Vector quantization and signal compression
Vector quantization and signal compression
Digitally Assisted Analog Circuits
IEEE Micro
An analytical constant modulus algorithm
IEEE Transactions on Signal Processing
Reduced-rank adaptive filtering
IEEE Transactions on Signal Processing
Optimum phase-only adaptive nulling
IEEE Transactions on Signal Processing
Direction finding with fewer receivers via time-varyingpreprocessing
IEEE Transactions on Signal Processing
Variable-phase-shift-based RF-baseband codesign for MIMO antenna selection
IEEE Transactions on Signal Processing
Quantized overcomplete expansions in IRN: analysis, synthesis, and algorithms
IEEE Transactions on Information Theory
A multistage representation of the Wiener filter based on orthogonal projections
IEEE Transactions on Information Theory
Antenna selection in MIMO systems
IEEE Communications Magazine
Analog-to-digital converter survey and analysis
IEEE Journal on Selected Areas in Communications
From theory to practice: an overview of MIMO space-time coded wireless systems
IEEE Journal on Selected Areas in Communications
| Hi-index | 35.68 |
In multiple-input multiple-output (MIMO) systems, the use of many radio frequency (RF) and analog-to-digital converter (ADC) chains at the receiver is costly. Analog beamformers operating in the RF domain can reduce the number of antenna signals to a feasible number of baseband channels. Subsequently, digital beamforming is used to capture the desired user signal. In this paper, we consider the design of the analog and digital beamforming coefficients, for the case of narrowband signals. We aim to cancel interfering signals in the analog domain, thus minimizing the required ADC resolution. For a given resolution, we will propose the optimal analog beamformer to minimize the mean squared error between the desired user and its receiver estimate. Practical analog beamformers employ only a quantized number of phase shifts. For this case, we propose a design technique to successively approximate the desired overall beamformer by a linear combination of implementable analog beamformers. Finally, an online channel estimation technique is introduced to estimate the required statistics of the wireless channel on which the optimal beamformers are based.