Fast millimeter wave beam alignment

Hassanieh, Haitham; Abari, Omid; Rodriguez, Michael; Abdelghany, Mohammed; Katabi, Dina; Indyk, Piotr

doi:10.1145/3230543.3230581

Cited by 168 publications

(97 citation statements)

References 25 publications

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“…Hassanieh et al proposed a fast BA protocol through scanning multiple directions simultaneously [7]. A similar method, which treats the problem of identifying the optimal beam as that of locating the error in linear block codes, is developed to reduce BA complexity [15].…”

Section: Related Workmentioning

confidence: 99%

Fast mmwave Beam Alignment via Correlated Bandit Learning

Cheng

Zhang

et al. 2019

IEEE Trans. Wireless Commun.

128

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Beam alignment (BA) is to ensure the transmitter and receiver beams are accurately aligned to establish a reliable communication link in millimeter-wave (mmwave) systems. Existing BA methods search the entire beam space to identify the optimal transmit-receive beam pair, which incurs significant BA latency on the order of seconds in the worst case. In this paper, we develop a learning algorithm to reduce BA latency, namely Hierarchical Beam Alignment (HBA) algorithm. We first formulate the BA problem as a stochastic multi-armed bandit problem with the objective to maximize the cumulative received signal strength within a certain period. The proposed algorithm takes advantage of the correlation structure among beams such that the information from nearby beams is extracted to identify the optimal beam, instead of searching the entire beam space. Furthermore, the prior knowledge on the channel fluctuation is incorporated in the proposed algorithm to further accelerate the BA process.Theoretical analysis indicates that the proposed algorithm is asymptotically optimal. Extensive simulation results demonstrate that the proposed algorithm can identify the optimal beam with a high probability and reduce the BA latency from hundreds of milliseconds to a few milliseconds in the multipath channel, as compared to the existing BA method in IEEE 802.11ad.

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Section: Related Workmentioning

confidence: 99%

Fast mmwave Beam Alignment via Correlated Bandit Learning

Cheng

Zhang

et al. 2019

IEEE Trans. Wireless Commun.

128

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“…Although a typical choice of M = K 2 is adopted for analyzing the sample complexity, it should not be difficult to reach a similar conclusion for a general choice of M with M = O(K 2 ). As a comparison, note that the sample complexity attained by most compressive phase retrieval methods [27], [28] and the AgileLink beam steering scheme [8], [24] is of order O(K log(N )).…”

Section: B Analysis Of Sample Complexitymentioning

confidence: 99%

Fast Beam Alignment for Millimeter Wave Communications: A Sparse Encoding and Phaseless Decoding Approach

Fang

Huang

et al. 2019

IEEE Trans. Signal Process.

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In this paper, we studied the problem of beam alignment for millimeter wave (mmWave) communications, in which we assume a hybrid analog and digital beamforming structure is employed at the transmitter (i.e. base station), and an omni-directional antenna or an antenna array is used at the receiver (i.e. user). By exploiting the sparse scattering nature of mmWave channels, the beam alignment problem is formulated as a sparse encoding and phaseless decoding problem. More specifically, the problem of interest involves finding a sparse sensing matrix and an efficient recovery algorithm to recover the support and magnitude of the sparse signal from compressive phaseless measurements. A sparse bipartite graph coding (SBG-Coding) algorithm is developed for sparse encoding and phaseless decoding. Our theoretical analysis shows that, in the noiseless case, our proposed algorithm can perfectly recover the support and magnitude of the sparse signal with probability exceeding a pre-specified value from O(K 2 ) measurements, where K is the number of nonzero entries of the sparse signal. The proposed algorithm has a simple decoding procedure which is computationally efficient and noise-robust. Simulation results show that our proposed method renders a reliable beam alignment in the low and moderate signal-to-noise ratio (SNR) regimes and presents a clear performance advantage over existing methods.Index Terms-Millimeter wave (mmWave) communications, beam alignment, sparse encoding and phaseless decoding.

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“…Although the multi-beam hash functions reduce the search time, they were not used to identify multiple channel clusters. [19] improves on [18] and reduces beam alignment delay by orders of magnitude. Similar to [19], the authors in [20] and [21] also aimed at scanning the environment with multi-lobe beam patterns and establishing communications through multiple lobes.…”

Section: Related Workmentioning

confidence: 99%

“…[19] improves on [18] and reduces beam alignment delay by orders of magnitude. Similar to [19], the authors in [20] and [21] also aimed at scanning the environment with multi-lobe beam patterns and establishing communications through multiple lobes. However, they did not optimize their search scheme and simply rotated a predesigned multi-lobe pattern to decide the best Rx pattern.…”

Section: Related Workmentioning

confidence: 99%

Multi-beam Transmissions for Blockage Resilience and Reliability in Millimeter-Wave Systems

Aykin

Akgun

Krunz

2019

IEEE J. Select. Areas Commun.

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Directionality in millimeter-wave (mmW) systems make link establishment and maintenance challenging, due to the search-time overhead of beam scanning and the vulnerability of directional links to blockages. In this paper, we propose a communication protocol called SmartLink, which exploits the clustering phenomenon at mmW frequencies to establish a multibeam link between a base station and a user. By utilizing multiple clusters, SmartLink enables efficient link maintenance and sustained throughput. We develop a logarithmic-time search algorithm called multi-lobe beam search (MLBS), which is used in SmartLink to discover the clusters. MLBS probes several directions simultaneously, using multi-lobe beam patterns. The number of simultaneous lobes is selected to minimize the search time of the clusters. We provide detailed analysis of the false alarm and misdetection probabilities for the designed beam patterns. Following cluster discovery, SmartLink divides antennas into sub-arrays to generate the optimal multi-lobe beam pattern that maximizes the average data rate under blockage. Extensive simulations using actual channel traces obtained by utilizing phased-array antennas at 29 GHz are used to verify the efficiency of SmartLink. MLBS decreases the discovery time by up to 88% compared to common existing search schemes, and exploiting multiple clusters improves the average data rate by 10%.

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Fast millimeter wave beam alignment

Cited by 168 publications

References 25 publications

Fast mmwave Beam Alignment via Correlated Bandit Learning

Fast mmwave Beam Alignment via Correlated Bandit Learning

Fast Beam Alignment for Millimeter Wave Communications: A Sparse Encoding and Phaseless Decoding Approach

Multi-beam Transmissions for Blockage Resilience and Reliability in Millimeter-Wave Systems

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