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The tremendous number of devices involved in the Internet of Things is bringing new challenges to wireless networking. The more devices that transmit in a wireless network, the higher the contention for the channel. The novel Wi-Fi HaLow standard introduces a new channel access mechanism called the Periodic Restricted Access Window (PRAW), which aims to reduce this contention. With this mechanism, an access point can define a series of time intervals during which only a predefined group of stations can transmit data while the other stations are forbidden to access the channel. Unfortunately, the standard does not suggest how to configure the PRAW mechanism according to scenario-specific requirements and restrictions. Many Internet of Things scenarios require the fast and low energy consumption delivery of measurement data from wireless sensors while saving channel resources for other stations that transmit, for example, multimedia traffic. Therefore, this paper studies the problem of the minimization of the channel timeshare consumed by the PRAW with restrictions on the average delay and power consumption. To solve the problem and configure the PRAW optimally, a novel analytical model is developed. The key feature of the model is the consideration of the case of short PRAW slots that allow the computational complexity to be reduced and high accuracy to be achieved. These properties make the model suitable for implementation in real devices.

With the massive integration of distributed renewable energy sources (RESs) into the power system, the demand for timely and reliable network quality monitoring, control, and fault analysis is rapidly growing. Following the successful deployment of Phasor Measurement Units (PMUs) in transmission systems for power monitoring, a new opportunity to utilize PMU measurement data for power quality assessment in distribution grid systems is emerging. The main problem however, is that a distribution grid system does not normally have the support of an infrastructure network. Therefore, the main objective in this paper is to develop a Machine-to-Machine (M2M) communication network that can support wide ranging sensory data, including high rate synchrophasor data for real-time communication. In particular, we evaluate the suitability of the emerging IEEE 802.11ah standard by exploiting its important features, such as classifying the power grid sensory data into different categories according to their traffic characteristics. For performance evaluation we use our hardware in the loop grid communication network testbed to access the performance of the network.

A 1.3 nJ/b IEEE 802.11ah TX for IoT applications is presented. A fully-digital polar architecture consisting of an all-digital PLL-based frequency modulator and an AM-retiming $\Delta \Sigma $ switched-capacitor PA (SC-PA) achieves more than $10\times $ power reduction than state-of-the-art OFDM TXs. Several circuit-design techniques such as LSB truncation error feedback are proposed to efficiently pre-process the AM/PM data to improve the TX performance. A design approach of the SC-PA for optimum overall efficiency is introduced. The PLL spur level is reduced to 55 dBc by a switched-capacitor based digital-to-time converter. A dynamic divider is implemented together with a 1.8 GHz oscillator for efficient LO generation. Fabricated in a 40 nm CMOS process, this TX fulfills all the IEEE 802.11ah mandatory-mode PHY requirements with 4.4% EVM and > 4.8 dB spectral mask margin, while consuming 7.1 mW from a 1 V supply when delivering 0 dBm output power.

A new IEEE standard for large-scale wireless connectivity in IoT and M2M applications, called IEEE 802.11ah, has recently been introduced. A single access point (AP) of 802.11ah can provide connectivity to a large number of devices (up to 8192) with the communication range of up to 1źkm. Due to such a large coverage area with a large number of connected devices, however, the hidden node problem of 802.11ah networks is severer than typical Wi-Fi networks. Especially, we observe that frequent occurrences of a collision chain results in significant deterioration of network performance even with the group-based access restriction mechanism of 802.11ah. To solve this problem, we propose a collision chain mitigation scheme that detects and interrupts a collision chain, lets a smaller number of devices contend thereafter and also provide the information from which a carrier-sensitivity table is constructed by AP. Although the proposed scheme mitigates performance deterioration due to a collision chain when occurred, collision chains still occur. So, we propose a grouping algorithm which can perform both initial grouping and regrouping from existing groups based on the carrier-sensitivity table constructed by the mitigation scheme so that only a negligible number of hidden devices remain in each group and the root cause of collision chain is obviated. Our simulation study shows that the mitigation scheme alone makes network throughput comparable to the case of no hidden devices and its combination with the grouping algorithm improves throughput performance over the 8-group case of the conventional mechanism by up to 146%.

