Pose Information Assisted 60 GHz Networks

Wei, Teng; Zhang, Xinyu

doi:10.1145/3117811.3117832

Cited by 74 publications

(29 citation statements)

References 35 publications

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“…Moreover, they also propose an online algorithm to deal with the real‐time traffic and human blockage. Wei et al 17 propose a robust 60GHz network architecture that can provide seamless coverage and mobility, which selects AP‐client links more accurately by combining the position information and the beam signal to reduce the probability of link blockage. Athanasiou et al 18 propose a distributed link scheduling algorithm based on Lagrangian duality theory and subgradient methods, which aims to minimize the maximum AP utilization, and prove its asymptotic optimality properties.…”

Section: Related Workmentioning

confidence: 99%

Energy‐efficient Link Scheduling in Time‐variant Dual‐Hop 60GHz Wireless Networks

Chen

et al. 2020

Concurrency and Computation

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Dual-hop 60 GHz wireless networks which support relay-assisted dual-hop transmission have been widely adopted in the recent years, aiming to prolong communication distance and bypass obstacles in 60 GHz band. However, it is very challenging to perform link scheduling in such dual-hop architecture while considering several factors, i.e., reducing network power consumption, avoiding overloaded APs/relays and adapting to network dynamics. To this end, we investigate the problem of energy-efficient link scheduling with load constraints (ELL), and propose solutions to deal with network dynamics. First, we present a fine-grained energy model for dual-hop 60 GHz networks, and formulate the ELL problem as an integer linear programming model that aims to minimize the network power consumption, while satisfying AP/relay load constraints. Then, we propose a polynomial-time global scheduling algorithm that obtains a near-optimal link scheduling solution via iterative relaxation, and the load constraint at each AP/relay can only be violated by at most an additive constant of two. Moreover, we present a local adjustment algorithm to adjust link-scheduling solutions efficiently, such as client arrival/departure and link blockage, and design a hybrid algorithm that combines global scheduling and local adjustment. Finally, we conduct simulation experiments that validate our algorithms' effectiveness and efficiency.

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Section: Related Workmentioning

confidence: 99%

Energy‐efficient Link Scheduling in Time‐variant Dual‐Hop 60GHz Wireless Networks

Chen

et al. 2020

Concurrency and Computation

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“…This is an inevitable phenomenon in current millimeter wave (mmWave) based networks and the performance loss is negligible. According to some recent results [3], even when the end device is kept within the Fieldof-View (FoV) of the AP's signal, the user may still face an up to 50% loss in the network throughput, compared with the stationary cases. Another problem in this scenario is that the signal is lost when the user steps behind an obstacle.…”

Section: Introductionmentioning

confidence: 99%

Enabling 60 GHz Seamless Coverage for Mobile Devices: A Motion Learning Approach

Ota

Dong

et al. 2018

2018 IEEE Global Communications Conference (GLOBECOM)

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Despite all the benefits 60 GHz networks bring about, such as high network bandwidth, effective data rates, etc., one of its main application scenarios, Line-of-Sight (LoS) communications, still has troubles in actual indoor environments due to its high directionality. Traditional beam training methods are inaccurate and time-wasting, leading to unstable and inefficient wireless networks. Therefore, in this paper, we attempt to address this problem from a new aspect, i.e., assisting the signal adaptation with human mobility prediction. A state-of-the-art long short-term memory (LSTM) model is adopted to analyze the past trajectories and predict the future position, which can serve as an important reference for the transmitters to proactively adjust their beams and provide seamless coverage. In addition, we also design an algorithm to optimize the beam selection problem and improve the network quality. To the best of our knowledge, this is the first work in the field to use deep learning models for the beam selection problem. Simulations demonstrate that our approach is robust and efficient, and outperforms the state-ofthe-art in several related tasks.

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“…Achieving pervasive connectivity in the mmWave with receivers, transmitters and reflectors moving, has become the topic of substantial research over the last few years [89][90][91][92]. The standard approach is to react, upon blockage detection, and search for a strong enough NLOS reflection over the (rather large) space of beam patterns (beam realignment or training), or for another AP (handover).…”

Section: Introductionmentioning

confidence: 99%

“…The standard approach is to react, upon blockage detection, and search for a strong enough NLOS reflection over the (rather large) space of beam patterns (beam realignment or training), or for another AP (handover). To alleviate the overhead incurred in such tedious approach (see e.g., [89]), several authors have studied preemptive alternatives [89][90][91][92], discussed in §7.2. Interestingly, all this literature exploits the concept of context awareness, such as out-of-band information [90], pose information [91], predictable traffic patterns [92] or device localization [93,94].…”

Section: Introductionmentioning

confidence: 99%

“…To alleviate the overhead incurred in such tedious approach (see e.g., [89]), several authors have studied preemptive alternatives [89][90][91][92], discussed in §7.2. Interestingly, all this literature exploits the concept of context awareness, such as out-of-band information [90], pose information [91], predictable traffic patterns [92] or device localization [93,94]. Evidently, the ability to locate devices precisely enables interesting optimizations, e.g., by executing an immediate handover upon blockage detection without the need for invoking a beam training or AP search procedure.…”

Section: Introductionmentioning

confidence: 99%

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Zero Overhead Device Tracking in 60 GHz Wireless Networks using Multi-Lobe Beam Patterns

Loch

Assasa

Palacios

et al. 2017

Proceedings of the 13th International Conference on Emerging Networking EXperiments and Technologies

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Millimeter wave (mmWave) technology is one of the main pillars of the next generation Wireless Local Area Networks (WLANs) and 5G mobile networks. The main reason lies in the quantum leap of capacity it provides with respect to wireless networks operating in the sub-6-GHz band. Nevertheless, efficient and reliable communication in the mmWave band demands novel techniques to tackle all the barriers associated with wireless propagation in this band. For

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Pose Information Assisted 60 GHz Networks

Cited by 74 publications

References 35 publications

Energy‐efficient Link Scheduling in Time‐variant Dual‐Hop 60GHz Wireless Networks

Energy‐efficient Link Scheduling in Time‐variant Dual‐Hop 60GHz Wireless Networks

Enabling 60 GHz Seamless Coverage for Mobile Devices: A Motion Learning Approach

Zero Overhead Device Tracking in 60 GHz Wireless Networks using Multi-Lobe Beam Patterns

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