Driven by Capacity or Blockage? A Millimeter Wave Blockage Analysis

Jain, Ish Kumar; Kumar, Rajeev; Panwar, Shiendra

doi:10.1109/itc30.2018.00032

Cited by 44 publications

(34 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The authors of [9] introduce a novel spatial dynamic channel sounding system at a frequency of 60 GHz. Moreover, based on the results in [10], [11], the authors propose that dynamic blockage plays an important role in the engineering design of mmWave cellular systems. Blockages impact on the channel propagation and on achieving the optimum antenna configuration for a given environment [12].…”

Section: A Related Workmentioning

confidence: 99%

Adaptive Sum of Markov Chains for Modelling 3D Blockage in mmWave V2I Communications

Alsaleem

Thompson

Laurenson

2020

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

Blockage attenuation is one of the main challenges that face reliable communication at the millimetre-wave (mmWave) band, especially for dynamic vehicle-to-infrastructure (V2I) communication systems. Modelling the dynamics of the blockage is important for evaluating high gain beamforming techniques, which are used to improve the signal strength in the mmWave communication systems. The novel sum of Markov chains (sum of MC) model is designed to do two main tasks successfully; capturing the dynamics of blockers affecting a moving transceiver and computing the arising channel attenuation. The sum of MC model has advantages over existing Markov chains models, which are: that it can adapt to model non-stationary scenarios. The sum of MC model can integrate any attenuation function, including the 3GPP blockage model and any lab measurement attenuation profile. Additionally, it is computationally efficient. The sum of MC model can match well with the performance results from a more complex geometric channel model.

show abstract

Section: A Related Workmentioning

confidence: 99%

Adaptive Sum of Markov Chains for Modelling 3D Blockage in mmWave V2I Communications

Alsaleem

Thompson

Laurenson

2020

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…For the sake of simplicity, we assume that a mobile selfblocking model is neglected, extending the result of this paper to the case of incorporating self-blocking is straight forward by including loss from [18].…”

Section: Self-blockage Modelmentioning

confidence: 99%

Handover Management in Dense Networks with Coverage Prediction from Sparse Networks

Mollel

Öztürk

Kisangiri

et al. 2019

2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)

View full text Add to dashboard Cite

Millimeter Wave (mm-Wave) provides high bandwidth and is expected to increase the capacity of the network thousand-fold in the future generations of mobile communications. However, since mm-Wave is sensitive to blockage and incurs in a high penetration loss, it has increased complexity and bottleneck in the realization of substantial gain. Network densification, as a solution for sensitivity and blockage, increases handover (HO) rate, unnecessary and ping-pong HO, which in turn reduces the throughput of the network. On the other hand, to minimize the effect of increased HO rate, Time to Trigger (TTT) and Hysteresis factor (H) have been used in Long term Evolution (LTE). In this paper, we primarily present two different networks based on Evolved NodeB (eNB) density: sparse and dense. As their name also suggests, the eNB density in the dense network is higher than the sparse network. Hence, we proposed an optimal eNB selection mechanism for 5G intramobility HO based on spatial information of the sparse eNB network. In this approach, User equipment (UE) in the dense network is connected only to a few selected eNBs, which are delivered from the sparse network, in the first place. HO event occurs only when the serving eNB can no longer satisfy the minimum Signal-to-Noise Ratio (SNR) threshold. For the eNBs, which are deployed in the dense network, follow the conventional HO procedure. Results reveal that the HO rate is decreased significantly with the proposed approach for the TTT values between 0 ms to 256 ms while keeping the radio link failure (RLF) at an acceptable level; less than 2% for the TTT values between 0 ms to 160 ms. This study paves a way for HO management in the future 5G network.

show abstract

“…Then, using tools from stochastic geometry, they derive a general expression of the signal-tointerference-plus-noise ratio coverage probability. In [21], the authors consider an open park-like scenario and obtain closedform expressions for the expected frequency and duration of blockage events using stochastic geometry. Their results indicate that the minimum density of base station, that is required to satisfy the quality of service requirements specially for ultra reliable low latency applications, is largely driven by blockage events rather than capacity requirements.…”

Section: A Prior Workmentioning

confidence: 99%

“…They modeled humans as cylinders with arbitrarily distributed heights and radii, whose centers follow a Poisson point process in two dimensions. By using stochastic geometry, the authors in [21] find the blockage probability as a function of receiver dimension and the transmitter-receiver separation. Then, based on their analysis, the optimal height of the mmW transmitter in crowded outdoor environments is derived and shown to be proportional to the transmitter-receiver separation.…”

Section: A Prior Workmentioning

confidence: 99%

Optimized Deployment of Millimeter Wave Networks for In-Venue Regions With Stochastic Users’ Orientation

Soorki

Saad

Bennis

2019

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

Millimeter wave (mmW) communication is a promising solution for providing high-capacity wireless network access. However, the benefits of mmW are limited by the fact that the channel between a mmW access point and the user equipment can stochastically change due to severe blockage of mmW links by obstacles such as the human body. Thus, one main challenge of mmW network coverage is to enable directional line-of-sight links between access points and mobile devices. In this paper, a novel framework is proposed for optimizing mmW network coverage within hotspots and in-venue regions, while being cognizant of the body blockage of the network's users. In the studied model, the locations of potential access points and users are assumed as predefined parameters while the orientation of the users is assumed to be stochastic. Hence, a joint stochastic access point placement and beam steering problem subjected to stochastic users' body blockage is formulated, under desired network coverage constraints. Then, a greedy algorithm is introduced to find an approximation solution for the joint deployment and assignment problem using a new "size constrained weighted set cover" approach. A closed-form expression for the ratio between the optimal solution and approximate one (resulting from the greedy algorithm) is analytically derived. The proposed algorithm is simulated for three in-venue regions: the meeting room in the Alumni Assembly Hall of Virginia Tech, an airport gate, and one side of a stadium football. Simulation results show that, in order to guarantee network coverage for different in-venue regions, the greedy algorithm uses at most three more access points (APs) compared to the optimal solution. The results also show that, due to the use of the additional APs, the greedy algorithm will yield a network coverage up to 11.7% better than the optimal, AP-minimizing solution.

show abstract

Driven by Capacity or Blockage? A Millimeter Wave Blockage Analysis

Cited by 44 publications

References 22 publications

Adaptive Sum of Markov Chains for Modelling 3D Blockage in mmWave V2I Communications

Adaptive Sum of Markov Chains for Modelling 3D Blockage in mmWave V2I Communications

Handover Management in Dense Networks with Coverage Prediction from Sparse Networks

Optimized Deployment of Millimeter Wave Networks for In-Venue Regions With Stochastic Users’ Orientation

Contact Info

Product

Resources

About