Utilization of flying platforms like Unmanned Aerial Vehicles (UAVs) is progressively increasing in our daily lives. Key characteristics such as flexibility, mobility and adaptive altitude, make UAVs particularly suitable for application in areas such as crop management, goods delivery, public safety and real-time video surveillance of public places to assist in terrestrial networks. IEEE 802.11ah is a WiFi brand Internet of Things (IoT) technology, with properties of suitable data rates, flexibility in channelization, Multi Input Multi Output (MIMO) capability and low power consumption etc. Compared to the existing wireless technologies, IEEE 802.11ah is a suitable choice in terms of data rate and performance. In this research, MultiCode (MC) MultiCarrier (MC) Code Division Multiple Access (CDMA) is incorporated in the Physical (PHY) layer of IEEE 802.11ah to meet the differential requirements of range and throughput of UAV to UAV and UAV to Ground Control Station (GCS) communication links for UAV swarm. Depending upon the nature of data transmitted between the UAVs and GCS, suitable Modulation and Coding Schemes (MCS) are selected for multiple bandwidths. Performance analysis of MC–MC CDMA in IEEE 802.11ah has been performed in Additive White Gaussian Noise (AWGN). It has been observed that an increase/decrease in the modulation order directly affects data rate, with a compromised performance at higher modulation order.

The IEEE 802.11ah standard relies on the conventional distributed coordination function (DCF) as a backoff selection method. The DCF is utilized in the contention-based period of the newly introduced medium access control (MAC) mechanism, namely restricted access window (RAW). Despite various advantages of RAW, DCF still utilizes the legacy binary exponential backoff (BEB) algorithm, which suffers from a crucial disadvantage of being prone to high probability of collisions with high number of contending stations. To mitigate this issue, this paper investigates the possibility of replacing the existing exponential sequence (i.e., as in BEB) with a better pseudorandom sequence of integers. In particular, a new backoff algorithm, namely Pseudorandom Sequence Contention Algorithm (PRSCA) is proposed to update the CW size and minimize the collision probability. In addition, the proposed PRSCA incorporates a different approach of CW freezing mechanism and backoff stage reset process. An analytical model is derived for the proposed PRSCA and presented through a discrete 2-D Markov chain model. Performance evaluation demonstrates the efficiency of the proposed PRSCA in reducing collision probability and improving saturation throughput, network throughput, and access delay performance.

This paper presents a discrete-time Markov model for the operation of a station in a single-hop IEEE 802.11ah network under saturated traffic and ideal channel conditions. In the proposed model, each beacon interval has only one RAW group that is further divided into a number of RAW slots to which stations are evenly assigned with equal priority. A novel feature in the model is the consideration of the event of RAW slot completion time using a specific probability. Two empirical expressions for this probability are proposed, and we study the average aggregate throughput for various numbers of RAW slots and stations in the network. Numerical results derived from the analytical model show similar behavior to those obtained with an IEEE 802.11ah model available for the ns-3 simulator.

IEEE 802.11ah, which is also called WiFi HaLow, is considered to be a promising protocol for Internet of Things (IoT). The legacy 802.11ah proposes a number of grouping mechanisms, which are based on the hierarchical organization, to relieve channel access’s collision in the IoT’s communication environment. However, the legacy 802.11ah still cannot effectively avoid collisions in a crowded environment. This work proposed the Registration-based Collision Avoidance (RCA) mechanism to avoid collisions and furthermore reduce the waiting time of backoff. The RCA mechanism lets the AP know the network situation in advance and then schedule stations to avoid collision. Comparing with the legacy 802.11ah, experimental results shown that the proposed RCA mechanism has the lower collision rate and better throughput when the number of stations in a time slot is high.

The Restricted Access Window (RAW) mechanism proposed by IEEE 802.11ah promises to address one of the major problems of the Internet of Things (IoT): high channel contention in large-scale densely deployed sensor networks. The RAW feature allows the Access Point (AP) to divide stations into different groups, with only the stations in the same group being allowed to access the channel simultaneously. Existing station grouping strategies only support homogeneous scenarios, where all sensor stations have the same fixed data transmission interval, modulation and coding scheme (MCS) and packet size. In this paper, we present two contributions to address this issue. First, we propose a surrogate modeling methodology to predict RAW performance for both throughput and energy efficiency given specific network conditions and RAW configuration parameters. The models are fast to train and can be solved in real-time. Second, we extend the original version of Model-Based RAW Optimization Algorithm (MoROA) which only focused on throughput. The extended MoROA uses the surrogate models to determine the optimal RAW configuration for both throughput and energy efficiency in real-time through multi-objective optimization. We compare the accuracy of our surrogate model to simulation results. Performance of MoROA is compared to existing RAW optimization algorithms and traditional 802.11 channel access methods. The results show that the trained surrogate models can accurately predict RAW performance with a relative error less than 7% and 10% for 90% and 95% of the RAW configurations respectively. Compare to the traditional 802.11 channel access functions, by using the objective weight and assigning stations into homogeneous groups, MoROA achieves either 65% higher throughput, or 96% less energy consumption, or a weighted solution in between, in dense heterogeneous networks. (C) 2019 Elsevier B.V. All rights reserved.

