrum efficiency can be achieved by proposed non-slotted frame structure compared to conventional slotted structure. [ABSTRACT FROM AUTHOR]

Wireless local area network fingerprint-based indoor localization schemes have been widely studied because of the increasing requirements of location-based services (LBSs). The features of fingerprint based localization are known to have higher precision in indoor environments than traditional methods, such as triangulation. However, the precision depends on the amount of pre-created received signal strength (RSS) fingerprints, which is associated with the number of reference points (RPs) of the RSS measurements and the available signal sources in the environment. In this paper, we consider the resource limitations of todays' wireless environment and propose an improved fingerprint-based localization approach that adapts a path loss model for fingerprint creation and localization. Based on the proposed approach, we present two related localization schemes. The first is a path-loss-based fingerprint localization (PFL) scheme and the second is a dual-scanned fingerprint localization (DFL) scheme. The PFL attempts to improve positioning precision, and the DFL attempts to guarantee positioning reliability. Several simulations are performed, and they show that the proposed schemes improve the positioning precision and reliability in resource-limited environments, which would improve the practicability of fingerprint-based localizations in indoor LBSs.

The dependence of Round Trip Time (RTT) on Signal to Noise Ratio (SNR) for multiple users in an IEEE 802.11b Wireless Local Area Network (WLAN) was studied in this work. Data collected in open corridor, small offices and free space environments in an infrastructure based network (where different quality of service traffic were continuously being sent by multiple users) was used to develop and validate Multiple User RTT models predicted from computed SNR.The models were also compared with single user models earlier developed. The tests results show that for multiple users on the network, RTT can be predicted from the computed SNR with reasonable accuracy as the models passed the F and T test at 0.1% level of significance and RMS errors of less than 867.378214ms were observed. During network design and installation, these models provide useful tools that can enable IEEE 802.11b WLAN installers to make fast and better informed RTT decisions. Keywords: Round trip time, Signal to noise ratio, empirical models, Wireless Local Area Networks

The performance of Wireless Local Area Network (WLAN) is highly dependent on the processes that are implemented in the Medium Access Control (MAC) sublayer regulated by the IEEE 802.11 standard. In turn, various parameters affect the performance of the MAC sublayer, the most important of which is the number of stations in the network and the offered load. With the massive growth of multimedia traffic, research of the network performance depending on traffic types is relevant. In this paper, we present the impact of a high-/low-priority traffic ratio on WLAN performance with different numbers of access categories. The simulation results show different impact of high-/low-priority traffic ratio on the performance of the MAC sublayer of wireless LANs depending on different network-sizes and on network conditions. Performance of the large network with two access categories and with the prevalent high-priority traffic is significantly higher than in the case of using four categories on the MAC sublayer. This allows us to conclude that the performance improvement of the large network with the prevalent high-priority traffic can be achieved by an adaptive adjustment of the access categories number on the MAC sublayer.

With the ever-increasing demand for wireless traffic and quality of services (QoS), wireless local area networks (WLANs) have developed into one of the most dominant wireless networks that fully influence human life. As the most widely used WLANs standard, IEEE 802.11 will release the upcoming next generation WLANs standard amendment: IEEE 802.11ax. Thus, this article briefly surveys the key technologies of IEEE 802.11ax. Furthermore, performance requirements of IEEE 802.11ax are evaluated via a proposed systems and link-level integrated simulation platform (SLISP). Simulations results confirm that IEEE 802.11ax significantly improves the user experience in high-density deployment, while successfully achieves the average per user throughput requirement in project authorization request (PAR) of IEEE 802.11ax by four times compared to the legacy IEEE 802.11. To the best of our knowledge, this article is the first work to thoroughly and deeply evaluate the compliance of the performance requirements of IEEE 802.11ax. [ABSTRACT FROM AUTHOR]

