The emerging paradigm of the Internet of Everything, along with the increasing demand of Internet services everywhere, results in a remarkable and continuous growth of the global Internet traffic. As a cost-effective Internet access solution, WiFi networks currently generate a major portion of the global Internet traffic. Furthermore, the number of WiFi public hotspots worldwide is expected to increase by more than sevenfold by 2018. To face this huge increase in the number of densely deployed WiFi networks, and the massive amount of data to be supported by these networks in indoor and outdoor environments, it is necessary to improve the current WiFi standard and define specifications for high efficiency wireless local area networks (HEWs). This paper presents potential techniques that can be applied for HEWs, in order to achieve the required performance in dense HEW deployment scenarios, as expected in the near future. The HEW solutions under consideration includes physical layer techniques, medium access control layer strategies, spatial frequency reuse schemes, and power saving mechanisms. To accurately assess a newly proposed HEW scheme, we discuss suitable evaluation methodologies, by defining simulation scenarios that represent future HEW usage models, performance metrics that reflect HEW user experience, traffic models for dominant HEW applications, and channel models for indoor and outdoor HEW deployments. Finally, we highlight open issues for future HEW research and development.

A Survey on High Efficiency Wireless Local Area Networks: Next Generation WiFi

The performance of current consumer-grade devices for 60 GHz wireless networks is limited. While such networks promise both high data rates and uncomplicated spatial reuse, we find that commercially available devices based on the WiHD and WiGig standards may suffer from their cost-effective design. Very similar mechanisms are used in upcoming devices based on the IEEE 802.11ad standard. Hence, understanding them well is crucial to improve the efficiency and performance of next generation millimeter wave networks. In this paper, we present the first in-depth beamforming, interference, and frame level protocol analysis of off-the-shelf millimeter wave systems with phased antenna arrays. We focus on (a) the interference due to the lack of directionality of consumer-grade antennas, and (b) the degree of data aggregation of current devices. Regarding (a), our beam pattern measurements show strong side lobes that challenge the common conception of high spatial reuse in 60 GHz networks. We also show that reflections in realistic settings worsen this effect. Further, we measure weak directionality when beamforming towards the boundary of the transmission area of an antenna array. Regarding (b), we observe that devices only aggregate data if connections require high bandwidth, thus increasing medium usage time otherwise.

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Boon and bane of 60 GHz networks: practical insights into beamforming, interference, and frame level operation

With the multi-antenna design of WiFi interfaces, phased array has become a promising mechanism for accurate WiFi localization. State-of-the-art WiFi-based solutions using Angle-of-Arrival (AoA), however, face a number of critical challenges. First, their localization accuracy degrades dramatically due to low Signal-to-Noise Ratio (SNR) and incoherent processing. Second, they tend to produce outliers when the available number of packets is low. Moreover, the prior phase calibration schemes are not multipath robust and accurate enough. All of the above degrade the robustness of localization systems. In this paper, we present ROArray, a RObust Array based system that accurately localizes a target even with low SNRs. The key insight of ROArray is to use sparse recovery and coherent processing across all available domains, including time, frequency, and spatial domains. Specifically, in the spatial domain, ROArray can produce sharp AoA spectrums by parameterizing the steering vector based on a sparse grid. Then, to expand into the frequency domain, it jointly estimates the Time-of-Arrival (ToAs) and AoAs of all the paths using multi-subcarrier OFDM measurements. Furthermore, through a novel multi-packet fusion scheme, ROArray is enabled to perform coherent estimation over multiple packets. Such coherent processing not only increases the virtual aperture size, which enlarges the number of maximum resolvable paths but also improves the system robustness to noise. In addition, ROArray includes an online phase calibration technique that can eliminate random phase offsets while keeping communication uninterrupted. Our implementation using off-the-shelf WiFi cards demonstrates that, with low SNRs, ROArray significantly outperforms state-of-the-art solutions in terms of localization accuracy; when medium or high SNRs are present, it achieves comparable accuracy.