Wi-Fi was originally designed to provide broadband wireless Internet access for devices which generate rather heavy streams. And Wi-Fi succeeded. The coming revolution of the Internet of Things with myriads of autonomous devices and machine type communications (MTC) traffic raises a question: can the Wi-Fi success story be repeated in the area of MTC? Started in 2010, IEEE 802.11 Task Group ah (TGah) has developed a draft amendment to the IEEE 802.11 standard, adapting Wi-Fi for MTC requirements. The performance of novel channel access enhancements in MTC scenarios can hardly be studied with models from Bianchi's clan, which typically assume that traffic load does not change with time. This paper contributes with a pioneer analytical approach to study Wi-Fi-based MTC, which can be used to investigate and customize many mechanisms developed by TGah.

The recent Wi-Fi HaLow technology focuses on adopting Wi-Fi for the needs of the Internet of Things. A key feature of Wi-Fi HaLow is the Restricted Access Window (RAW) mechanism that allows an access point to divide the sensors into groups and to assign each group to an exclusively reserved time interval where only the stations of a particular group can transmit. In this work, we study how to optimally configure RAW in a scenario with a high number of energy harvesting sensor devices. For such a scenario, we consider a problem of device grouping and develop a model of data transmission, which takes into account the peculiarities of channel access and the fact that the devices can run out of energy within the allocated intervals. We show how to use the developed model in order to determine the optimal duration of RAW intervals and the optimal number of groups that provide the required probability of data delivery and minimize the amount of consumed channel resources. The numerical results show that the optimal RAW configuration can reduce the amount of consumed channel resources by almost 50%.

The growth of Wireless Fidelity (WiFi) technology is so rapid and popular. The technology most widely used for WiFi services is the IEEE 802.11 family of standards. To support the Internet of Things (IoT) era, 802.11ah standard technology has developed, and the standard is intended to provide a low-cost mode of operation, with a wider coverage area, and can support thousands of devices per cell. This paper discusses IEEE 802.11ah Standard Network Planning for the Internet of Things Application (Case Study: Smart Meter Using WiFi.id Network in Bandung), to improve network quality in terms of coverage and capacity to improve the efficiency of the WiFi network and so that it can supports the Internet of Things (IoT) service. Network planning using 802.11ah for the internet of things application with a smart meter case study using the WiFi.id network has been successfully carried out. To cover the entire area of Bandung, 23 sites are required. In the capacity, the Tx slots needed to cover possible smart meters for each site are only 9 tx slots out of a total of 100 tx slots.

A great number of Internet of Things (IoT) and machine-to-machine (M2M) based applications require energy efficient, long range and low data rate wireless communication links. In order to offer a competitive solution in these areas, IEEE 802.11 standardization group has defined the "ah" amendment, the first sub-1GHz WLAN standard, with flexible channel bandwidths, starting from 1MHz, up to 16MHz, and many other physical and link layer improvements, enabling long-range and energy efficient communications. However, for some regions, like Europe, the maximum transmitted power in dedicated frequency band is limited to only 10mW, thus disabling the achievement of ranges which would be close to targeted of up to 1km. In this paper we examine possibilities for range extension through implementation of half-duplex decode-and forward (DF) relay station (RS) in communication between an access point (AP) and an end-station (ST). Assuming a Rician fading channel between AP and RS, and a Rayleigh fading channel on the RS-ST link, we analytically derive results on achievable ranges for the most robust modulation and coding schemes (MCSs). Analyses are performed for two different standard adopted deployment scenarios on the RS-ST link. Moreover, we have analyzed whether the considered most robust MCSs, known for supporting the longest range, but the lowest data rates, can meet the defined requirement of at least 100kb/s for the greatest attainable AP-RS-ST distances. We examine data rate enhancements, brought by coding and using of short packets, for both downlink (DL) and uplink (UL). Finally, we present bit error rate (BER) results, obtained through simulations of a dual-hop DF IEEE 802.11ah relay system for the considered MCs. All presented results confirm that IEEE 802.11ah systems, through deployment of relay stations, become an interesting solution for M2M and IoT based applications.