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The existing medium access control (MAC) protocols are not able to utilize the full opportunities from power-domain non-orthogonal multiple access (NOMA) technique in wireless local area networks (WLANs). In this paper, we propose a carrier sense multiple access (CSMA) MAC protocol to increase downlink throughput by utilizing the opportunities offered by NOMA technique in downlink access of WLANs. For downlink transmission, an algorithm is developed to select an optimal user-set with appropriate power allocation from a randomly selected user-set. We then develop an analytical model to compute the uplink and downlink throughputs of a WLAN under the proposed MAC protocol by modelling the WLAN system as a discrete time Markov chain. The uplink and downlink throughputs of a WLAN under the proposed MAC protocol are determined by means of the analytical model and the accuracy of the analytical model is verified via extensive simulation. It is demonstrated that the proposed NOMA based MAC protocol improves the downlink throughput significantly compared to an orthogonal multiple access (OMA) based traditional CSMA MAC protocol without reducing the uplink throughput considerably. For a reasonable configuration, the downlink throughput gain is found to be more than 250%. We also study the throughput performance of the proposed MAC protocol for different transmit power levels, user medium access rates, data rates, path loss exponents and number of users in WLAN. We find that the throughput gain obtained by the proposed MAC protocol increases with increasing the transmit power and decreases with increasing the data rates and path loss. However, the change in the throughput gain obtained by the proposed MAC protocol is not significant for increasing the number of users and the user medium access rate. [ABSTRACT FROM AUTHOR]

The signal intensity based wireless terminal access mechanism is the key cause of imbalanced load of WLAN. In the environment where users are densely packed, such as banks, office buildings and malls, load imbalance will severely decrease the quality and source utility rate of WLAN, thus the node load balance strategy becomes increasingly in demand to solve the problem. First, this paper studied the mainstream node load balance technologies and proposed an evaluation model which identifies and measures the level of load; next, the load level gain calculation model was designed and the prediction-based load balance and resource adjustment strategy was put forward; at last, the load balance mechanism ST-WLB was enabled and the test result shows that it can improve the performance by 10% without excessive costs. [ABSTRACT FROM AUTHOR]

The dependence of Round Trip Time (RTT) on Signal to Noise Ratio (SNR) for multiple users in an IEEE 802.11b Wireless Local Area Network (WLAN) was studied in this work. Data collected in open corridor, small offices and free space environments in an infrastructure based network (where different quality of service traffic were continuously being sent by multiple users) was used to develop and validate Multiple User RTT models predicted from computed SNR. The models were also compared with single user models earlier developed. The tests results show that for multiple users on the network, RTT can be predicted from the computed SNR with reasonable accuracy as the models passed the F and T test at 0.1% level of significance and RMS errors of less than 867.378214ms were observed. During network design and installation, these models provide useful tools that can enable IEEE 802.11b WLAN installers to make fast and better informed RTT decisions. [ABSTRACT FROM AUTHOR]

Due to the uplink-centric characteristic of diverse Internet of things (IoT) applications, the wireless connectivity for the IoT should provide a sufficient data rate for the delivery of a huge amount of data traffic toward the uplink direction; furthermore, it needs to satisfy the low complexity and high energy efficiency for the deployment of resource-constrained IoT devices. To this end, we propose an IoT uplink multiple-input and multiple-output (MIMO) scheduling scheme (IoT-UL-MIMO) for which a multi-user (MU)-MIMO capability is implemented in the IoT-gateway device to greatly extend the uplink bandwidth and support the massive data delivery from a plurality of devices toward the gateway. In the IoT-UL-MIMO, a simple user-selection process that selects a proper set of transmitters by just counting the number of successful control-frame transmissions from the devices is used without a channel-sensing mechanism. The aim of this design principle is a mitigation of the system complexity that reduces the energy consumption, which is a key consideration for resource-constrained IoT devices. The simulation results show significant improvements for the throughput and energy efficiency of IoT-UL-MIMO. A duration-length optimization regarding the uplink scheduling phase is also discussed in this paper. [ABSTRACT FROM AUTHOR]

A large number of access points (APs) may be required to provide network coverage in a given environment. However, a non-optimized deployment of these APs can reduce the network performance significantly due to the excessive interference. The optimization of the channel and transmit power is an efficient method to reduce the interference and therefore guarantee a minimally acceptable performance. In this paper, we propose a heuristic algorithm to find a proper channel and transmit power configuration for all APs within a network. The algorithm evaluates the network, using theoretical models, and employs several techniques to optimize the channel and the transmit power to increase the network performance. We also estimate the complexity of the proposed algorithm comparing it with an exhaustive search approach. The results show that the proposed algorithm can arrive at a solution very close to the optimal with a much reduced computational complexity. [ABSTRACT FROM AUTHOR]