RoArray: Towards More Robust Indoor Localization Using Sparse Recovery with Commodity WiFi

In this paper, we discuss the effects on throughput and fairness of dynamic channel bonding (DCB) in spatially distributed high-density wireless local area networks (WLANs). First, we present an analytical framework based on continuous-time Markov networks (CTMNs) for depicting the behavior of different DCB policies in spatially distributed scenarios, where nodes are not required to be within the carrier sense range of each other. Then, we assess the performance of DCB in high-density IEEE 802.11ac/ax WLANs by means of simulations. We show that there may be critical interrelations among nodes in the spatial domain–even if they are located outside the carrier sense range of each other–in a chain reaction manner. Results also reveal that, while always selecting the widest available channel normally maximizes the individual long-term throughput, it often generates unfair situations where other WLANs starve. Moreover, we show that there are scenarios where DCB with stochastic channel width selection improves the latter approach both in terms of individual throughput and fairness. It follows that there is not a unique optimal DCB policy for every case. Instead, smarter bandwidth adaptation is required in the challenging scenarios of next-generation WLANs.

Dynamic Channel Bonding in Spatially Distributed High-Density WLANs

In dense Wireless Local Area Networks (WLANs), high-density Access Points (APs) bring severe interference that seriously affects the experience of users, resulting in lower throughput and poor connection quality. Due to the heavy computation workload raised by the sizable networking systems and the difficulty in estimating instantaneous Channel State Information (CSI), existing works are hard to solve interference problem. In this paper, we propose a Joint Power control and Channel allocation based on Reinforcement Learning (JPCRL) algorithm combining with statistical CSI to reduce interference adaptively. Firstly, we analyze the correlation between transmit power and channel, and formulate the interference optimization as a Mixed Integer Nonlinear Programming (MINLP) problem. Secondly, we use the statistical CSI method to take the power and channel state as the state and action space, the overall throughput increment as the reward function of Q-learning, and obtain the optimal joint optimization strategy through off-line training. Moreover, for the periodic reinforcement learning process leading to resource consumption, we design an event-driven mechanism of Q-learning, which triggers online learning to refresh the optimal policy by event-driven condition and the consumption of computing resources can be reduced. The evaluation results show that the proposed algorithm can effectively improve the throughput compared with the existing scheme.

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Joint Power Control and Channel Allocation for Interference Mitigation Based on Reinforcement Learning

IEEE 802.11n WLAN supports frame aggregation called aggregate MAC protocol data unit (A-MPDU) as a key MAC technology to achieve high throughput. While it has been generally accepted that aggregating more subframes results in higher throughput by reducing protocol overheads, our measurements reveal various situations where the use of long A-MPDU frames frequently leads to poor performance in time-varying environments. Especially, since mobility intensifies the time-varying nature of the wireless channel, the current method of channel estimation conducted only at the beginning of a frame reception is insufficient to ensure robust delivery of long A-MPDU frames. Based on extensive experiments, we develop MoFA, a standard-compliant mobility-aware A-MPDU length adaptation scheme with ease of implementation. Our prototype implementation in commercial 802.11n devices shows that MoFA achieves the throughput 1.8x higher than a fixed duration setting (i.e., 10 ms, the maximum frame duration according to IEEE 802.11n standard). To our best knowledge, this is the first effort to optimize the A-MPDU length for commercial 802.11n.

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MoFA: Mobility-aware Frame Aggregation in Wi-Fi

IEEE 802.11n/ac wireless local area network (WLAN) supports frame aggregation, called aggregate medium access control (MAC) protocol data unit (A-MPDU), to enhance MAC efficiency by reducing protocol overhead. However, the current channel estimation process conducted only once during the preamble reception is known to be insufficient to ensure robust delivery of long A-MPDU frames in mobile environments. To cope with this problem, we first build a model which represents the impact of mobility with a noise vector in the I-Q plane, and then analyze how the mobility affects the A-MPDU reception performance. Based on our analysis, we develop STRALE, a standard-compliant and mobility-aware PHY rate and A-MPDU length adaptation scheme with ease of implementation. Through extensive simulations with 802.11ac using ns-3 and prototype implementation with commercial 802.11n devices, we demonstrate that STRALE achieves up to 2.9x higher throughput, compared to a fixed duration setting according to IEEE 802.11 standard.