IEEE 802.11ah protocol is specifically designed to provide network connectivity to a large number of energy efficient heterogeneous internet of things (IoT) devices. Restricted access window (RAW) mechanism of the protocol is an innovative feature which aims at reducing medium access contention by slotting the beacon interval and allowing limited number of nodes to contend in a specific slot. In this paper, we evaluate important medium access control (MAC) layer performance metrics of differentiated quality of service (QoS) heterogeneous IoT nodes in IEEE 802.11ah RAW mechanism. Our analysis evaluates the feasibility of coexistence of priority and non-priority traffic in IoT devices without degrading network performance.

Recent advancements in wireless technology has led to the development of large number of Machine-to- Machine (M2M) and Internet of Things (IOT) applications, with the fastest foreseen growth rate in coming years. The key functional requirements include long range, energy efficiency and suitable data rates. To provide a better solution compared to existing wireless technologies, IEEE 802.11ah HaLow was standardized by making amendments to IEEE 802.11 in 2016. It is a sub 1 GHz IOT Brand WiFi Technology with the capability of multiple band multimode of operation , improved physical and link layer, longer transmission range, energy conserving mechanisms and operability of up to 4 spatial streams. However, an in-depth performance analysis of this standard needs to be further investigated. This work provides BER and Effective throughput analysis of IEEE 802.11ah for various modes of operation. The presented analysis is helpful for the development of adaptive modulation & coding to include link adaptation in this standard.

To implement the new restricted access window (RAW) medium access control mechanism in IEEE 802.11ah, stations (STAs) must be assigned to RAW slots based on their association IDs (AIDs). In this paper, we first identify the fixed subgroup problem with the current round-robin slot assignment. To address it, a novel AID shuffle mechanism is proposed for each STA to distributedly find a different and distinct temporary AID in each RAW. Each STA then reuses the round-robin slot assignment with its temporary AID. As a result, the set of STAs assigned to each subgroup/slot are randomized, yet with the same subgroup size. Simulation results show that the transmission fairness problem with the original round-robin assignment is solved and the system throughput is also improved.

Wireless communication has gained significant importance in industrial automation due to the ease of deployment and the low cost of components. Among the wireless standards, IEEE 802.11ah is able to provide long-range (1 km), low power communication and high degree of scalability communication, which makes it a good candidate for industrial real-time applications. Having spotted the advantages of the triggered Restricted Access Window (RAW) mode in IEEE 802.11ah, this paper intends to evaluate the real-time performance of the RAW mode. This paper first presents a detailed introduction of IEEE 802.11ah RAW mechanism, especially triggered RAW mode. Then, a simple analytical model is proposed to describe how to determine a set of proper values of RAW parameters to fulfil the requirements of a specified industrial real-time application. Additionally, we investigated the performance of the triggered RAW mechanism when adopting in industrial applications by simulation. The results show the number of the station groups, the number of the RAW slots and the duration of the RAW slots all have significant influence on the real-time performance of the network. When the number of the station groups and the number of the RAW slots keep increasing, the deadline miss ratio of the network will drop from 100% to 0%, which significantly improves the network real-time performance.

IEEE 802.11ah protocol aims at providing network connectivity to a large number of end points while maintaining a satisfactory network performance. The RAW scheme of MAC access technique enables STAs to contend in different RAW slots and thereby reducing the chance of collision. In this paper we evaluate the performance metrics of the RAW scheme and observe that RAW scheme may be suitable for very small traffic condition. At higher traffic load, some of the nodes need to wait longer to transmit packets and network becomes unstable very quickly as the traffic for each node is increased beyond two packets per second in our test condition. The highest normalized network throughput achieved in this network is around 40%. Some important performance metrics like idle probability, backoff time and transmission probability are evaluated and studied in detail in this paper.