Large databases with Received Signal Strength (RSS) measurements are essential for various use cases in mobile wireless communications and navigation, including radio resource management algorithms and network-based localization. Because of the constantly increasing number of radio transmitters with various wireless technologies and with the advent of 5G cloud computing and Internet of Things (IoT), the required size of the RSS databases are becoming unmanageably large. Thus, the requirements for the bandwidth and data rates for accessing the memory might become too costly. Therefore, in order to reduce the size of the RSS database, while maintaining the data quality, we have previously proposed the method of spectrally compressed RSS images, which are able to achieve considerable data compression of up to 70 percent. In this paper, we deeply analyze the process of spectral compression and introduce error sources, which affect the compression performance. Based on the analysis, we propose a novel theoretical framework and methods to optimize the performance of the spectral compression. In addition, we derive the Cramér-Rao Lower Bound (CRLB) for the RSS-based localization error and compare the CRLB between separate baseline localization approaches. The theoretical analysis is justified and compared with experimental RSS measurements taken from several multi-storey buildings. [ABSTRACT FROM PUBLISHER]

A wireless local area network (WLAN) is an important type of wireless network which connotes different wireless nodes in a local area network. Network traffic or data traffic in a WLAN is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's network traffic is the main component for network traffic measurement, network traffic control, and simulation. In addition, traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications, such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows one to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to identify and organize network traffic, which is an important key for improving the QoS feature. In this paper, a new architecture based on the following algorithms is presented for improving the QoS feature in a wireless local area network: (1) Real-Time Network Traffic Classification (RTNTC) algorithm for WLANs based on Compressed Sensing (CS); (2) Real-Time Network Traffic Monitoring (RTNTM) approach based on CS. This architecture enables continuous data acquisition and compression of WLAN's signals that are suitable for a variety of other wireless networking applications. At the transmitter side of each wireless node, an analog CS framework is applied at the sensing step before an analog to digital converter in order to generate the compressed version of the input signal. At the receiver side of the wireless node, a reconstruction algorithm is applied in order to reconstruct the original signals from the compressed signals with high probability and enough accuracy. The proposed architecture allows reducing Data Delay Probability (DDP) to 15%, Bit Error Rate (BER) to 14% at each wireless node, False Detection Rate (FDR) to 25%, and Packet Delay (PD) to 15%, which are good records for WLANs. The proposed architecture is increased Data Throughput (DT) to 22% and Signal to Noise (S/N) ratio to 17%, and 10% accuracy of wireless transmission. The proposed algorithm outperforms existing algorithms by achieving a good level of Quality of Service (QoS), which provides a good background for establishing high quality wireless local area networks. [ABSTRACT FROM AUTHOR]

In the past, WLAN planning was coverage driven to ensure that the signal quality is satisfied in all targeted areas. As the number of users with more high-throughput applications, supported by sophisticated mobile computing devices, continues to grow rapidly on the one hand and on the other hand the new high-speed IEEE802.11 based WLANs continue to have a significant wireless communication market spread, it has been recognized that capacity is equally important as coverage for the WLAN planning. In this paper WLANs capacity planning and performance evaluation focusing on the impact of the applications throughput requirements, high-speed IEEE802.11 WLAN standards and user terminal capabilities are discussed. To investigate the impact of the high-speed WLANs and user terminal capabilities on the network throughput, performance evaluation is carried out by means of measurements, using IEEE 802.11ac and IEEE 802.11n standards. [ABSTRACT FROM AUTHOR]

