On the performance of random vector quantization limited feedback beamforming in a MISO system

By Chun Kin Au-Yeung, D. J. Love. IEEE Transactions on Wireless Communications, 2007

518 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/af69e3be298cad9c2e3ff78fc6326c73f9b94289

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Nihar Jindal
2. Bruno Clerckx
3. Andrea J. Goldsmith
4. Taesang Yoo
5. Yijie Mao
6. Jinhong Yuan
7. D. J. Love
8. Giuseppe Caire

In Computer Networks and Communications

1. Nihar Jindal
2. Giuseppe Caire
3. Robert W. Heath
4. Bruno Clerckx
5. Yijie Mao
6. Andrea J. Goldsmith
7. Mari Kobayashi
8. Niranjay Ravindran

In Electrical and Electronic Engineering

1. Nihar Jindal
2. Robert W. Heath
3. Giuseppe Caire
4. Andrea J. Goldsmith
5. Bruno Clerckx
6. Taesang Yoo
7. Yijie Mao
8. Mari Kobayashi

Citations in the corpus

• An overview of limited feedback in wireless communication systems (2008, unknown): “Closed-form analysis is also possible when the chann el follows a spatially uncorrelated Rayleigh model [24].”
• MIMO broadcast channels with finite rate feedback (2006, methodology): “The distribution and expectation of sin(2)(∠(hi, ĥi)) is given in [16], yielding (c).”
• MIMO Broadcast Channels With Finite-Rate Feedback (2006, methodology): “There has also been very recent work characterizing the error performance of point-to-point multiple-input, single-output (MISO) systems utilizing RVQ [29].”
• A Primer on Rate-Splitting Multiple Access: Tutorial, Myths, and Frequently Asked Questions (2022, background): “Ideally, the number of feedback bits should scale linearly with the number of users [93], [237]–[239].”
• Multi-Antenna Downlink Channels with Limited Feedback and User Selection (2007, methodology): “To see how tight the upper bound is, in numerical results in Section VI, we evaluate the performance of our proposed system using both the above quantization cell upper bound (QUB) and an actual codebook design based on a random vector quantization (RVQ) scheme [14], [24], [25].”
• Multiuser MIMO Achievable Rates With Downlink Training and Channel State Feedback (2007, background): “In [24] and [26], it is shown that for a random ensemble of quantization codebooks referred to as random vector quantization (RVQ), obtained by generating quantization vectors independently and uniformly distributed on the unit sphere in (see [26] and references therein), the average (angular) disto”