The recent advances in Internet of Things (IoT) have led to numerous emerging applications ranging from eHealthcare to industrial control, which often demand stringent Quality of Service (QoS) requirements such as low-latency and high system reliability. However, the ever-increasing number of connected devices in ultra-dense IoT networks and the dynamic traffic patterns increase the channel access delay and packet collision rate. In this regard, this paper proposes a sector-based device grouping scheme for fast and efficient channel access in IEEE 802.11ah based IoT networks such that the total number of the connected devices within each sector is dramatically reduced. In the proposed framework, the Access Point (AP) divides its coverage area into different sectors, and then each sector is further divided into distinct groups based on the number of devices and their location information available from the cloud-center. Subsequently, individual groups within a sector are assigned to specific Random Access Window (RAW) slots, and the devices within distinct groups in different sectors access the allocated RAW slots by employing a spatial orthogonal access mechanism. The performance of the proposed sectorized device grouping scheme has been analyzed in terms of system delay and network throughput. Our simulation results show that the proposed scheme can significantly enhance the network throughput while simultaneously decreasing the system delay as compared to the conventional Distributed Coordination Function (DCF) and IEEE 802.11ah grouping scheme.

The proliferation of Internet-of-Things (IoT) technology and its reliance on the license-free Industrial, Scientific, and Medical (ISM) bands have rendered radio spectrum scarce. The IoT can nevertheless obtain great advantage from Cognitive Radio (CR) technology for efficient use of a spectrum, to be implemented in IEEE 802.11af-based primary networks. However, such networks require a geolocation database and a centralized architecture to communicate white space information on channels. On the other hand, in spectrum sensing, CR presents various challenges such as the Hidden Primary Terminal (HPT) problem. To this end, we focus on the most recently released standard, i.e., IEEE 802.11ah, in which IoT stations can first be classified into multiple groups to reduce collisions and then they can periodically access the channel. Therein, both services are similarly supported by a centralized server that requires signaling overhead to control the groups of stations. In addition, more regroupings are required over time due to the frequent variations in the number of participating stations, which leads to more overhead. In this paper, we propose a new Multiple Access Control (MAC) protocol for CR-based IEEE 802.11ah systems, called Restricted Access with Collision and Interference Resolution (RACIR). We introduce a decentralized group split algorithm that distributes the participating stations into multiple groups based on a probabilistic estimation in order to resolve collisions. Furthermore, we propose a decentralized channel access procedure that avoids the HPT problem and resolves interference with the incumbent receiver. We analyze the performance of our proposed MAC protocol in terms of normalized throughput, packet delay and energy consumption with the Markov model and analytic expressions. The results are quite promising, which makes the RACIR protocol a strong candidate for the CR-based IoT environment.

Recently appeared the IEEE 802.11ah standard has introduced a new channel access mechanism, so-called Restricted Access Window (RAW). This mechanism allows an access point (AP) to reduce contention for the channel in overloaded Wi-Fi networks by limiting the number of stations simultaneously accessing the channel. The 802.11ah AP divides all associated stations into groups and allocates for each group an interval of time, which is called a RAW slot. This paper considers the RAW mechanism with enabled transmissions crossing slot boundaries, which means that a station is allowed to end the current transmission attempt even after a completion of the allocated RAW slot. We present a new mathematical model, which allows estimating throughput and energy consumption with this mechanism, and optimizing performance of RAW.

Wi-Fi HaLow is an adaptation of the widespread Wi-Fi technology for the Internet of Things scenarios. Such scenarios often involve numerous wireless stations connected to a shared channel, and contention for the channel significantly affects the performance in such networks. Wi-Fi HaLow contains numerous solutions aimed at handling the contention between stations, two of which, namely, the Centralized Authentication Control (CAC) and the Distributed Authentication Control (DAC), address the contention reduction during the link set-up process. The link set-up process is special because the access point knows nothing of the connecting stations and its means of control of these stations are very limited. While DAC is self-adaptive, CAC does require an algorithm to dynamically control its parameters. Being just a framework, the Wi-Fi HaLow standard neither specifies such an algorithm nor recommends which protocol, CAC or DAC, is more suitable in a given situation. In this paper, we solve both issues by developing a novel robust close-to-optimal algorithm for CAC and compare CAC and DAC in a vast set of experiments.

