[Paper Review] Fast and Reliable Initial Access with Random Beamforming for mmWave Networks

Yanpeng Yang, Shokri-Ghadikolaei Hossein+3 more|arXiv (Cornell University)|Nov 30, 2018

Millimeter-Wave Propagation and Modeling34 references4 citations

TL;DR

This paper proposes random beamforming for fast and reliable initial access in dense mmWave networks, using stochastic geometry to model interference and beam alignment. It shows that random beamforming reduces initial access latency with comparable failure probability to exhaustive and iterative search, especially in light-traffic and low-latency scenarios.

ABSTRACT

Millimeter-wave (mmWave) communications rely on directional transmissions to overcome severe path loss. Nevertheless, the use of narrow beams complicates the initial access procedure and increase the latency as the transmitter and receiver beams should be aligned for a proper link establishment. In this paper, we investigate the feasibility of random beamforming for the cell-search phase of initial access. We develop a stochastic geometry framework to analyze the performance in terms of detection failure probability and expected latency of initial access as well as total data transmission. Meanwhile, we compare our scheme with the widely used exhaustive search and iterative search schemes, in both control plane and data plane. Our numerical results show that, compared to the other two schemes, random beamforming can substantially reduce the latency of initial access with comparable failure probability in dense networks. We show that the gain of the random beamforming is more prominent in light traffics and low-latency services. Our work demonstrates that developing complex cell-discovery algorithms may be unnecessary in dense mmWave networks and thus shed new lights on mmWave network design.

Motivation & Objective

• To address the high latency and complexity of initial access in mmWave networks due to directional beamforming requirements.
• To evaluate whether random beamforming can achieve fast and reliable cell search in dense mmWave deployments.
• To compare random beamforming against exhaustive and iterative search schemes in terms of detection failure probability, latency, and data plane performance.
• To develop a system-level analytical framework using stochastic geometry that accounts for LOS/NLOS propagation, antenna sidelobes, and realistic 3GPP NR configurations.

Proposed method

• Develops a stochastic geometry-based framework to model the spatial distribution of base stations and user equipment in a multi-cell mmWave network.
• Models interference from both mainlobes and sidelobes using independent Poisson point processes and derives Laplace transforms for interference power in mini-slots.
• Derives exact expressions for detection failure probability by combining mainlobe and sidelobe detection probabilities, assuming independence between them.
• Uses selection combining across multiple mini-slots to model the probability of successful SINR detection above a threshold.
• Models the initial access latency as a geometric distribution of failed frames, with the expected latency computed as the sum of failed frame durations and one successful access period.
• Extends the model to compute total transmission latency, including data transmission time, based on frame duration, access time, and data rate.

Experimental results

Research questions

• RQ1 Can random beamforming achieve lower initial access latency than exhaustive and iterative search in dense mmWave networks?
• RQ2 What is the detection failure probability of random beamforming under realistic propagation conditions (LOS/NLOS) and non-zero antenna sidelobes?
• RQ3 How does the performance of random beamforming scale with network density and traffic load?
• RQ4 What is the trade-off between initial access latency and data transmission latency under random beamforming?
• RQ5 In what network scenarios (e.g., light traffic, low-latency services) does random beamforming provide the most significant gain?

Key findings

• Random beamforming achieves substantially lower initial access latency than exhaustive and iterative search schemes, especially in dense mmWave networks.
• The detection failure probability of random beamforming remains comparable to that of exhaustive and iterative search, even with non-zero antenna sidelobes and NLOS propagation.
• The latency gain of random beamforming is most pronounced in light-traffic scenarios and for low-latency services, where fast connection setup is critical.
• The proposed stochastic geometry framework accurately captures interference from both mainlobes and sidelobes, enabling precise latency and reliability analysis.
• The expected initial access latency under random beamforming is given by $ oxed{rac{1}{1 - P_f(N_c)} - 1} imes T_f + T_{ ext{cs}} + T_{ ext{ra}} $, where $ P_f $ is the failure probability and $ T_f $ is the frame duration.
• Total transmission latency is minimized under random beamforming due to reduced initial access delay, even when accounting for data transmission overhead.