This paper presents a wireless local area network (WLAN) spectrum control system that uses active frequency selective shielding walls to selectively reduce or pass WLAN signals in the 5 GHz band indoors. The proposed system utilizes a well-known active frequency selective structure based on a rectangular loop with PIN diodes and is thus capable of either reducing or passing the WLAN frequency by using the on/off switching of the PIN diode based on the measured electric field strength in indoor. We designed and simulated the proposed active frequency selective shielding wallpaper by using commercial electromagnetic simulation software and confirmed that the proposed structure can reduce the WLAN signal by switching the PIN diode by applying the manufactured prototype on the exterior of an experimental apparatus containing a WLAN receiver antenna that is capable of measuring the received electric field strength. Extension of the results presented herein can be applied to reduce the wireless signal to enhance the spectrum efficiency of an indoor space. [ABSTRACT FROM AUTHOR]

In this paper, Synchronized Contention Window Full-Duplex (S-CW FD) protocol is presented as a medium access control (MAC) protocol that enables full-duplex (FD) in wireless local area networks (WLANs), while seamlessly operating together with legacy nodes. For performance analysis, a Markov chain model of S-CW FD is devised, using this model, the saturated throughput of S-CW FD is derived and the results are validated by comparisons with OPNET simulations. Later, through detailed simulations, S-CW FD is evaluated against standard half-duplex IEEE 802.11, considering realistic self-interference and channel models and the effect of hidden nodes. It is shown that S-CW FD MAC protocol can double the throughput of standard half duplex IEEE 802.11 without hidden nodes in the network, and its improvement can get as high as ten fold in the presence of hidden nodes. In this work, S-CW FD is also compared to two similar contention based FD MAC protocols from the literature, and it is shown that, under typical network loads, S-CW FD outperforms those protocols by up to 30%, despite much lower complexity. Overall, S-CW FD stands out as a promising candidate for implementing FD in WLANs due to significant performance improvements, simplicity and flexibility for application in different FD modes to support bidirectional, relaying and cellular scenarios. [ABSTRACT FROM AUTHOR]

As the low frequency band has become more and more crowded, millimeter-wave (mmWave) has attracted significant attention. The IEEE has released the 802.11ad standard to satisfy the demand of ultra-high-speed communication. It adopts beamforming technology that can generate directional beams to compensate for high path loss. In the association beamforming training (A-BFT) phase of BF training, a station (STA) randomly selects an A-BFT slot to contend for training opportunity. Due to the limited number of A-BFT slots, the A-BFT phase suffers high probability of collisions in dense user scenarios, resulting in inefficient training performance. Based on the evaluation of the IEEE 802.11ad standard and 802.11ay draft in dense user scenarios of mmWave wireless networks, we propose an enhanced A-BFT beam training and random access mechanism, including the separated A-BFT (SA-BFT) and secondary backoff A-BFT (SBA-BFT). The SA-BFT can provide more A-BFT slots and divide the A-BFT slots into two regions by defining a new E-A-BFT Length field compared with the legacy 802.11ad A-BFT, thereby maintaining compatibility when 802.11ay devices are mixed with 802.11ad devices. It can also greatly reduce the collision probability in dense user scenarios. The SBA-BFT performs secondary backoff with very small overhead of transmission opportunities within one A-BFT slot, which not only further reduces collision probability, but also improves the A-BFT slots utilization. Furthermore, we propose a 3-D Markov model to analyze the performance of the SBA-BFT. The analytical and simulation results show that both the SA-BFT and the SBA-BFT can significantly improve BF training efficiency, which is beneficial to the optimization design of dense user wireless networks based on the IEEE 802.11ay standard and mmWave technology. [ABSTRACT FROM PUBLISHER]

IEEE 802.11e has been introduced to support quality of service (QoS) in WLANs by allocating different traffics to four access categories. Cross-layer design is a method to improve the transmission quality of multimedia over wireless networks. However, when the fragmented packets of a single frame are allocated to different AC queues, out-of-order delivery may occur. Then the receiving node requires more buffer space to absorb the out-of-order packets. Therefore, even with a significance classification mechanism, the quality of the video transmission may still be limited due to the occurrence of out-of-order delivery and the transmission of information that becomes useless to the receiver. Therefore, this work developed a novel mapping mechanism (NMM) to improving the quality of MPEG-4 video delivery over IEEE 802.11e networks. The NMM considers the action that was taken on packet of the video frame that had been previously transmitted to resolve the out-of-order delivery by allocating them to the same AC queue as the previously process if possible. Furthermore, the proposed mechanism NMM takes more aggressive scheme to protect more important frame packets from being dropped. In order to evaluate the quality of MPEG-4 video delivery over IEEE 802.11e networks by the proposed mechanism, this work adopted two evaluation metrics, which is called Peak to Signal Noise Ratio (PSNR) and the ratio of frames loss. The simulation results demonstrate that, in terms of both PSNR and the ratio of frames loss, the proposed scheme outperforms exiting schemes such as EDCA (Enhanced Distributed Channel Access) and adaptive mapping. [ABSTRACT FROM AUTHOR]

