Beam Codebook Based Beamforming Protocol for Multi-Gbps Millimeter-Wave WPAN Systems

By Junyi Wang, Zhou Lan, C. Pyo, T. Baykaş, C. Sum, Mohammad Azizur Rahman, R. Funada, F. Kojima, I. Lakkis, H. Harada and 1 more. Global Communications Conference, 2009

707 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/975d6d3cf03feaa5a850719459f5cff94d324f6a

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In Electrical and Electronic Engineering

Citations in the corpus

Beamforming for Millimeter Wave Communications: An Inclusive Survey (2016, methodology): “The RF beamsteering codebook [127] is quantified in terms of the steering angle, and as a result is design”
Millimeter Wave Communications for Future Mobile Networks (2017, methodology): “For example, the single-beam training scheme in IEEE 802.11ad consists of three phases [142]: i) Sector level sweep (SLS): the wide beamwidth is considered at ﬁrst, as shown in Fig.”
A Planar Switchable 3-D-Coverage Phased Array Antenna and Its User Effects for 28-GHz Mobile Terminal Applications (2017, methodology): “In addition, the proposed switchable array can also be utilized to significantly shorten the beamforming training period using the hieratical beamforming training scheme [23].”
The Integrated Sensing and Communication Revolution for 6G: Vision, Techniques, and Applications (2024, positive): “The standard approaches are a brute-force search over pairs [273] or a hierarchical search [274] over increasingly refined codebooks.”
A survey of millimeter wave communications (mmWave) for 5G: opportunities and challenges (2015, positive): “To make the transmitter and receiver direct their beams towards each other, the procedure of beam training is needed, and several beam training algorithms have been proposed to reduce the required beam training time [49–51].”
End-to-End Simulation of 5G mmWave Networks (2017, methodology): “The computation for the receiver is done in the same way, starting from In the beam search method, we assume that the TX and the RX scan a discrete number of beams from a pre-designed codebook [64].”
Position and Orientation Estimation Through Millimeter-Wave MIMO in 5G Systems (2017, background): “The resulting loss in signal-to-noise ratio (SNR) must be compe nsated through sophisticated beamforming at the transmitter and/or receiver side, leading to highly dir ect onal links [4]–[6].”
A Tutorial on Environment-Aware Communications via Channel Knowledge Map for 6G (2023, methodology): “Analog beamforming is an effective technique to reduce RF chain cost [42]–[44], where one RF chain is shared by all array”
Channel Estimation via Orthogonal Matching Pursuit for Hybrid MIMO Systems in Millimeter Wave Communications (2016, methodology): “In mm-wave communication, closed-loop beam training-based methods are proposed for CSI estimation [3], [4], [9]–[11].”
Millimeter-Wave Massive MIMO Communication for Future Wireless Systems: A Survey (2018, background): “An extensive survey on beamforming types and architectures can be found in [14], [15], [44], [51], and [93]–[96] and a quick overview on comparison of digi-”
Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems (2014, methodology): “Moreover, the performance of analog strategies such as those in [3], [7]–[9] is sub-optimal compared with digital precoding solutions due to (i) the constant amplitude constraint on the analog phase shifters, and (ii) the potentially low-resolution signal phase control.”
Millimeter Wave MIMO With Lens Antenna Array: A New Path Division Multiplexing Paradigm (2015, background): “…arrays, channel estimation is a challenging task due to the large-antenna dimension as well as the low SNR before beamforming is applied [14], [16], [21]; whereas with lens antenna arrays, by exploiting its energy focusing as well as the multi-path sparsity of mmWave channels, the…”
Deep Learning Coordinated Beamforming for Highly-Mobile Millimeter Wave Systems (2018, methodology): “This is a key advantage of our developed deep-learning based solution over traditional mmWave channel training/estimation techniques such as analog beam training [20], [51] and compressive sensing [24], [25], [52].”
Channel Estimation for Hybrid Architecture-Based Wideband Millimeter Wave Systems (2016, background): “Further, operating at mmWave frequencies complicates the estimation of the channel because the signal-to-noise-ratio (SNR) before beamforming is low and the dimensions of the channel matrices associated with mmWave arrays [2], [3] are large.”
Spatially Sparse Precoding in Millimeter Wave MIMO Systems (2013, methodology): “To improve performance over correlated channels, the work [17]–[19] considers beam steering solutions in which phase shifters are used to optimally orient an array’s response in space, potentially based on statistical channel knowledge.”