Beam Search is a search algorithm commonly used in natural language processing and machine translation which is employed during the decoding phase of sequence generation tasks, such as language translation or text generation. It is an algorithmic approach used in neural network models, which are a key component of many network-related applications. Beam search is widely used in tasks like machine translation, text summarization, and image captioning. While it may not directly relate to network infrastructure, these natural language processing applications are often components of systems that use network resources for communication and data exchange.

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The Trade-off between Scanning Beam Penetration and Transmission Beam Gain in mmWave Beam Alignment

The Trade-off between Scanning Beam Penetration and Transmission Beam Gain in mmWave Beam Alignment Beam search algorithms have been proposed to align the beams from an access point to a user equipment. The process relies on sending beams from a set of scanning beams (SB) and tailoring a transmission beam (TB) using the received feedback. In this paper, we discuss a fundamental trade-off between the gain of SBs and TBs. The higher the gain of an SB, the better the penetration of the SB and the higher the gain of the TB the better the communication link performance. However, TB depends on the set of SBs and by increasing the coverage of each SB and in turn reducing its penetration, there is more opportunity to find a sharper TB to increase its beamforming gain. We define a quantitative measure for such trade-off in terms of a trade-off curve. We introduce SB set design namely Tulip design and formally prove it achieves this fundamental trade-off curve for channels with a single dominant path. We also find closed-form solutions for the trade-off curve for special cases and provide an algorithm with its performance evaluation results to find the trade-off curve revealing the need for further optimization on the SB sets in the state-of-the-art beam search algorithms.

Robust Beam Tracking and Data Communication in Millimeter Wave Mobile Networks

Robust Beam Tracking and Data Communication in Millimeter Wave Mobile Networks Millimeter-wave (mmWave) bands have shown the potential to enable high data rates for next generation mobile networks. In order to cope with high path loss and severe shadowing in mmWave frequencies, it is essential to employ massive antenna arrays and generate narrow transmission patterns (beams). When narrow beams are used, mobile user tracking is indispensable for reliable communication. In this paper, a joint beam tracking and data communication strategy is proposed in which, the base station (BS) increases the beamwidth during data transmission to compensate for location uncertainty caused by user mobility. In order to evade low beamforming gains due to widening the beam pattern, a probing scheme is proposed in which the BS transmits a number of probing packets to refine the estimation of angle of arrival based on the user feedback, which enables reliable data transmission through narrow beams again. In the proposed scheme, time is divided into similar frames each consisting of a probing phase followed by a data communication phase. A steady state analysis is provided based on which, the duration of data transmission and probing phases are optimized. Furthermore, the results are generalized to consider practical constraints such as minimum feasible beamwidth. Simulation results reveal that the proposed method outperforms well-known approaches such as optimized beam sweeping.