The increasing deployment of smart devices has proved that Internet of Things (IoT) is an overwhelming trend for the next era. IEEE 802.11ah, a specification belonging to 802.11 Wireless Local Area Network (WLAN) protocol family, has been recently released to support the long-range, low-power and low-rate wireless communication among smart devices used in IoT systems. However, security requirements on the energy- constrained devices have plenty of features different from the traditional devices. The overhead of messages has to be minimized, even though the entire performance might be compromised. There is an upcoming solution towards this problem discussed in IEEE group, which was described in IEEE 802.11ai, where the Fast Initial Link Setup (FILS) has been defined as a novel methodology aiming at establishing fast, stable and secure links among smart devices. This paper is to address the security issues of the IEEE 802.11ai specified wireless networks with a proposal of an enhancement to the authentication process in the setup procedures for the IEEE 802.11ah specified low power driven wireless sensor networks. The security functionality of the proposed solution is derived by BAN logic while the performance of the solution is evaluated by simulation experiments to demonstrate the advantages of the proposed solution.

This paper presents an open environment wireless sensing framework which reports data through wireless wide area network (WAN). It has low power consumption feature by Sigfox, and this new worldwide low power WAN communication technology is based on IEEE 802.11ah.

Low Power Wide Area Networks are the fundamental keys of the internet of Things (IoT). These networks provide long-range coverage to end nodes, exploiting license-free frequency bands and the sub 1Ghz communications. In this paper we evaluate and analyze using NS-3 network simulator, the uplink throughput of the two promises networks IEEE 802.11ah and LoRaWAN all by implementing the maximum number of the end devices served by a single base station. Also in the second scenario where the nodes are depends on the distance from the base station. In the conclusion we brief and compare the obtained results, and we make actions to be taken in case of making applications or deployments using these networks.

The future Internet of Things (IoT) applications require long range, high rate and reliable wireless links. To support IoT applications, IEEE 802.11 standardization group defined a new amendment ah with improved physical and link layer functionalities. To achieve a target range of 1Km and a minimum data rate of 100Kbps, dual-hop relay stations (RSs) are introduced in IEEE 802.11ah. The analytical model and simulation results presented in the paper, confirms that through the proper deployment of RSs, IEEE 802.11ah can become a flexible solution for IoT applications.

This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

The IEEE 802.11ah standard has proven to be a scalable solution for medium range networks in Internet of Things (IoT). The Restricted Access Window (RAW)-based channel access mechanism of 802.11ah reduces collisions and improves scalability. However, the RAW mechanism creates congestion in the network having event-driven traffic generated randomly. This paper proposes a Quality of Service (QoS)-aware priority grouping and RAW scheduling algorithm for the 802.11ah-based network. The proposed protocol reduces collisions and ensures required bandwidth for rare but critical event-driven stations. Performance evaluation of the proposed scheme shows significant improvement over 802.11ah-based MAC protocol.

IEEE 802.11ah Task Group has been developing an amendment to the 802.11 standard to define sub-1-GHz license-exempt operation to support sensors and Internet of Things applications. This article presents an overview of major physical layer and MAC layer features of 802.11ah.

New technologies continue to be introduced for WLAN applications at a robust pace. We review the value proposition for some of the key features of 802.11ac such as larger bandwidth, higher order modulation, and MIMO and MUMIMO transmission modes, explaining how each feature translates to improved user experience. We present channel measurements and prototype performance data to demonstrate the gains of MIMO and MU-MIMO in an indoor environment. Next, we discuss the value proposition of some key features of 802.11ah. Measurement data of 802.11ah performance is provided, showing how it is a compelling technology for the growing Internet of Things market. We conclude with a preview of emerging technologies that promise to improve user experience — 802.11ai for fast network acquisition and 802.11ax for high-efficiency networking in dense indoor and outdoor networks.

We study carefully the IEEE 802.11ah draft standard published in July 2014.We overview use cases of .11ah, especially related to smart cities scenarios.We describe in details novel mechanisms and explain why they are needed in .11ah. Smart technologies play a key role in sustainable economic growth. They transform houses, offices, factories, and even cities into autonomic, self-controlled systems acting often without human intervention and thus sparing people routine connected with information collecting and processing. The paper gives an overview of a novel Wi-Fi technology, currently under development, which aims to organize communication between various devices used in such applications as smart grids, smart meters, smart houses, smart healthcare systems, smart industry, etc.

