Capacity and power allocation for fading MIMO channels with channel estimation error
By Taesang Yoo, Andrea J. Goldsmith. IEEE Transactions on Information Theory, 2006
831 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/24a1962d2a357db2bc2c8c557260d0e7cc33949d
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In Computer Networks and Communications
- Emil Björnson
- Luca Sanguinetti
- Jakob Hoydis
- Merouane Debbah
- Michail Matthaiou
- Zhiguo Ding
- Alessio Zappone
- Chau Yuen
In Electrical and Electronic Engineering
- Emil Björnson
- Merouane Debbah
- Zhiguo Ding
- Luca Sanguinetti
- Chau Yuen
- Yuanwei Liu
- Rui Zhang
- Chongwen Huang
Citations in the corpus
- Secure Transmission With Artificial Noise Over Fading Channels: Achievable Rate and Optimal Power Allocation (2010, background): “The existing study on the point-to-point channel capacity, e.g. in [29], showed that the temporal power optimization gives little capacity gain provided that the spatial power optimization is used.”
- Knowledge-Aided (Potentially Cognitive) Transmit Signal and Receive Filter Design in Signal-Dependent Clutter (2013, background): “Precisely, the following proposition can be proved [49], [50].”
- Millimeter Wave Communications for Future Mobile Networks (2017, methodology): “However, the precoder/combiner design is considerably different from the precoding/combining optimizations in [163] for the conventional fully digital MIMO systems, due to the special hardware constraints in hybrid architecture of mmWave systems.”
- Deep Learning for UL/DL Channel Calibration in Generic Massive MIMO Systems (2019, background): “For example, nonlinear solid-state devices, like signal power and low noise amplifiers, are modeled as memoryless devices whose nonlinearity appears when the instantaneous input signal power fluctuates and approaches the saturation level of the device [28].”
- On the Performance of Non-orthogonal Multiple Access Systems With Partial Channel Information (2016, methodology): “• Imperfect CSI: We assume the channel estimation error model presented in [17], [18], where the BS and the users have an estimate of the channel and a priori knowledge of the variance of the estimation error.”
- Massive MIMO Systems With Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits (2013, methodology): “Proof: This theorem is obtained by taking lower bounds on the mutual information in the same way as was previously proposed in [5] and [41].”