STRALE: Mobility-aware PHY rate and frame aggregation length adaptation in WLANs

Today, voice over IP (VoIP) service is emerging as a popular and important application in wireless local area networks (WLANs). While rate adaptation (or link adaptation) has been identified as a key factor determining the performance of WLANs, we have observed that most (if not all) rate adaptation algorithms have been developed to improve the throughput of data traffic, not the quality of service (QoS) of VoIP traffic. Accordingly, in this paper, we investigate the characteristics of VoIP traffic and the limitations of state-of-the-art rate adaptation algorithms, and then enhance the QoS of voice over WLAN (VoWLAN) by ameliorating the existing rate adaptation algorithms. Specifically, we design fast decrease to control the transmission rate of retransmissions, and retry scheduling to avoid the deep fading of the wireless channel as well as hidden terminal interference. We comparatively evaluate the QoS of the revised rate adaptation algorithms via ns-3 simulations and MadWiFi implementations in various communication environments, and demonstrate that the proposed schemes improve the R-score performance by up to 80 percent depending on the network scenarios.

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Enhancing Voice over WLAN via Rate Adaptation and Retry Scheduling

IEEE 802.11 has evolved from 802.11a/b/g/n to 802.11ac in order to meet ever-increasing high throughput demand. The newest standard supports various channel widths up to 160 MHz by bonding multiple 20 MHz channels. In order to efficiently utilize multiple channel widths, 802.11ac defines two operations, namely, dynamic channel access (DCA) and dynamic bandwidth operation (DBO). In this paper, we reveal that the use of DCA improves channel utilization significantly, and DBO not only partly overcomes secondary channel hidden interference problems but also achieves better channel utilization. However, when a transmitter attempts to send an enhanced RTS frame before data transmission as part of DBO, the station has no way to know how much bandwidth will be used, thus leading to malfunction of virtual carrier sensing at neighboring stations. On the other hand, the use of enhanced RTS/CTS without hidden traffic wastes airtime significantly. To address these problems, we first define how to calculate an appropriate value of duration field for enhanced RTS/CTS, and then develop an algorithm which adaptively enables/disables DBO considering the (secondary) hidden interference. Through ns-3 simulations, we demonstrate that the proposed scheme achieves up to 2x higher throughput compared to the baseline of 802.11ac.

Enhancement of wide bandwidth operation in IEEE 802.11ac networks

In this paper, we develop a contention window (CW) control scheme for practical IEEE 802.11 wireless local area networks (WLANs) that have node heterogeneity in terms of the traffic load, transmission rate, and packet size. We introduce activity probability , i.e., the probability that a node contends for medium access opportunities at a given time. We then newly develop a performance analysis model that enables analytic estimation on the contention status including the collision probability, collision time, back-off time, and throughput with comprehensive consideration of node heterogeneity. Based on the newly developed model, we derive the theoretically ideal contention status, and develop a CW control scheme that achieves the ideal contention status in an average sense. We perform extensive NS-3 simulations and real testbed experiments for evaluation of both the proposed performance analysis model and CW control scheme. The results show that the proposed model provides accurate prediction on the contention status, and the proposed CW control scheme achieves considerable throughput improvement compared to the existing schemes which do not comprehensively consider node heterogeneity.

Seongho Byeon

Papers

MoFA: Mobility-aware Frame Aggregation in Wi-Fi

STRALE: Mobility-aware PHY rate and frame aggregation length adaptation in WLANs

Enhancing Voice over WLAN via Rate Adaptation and Retry Scheduling

Enhancement of wide bandwidth operation in IEEE 802.11ac networks

Activity Probability-Based Performance Analysis and Contention Control for IEEE 802.11 WLANs