Enabling the Internet of Things, machine-type communications (MTC) is a next big thing in wireless innovation. In this work, we concentrate on the attractive benefits offered by the emerging IEEE 802.11ah technology to support a large number of MTC devices with extended communication ranges. We begin with a comprehensive overview of the novel features introduced by the latest IEEE 802.11ah specifications followed by the development of a powerful mathematical framework capturing the essential properties of a massive MTC deployment with unsaturated traffic patterns. Further, we compare our analytical findings for a characteristic MTC scenario against respective system-level simulations across a number of important performance indicators. Our analytical results provide adequate performance predictions even when simulations are challenged by the excessive computational complexity. In addition, we study the novel IEEE 802.11ah mechanisms offering improved support for massive device populations and conclude on their expected performance. acceptedVersion

IEEE 802.11ah, marketed as Wi-Fi HaLow, is a new Wi-Fi standard for sub-1Ghz communications, aiming to address the major challenges of the Internet of Things (IoT), namely connectivity among a large number of densely deployed power-constrained stations. The standard was only published in May 2017 and hardware supporting Wi-Fi HaLow is not available on the market yet. As such, research on 802.11ah has been mostly based on mathematical and simulation models. Mathematical models generally introduce several simplifications and assumptions, which do not faithfully reflect real network conditions. As a solution, we previously developed an IEEE 802.11ah module for ns-3, publicly released in 2016. This initial release consisted of physical layer models fir sub-1GHz communications and an implementation of the fast association and Restricted Access Window (RAW) channel access method. In this paper, we present an extension to our IEEE 802.11ah simulator. It contains several new features: an online RAW configuration interface, an energy state model, adaptive Modulation and Coding Scheme (MCS), and Traffic Indication Map (TIM) segmentation. This paper presents the details of our implementation, along with experimental results to validate each new feature. The extended Wi-Fi HaLow module can now support different scenarios with both uplink and downlink heterogeneous traffic, together with real-time RAW optimization, sleep management for energy conservation and adaptive MCS.

The Restricted Access Window (RAW) mechanism proposed by IEEE 802.11ah promises to address one of the major problems of the Internet of Things (IoT): high channel contention in large-scale densely deployed sensor networks. The RAW feature allows the Access Point (AP) to divide stations into different groups, with only the stations in the same group being allowed to access the channel simultaneously. Existing station grouping strategies only support homogeneous scenarios, where all sensor stations have the same fixed data transmission interval, modulation and coding scheme (MCS) and packet size. In this paper, we present two contributions to address this issue. First, a surrogate model that predicts RAW performance given specific network conditions and RAW configuration parameters. It is fast to train and can be solved in real-time. Second, the Model-Based RAW Optimization Algorithm (MoROA), which uses the surrogate model to determine the optimal RAW configuration in real-time, for heterogeneous stations and dynamic traffic. We compare the accuracy of our surrogate model to simulation results. Performance of MoROA is compared to existing RAW optimization algorithms and traditional 802.11 channel access methods. The results shows that the trained surrogate model can accurately predict RAW performance with a relative error less than 7% and 10% for 95% and 98% of the RAW configurations respectively. MoROA achieves a throughput up to twice as high as traditional 802.11 channel access functions in dense heterogeneous networks.

Internet of Things (IoT) is an emerging technology, which enables the interconnection of computing devices through Internet. IEEE 802.11ah is introduced as an amendment to IEEE 802.11 standard to provide ubiquitous connectivity, scalability and to reduce the energy consumption in dense networks like IoT. IEEE 802.11ah implements Restricted Access Window (RAW) mechanism to reduce packet collisions and improve energy efficiency. RAW reduces contention among the devices by dividing them into several groups and channel time into various slots. In this article, we have developed an analytical model to evaluate the performance of RAW mechanism in terms of throughput and energy efficiency in a dense IoT network. We have also analyzed the performance of RAW mechanism for different Modulation and Coding Schemes (MCS) proposed in the draft standard. The analytical model has been validated through the simulation studies. The results show that, the RAW mechanism outperforms the legacy DCF in a dense IoT scenario.