A wireless local area network (WLAN) is an important type of wireless network which connotes different wireless nodes in a local area network. Network traffic or data traffic in a WLAN is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN’s network traffic is the main component for network traffic measurement, network traffic control, and simulation. In addition, traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications, such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows one to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to identify and organize network traffic, which is an important key for improving the QoS feature. In this paper, a new architecture based on the following algorithms is presented for improving the QoS feature in a wireless local area network: (1) Real-Time Network Traffic Classification (RTNTC) algorithm for WLANs based on Compressed Sensing (CS); (2) Real-Time Network Traffic Monitoring (RTNTM) approach based on CS. This architecture enables continuous data acquisition and compression of WLAN’s signals that are suitable for a variety of other wireless networking applications. At the transmitter side of each wireless node, an analog CS framework is applied at the sensing step before an analog to digital converter in order to generate the compressed version of the input signal. At the receiver side of the wireless node, a reconstruction algorithm is applied in order to reconstruct the original signals from the compressed signals with high probability and enough accuracy. The proposed architecture allows reducing Data Delay Probability (DDP) to 15%, Bit Error Rate (BER) to 14% at each wireless node, False Detection Rate (FDR) to 25%, and Packet Delay (PD) to 15%, which are good records for WLANs. The proposed architecture is increased Data Throughput (DT) to 22% and Signal to Noise (S/N) ratio to 17%, and 10% accuracy of wireless transmission. The proposed algorithm outperforms existing algorithms by achieving a good level of Quality of Service (QoS), which provides a good background for establishing high quality wireless local area networks.

This paper investigates the user grouping problem of downlink wireless local area networks (WLANs) with multi-user MIMO (MU-MIMO). Particularly, we focus on the problem of whether single user transmit beamforming (SU-TxBF) or MU-MIMO should be utilized, and how many users and which users should be in a multi-user (MU) group. We formulate the problem for maximizing the system throughput subject to the multi-user air time fairness (MU-ATF) criterion. We show that hypergraphs provide a suitable mathematical model and effective tool for finding the optimal or close to optimal solution. We show that the optimal grouping problem can be solved efficiently for the case where only SU-TxBF and 2-user MU groups are allowed in the system. For the general case, where any number of users can be assigned to groups of different sizes, we develop an efficient graph matching algorithm (GMA) based on graph theory principles. We evaluate the proposed algorithm in terms of system throughput using an 802.11ac emulator, which is created using collected channel measurements from an indoor environment and simulated channel samples for outdoor scenarios. We show that our GMA achieves at least 93% of the optimal system throughput in all considered test cases. [ABSTRACT FROM AUTHOR]

Increased co-channel interference (CCI) in wireless local area networks (WLANs) is bringing serious resource constraints to today’s high-density wireless environments. CCI in IEEE 802.11-based networks is inevitable due to the nature of the carrier sensing mechanism however can be reduced by resource optimization approaches. That means the CCI analysis is basic, but also crucial for an efficient resource management. In this article, we present a novel CCI analysis approach based on the queuing theory, which considers the randomness of end users’ behavior and the irregularity and complexity of network traffic in high-density WLANs that adopts the M/M/c queuing model for CCI analysis. Most of the CCIs occur when multiple networks overlap and trigger channel contentions; therefore, we use the ratio of signal-overlapped areas to signal coverage as a probabilistic factor to the queuing model to analyze the CCI impacts in highly overlapped WLANs. With the queuing model, we perform simulations to see how the CCI influences the quality of service (QoS) in high-density WLANs. [ABSTRACT FROM AUTHOR]