2,720 research outputs found
Reciprocity Calibration for Massive MIMO: Proposal, Modeling and Validation
This paper presents a mutual coupling based calibration method for
time-division-duplex massive MIMO systems, which enables downlink precoding
based on uplink channel estimates. The entire calibration procedure is carried
out solely at the base station (BS) side by sounding all BS antenna pairs. An
Expectation-Maximization (EM) algorithm is derived, which processes the
measured channels in order to estimate calibration coefficients. The EM
algorithm outperforms current state-of-the-art narrow-band calibration schemes
in a mean squared error (MSE) and sum-rate capacity sense. Like its
predecessors, the EM algorithm is general in the sense that it is not only
suitable to calibrate a co-located massive MIMO BS, but also very suitable for
calibrating multiple BSs in distributed MIMO systems.
The proposed method is validated with experimental evidence obtained from a
massive MIMO testbed. In addition, we address the estimated narrow-band
calibration coefficients as a stochastic process across frequency, and study
the subspace of this process based on measurement data. With the insights of
this study, we propose an estimator which exploits the structure of the process
in order to reduce the calibration error across frequency. A model for the
calibration error is also proposed based on the asymptotic properties of the
estimator, and is validated with measurement results.Comment: Submitted to IEEE Transactions on Wireless Communications,
21/Feb/201
On Low-Resolution ADCs in Practical 5G Millimeter-Wave Massive MIMO Systems
Nowadays, millimeter-wave (mmWave) massive multiple-input multiple-output
(MIMO) systems is a favorable candidate for the fifth generation (5G) cellular
systems. However, a key challenge is the high power consumption imposed by its
numerous radio frequency (RF) chains, which may be mitigated by opting for
low-resolution analog-to-digital converters (ADCs), whilst tolerating a
moderate performance loss. In this article, we discuss several important issues
based on the most recent research on mmWave massive MIMO systems relying on
low-resolution ADCs. We discuss the key transceiver design challenges including
channel estimation, signal detector, channel information feedback and transmit
precoding. Furthermore, we introduce a mixed-ADC architecture as an alternative
technique of improving the overall system performance. Finally, the associated
challenges and potential implementations of the practical 5G mmWave massive
MIMO system {with ADC quantizers} are discussed.Comment: to appear in IEEE Communications Magazin
Soft-Decision-Driven Channel Estimation for Pipelined Turbo Receivers
We consider channel estimation specific to turbo equalization for
multiple-input multiple-output (MIMO) wireless communication. We develop a
soft-decision-driven sequential algorithm geared to the pipelined turbo
equalizer architecture operating on orthogonal frequency division multiplexing
(OFDM) symbols. One interesting feature of the pipelined turbo equalizer is
that multiple soft-decisions become available at various processing stages. A
tricky issue is that these multiple decisions from different pipeline stages
have varying levels of reliability. This paper establishes an effective
strategy for the channel estimator to track the target channel, while dealing
with observation sets with different qualities. The resulting algorithm is
basically a linear sequential estimation algorithm and, as such, is
Kalman-based in nature. The main difference here, however, is that the proposed
algorithm employs puncturing on observation samples to effectively deal with
the inherent correlation among the multiple demapper/decoder module outputs
that cannot easily be removed by the traditional innovations approach. The
proposed algorithm continuously monitors the quality of the feedback decisions
and incorporates it in the channel estimation process. The proposed channel
estimation scheme shows clear performance advantages relative to existing
channel estimation techniques.Comment: 11 pages; IEEE Transactions on Communications 201
- …