The main purpose of running ns-3 simulations is to generate relevant data sets for further study. There are two strategies to generate output from ns-3, either using generic predefined bulk output mechanisms or using the ns-3's Tracing system. Both require parsing the raw output data to extract and process the data of interest to obtain meaningful information. However, parsing such output is in most cases time consuming and prone to mistakes. Post-processing is even harder when a large number of simulations needs to be analyzed and even the tracing system cannot simplify this task. Moreover, results obtained this way are only available once the simulation is finished.Therefore, we developed a user-friendly interactive visualization and post-processing tool for IEEE 802.11ah called ahVisualizer. Beside the topology and MAC configuration, ahVisualizer also plots our traces for each node over time during the simulation, as well as averages and standard deviations for each traced parameter. It can compare all the measured values across different simulations. Users can easily download figures and data in various formats. Moreover, it includes a post-processing tool which plots desired series, with desired fixed parameters, from a large set of simulations. This paper presents the ahVisualizer, its services and its architecture and shows how this tool enables much faster and easier data analysis and monitoring of ns-3 simulations with 802.11ah.

Several service applications have been reported by many who proposed the use of wireless LANs (WLANs) over a wide variety of outdoor deployments. In particular, the upcoming IEEE 802.11ah WLAN protocol will enable a longer transmission range between WLAN access points (APs) and stations (STAs) up to multiple kilometers using carrier frequencies at 900 MHz. However, limitations of WLAN outdoor installations have been found of the plethora of WLAN protocols in experimental studies. This article summarizes the challenges and provides a comprehensive overview of suggested improvements. As the standardization of the IEEE 802.11ah is reaching its final stage, important protocol aspects as well as new features are to be outlined. Interference problems and issues with the WLAN configuration, the physical layer (PHY), and media access control (MAC) are of paramount importance in outdoor WLAN networks, and thus, are discussed in detail. Further, we examine the reported upper boundaries in throughput and link reliability of long-range WLANs in different environments, including sea-surfaces, unmanned aerial vehicles (UAVs), and tunnels. At the end of this study, we reflect on the major issues regarding sub-1 GHz (S1G) WLANs and propose avenues for further research.

One of new mobile technology is being developed by 3GPP is Long Term Evolution (LTE). LTE usually used by user because provide high data rate. Many traffic sending over LTE, makes several users didn’t get good Quality of Service (QoS). Traffic diversion is needed to increasing QoS value. It can be done with offloading data method from LTE to Wi-Fi network. This paper using 802.11ah standard to evaluate Wi-Fi network. IEEE 802.11ah have 1000 meters coverage area and efficiency energy mechanism, which is proposed for M2M in 5G techonology. Some research has proven that traffic diversion with offloading can increasing network performance. The contribution of this paper is to evaluate the impact of traffic offload between LTE and IEEE 802.11ah standard. This paper propose two scenarios using increment number of user and increment mobility speed of user to evaluate throughput and delay value before and after the offload process. The simulation will simulate using Network Simulator-3. We can conclude that network performance after offloading is better for every scenario. For increment number of user scenario, throughput value increasing 29.08%, and delay decreasing 8.12%. Scenario with increment mobility speed of user obtain throughput value increasing 37,57%, and delay value decreasing 27.228%.

Wireless networking technologies are the best options to connect a large number of devices. The emerging IEEE 802.11ah, aka Wi-Fi HaLow, is a promising communication standard that supports a massive number of heterogeneous devices in the Internet of Things (IoT). It utilizes sub-1 GHz license-exempt bands to provide an extended range to the Wi-Fi networks. This standard seeks to address various limitations of legacy 802.11 Wi-Fi by incorporating enhancements in both the PHY and MAC layers. This work assesses the evolution and the market readiness of this new, low power Wi-Fi standard. It focuses on the technical challenges faced by this standard. This standard is still in its infancy and there is a large spectrum of opportunities for the research community to evaluate its successful deployment. In this paper, we survey the state of the art of 802.11ah and identify how device manufacturers are responding to this new standard and the promising research directions in this area.

IEEE 802.11ah is a new Wi-Fi standard operating on unlicensed sub-GHz frequencies. It aims to provide long-range connectivity to Internet of Things (IoT) devices. The IEEE 802.11ah restricted access window (RAW) mechanism promises to increase throughput and energy efficiency in dense deployments by dividing stations into different RAW groups and allowing only one group to access the channel at a time. In this demo, we demonstrate the ability of the RAW mechanism to support a large number of densely deployed IoT stations with heterogeneous traffic requirements. Differentiated Quality of Service (QoS) is offered to a small set of high-throughput wireless cameras that coexist with thousands of best-effort sensor monitoring stations. The results are visualized in near real-time using our own developed IEEE 802.11ah visualizer running on top of the ns-3 event-based network simulator.