316 research outputs found
mmWave Massive MIMO with Simple RF and Appropriate DSP
There is considerable interest in the combined use of millimeter-wave
(mmwave) frequencies and arrays of massive numbers of antennas (massive MIMO)
for next-generation wireless communications systems. A symbiotic relationship
exists between these two factors: mmwave frequencies allow for densely packed
antenna arrays, and hence massive MIMO can be achieved with a small form
factor; low per-antenna SNR and shadowing can be overcome with a large array
gain; steering narrow beams or nulls with a large array is a good match for the
line-of-sight (LOS) or near-LOS mmwave propagation environments, etc.. However,
the cost and power consumption for standard implementations of massive MIMO
arrays at mmwave frequencies is a significant drawback to rapid adoption and
deployment. In this paper, we examine a number of possible approaches to reduce
cost and power at both the basestation and user terminal, making up for it with
signal processing and additional (cheap) antennas. These approaches include
lowresolution Analog-to-Digital Converters (ADCs), wireless local oscillator
distribution networks, spatial multiplexing and multistreaming instead of
higher-order modulation etc.. We will examine the potential of these approaches
in making mmwave massive MIMO a reality and discuss the requirements in terms
of digital signal processing (DSP).Comment: published in Asilomar 201
Minimum BER Precoding in 1-Bit Massive MIMO Systems
1-bit digital-to-analog (DACs) and analog-to-digital converters (ADCs) are
gaining more interest in massive MIMO systems for economical and computational
efficiency. We present a new precoding technique to mitigate the
inter-user-interference (IUI) and the channel distortions in a 1-bit downlink
MUMISO system with QPSK symbols. The transmit signal vector is optimized taking
into account the 1-bit quantization. We develop a sort of mapping based on a
look-up table (LUT) between the input signal and the transmit signal. The LUT
is updated for each channel realization. Simulation results show a significant
gain in terms of the uncoded bit-error-ratio (BER) compared to the existing
linear precoding techniques.Comment: Presented in IEEE SAM 2016, 10th-13th July 2016, Rio De Janeiro,
Brazi
Multiple Parameter Estimation With Quantized Channel Output
We present a general problem formulation for optimal parameter estimation
based on quantized observations, with application to antenna array
communication and processing (channel estimation, time-of-arrival (TOA) and
direction-of-arrival (DOA) estimation). The work is of interest in the case
when low resolution A/D-converters (ADCs) have to be used to enable higher
sampling rate and to simplify the hardware. An Expectation-Maximization (EM)
based algorithm is proposed for solving this problem in a general setting.
Besides, we derive the Cramer-Rao Bound (CRB) and discuss the effects of
quantization and the optimal choice of the ADC characteristic. Numerical and
analytical analysis reveals that reliable estimation may still be possible even
when the quantization is very coarse.Comment: 9 pages, 9 figures, International ITG Workshop on Smart Antennas -
WSA 2010, Bremen, German
Chromatic Dispersion Compensation Using Filter Bank Based Complex-Valued All-Pass Filter
A long-haul transmission of 100 Gb/s without optical chromatic-dispersion
(CD) compensation provides a range of benefits regarding cost effectiveness,
power budget, and nonlinearity tolerance. The channel memory is largely
dominated by CD in this case with an intersymbol-interference spread of more
than 100 symbol durations. In this paper, we propose CD equalization technique
based on nonmaximally decimated discrete Fourier transform (NMDFT) filter bank
(FB) with non-trivial prototype filter and complex-valued infinite impulse
response (IIR) all-pass filter per sub-band. The design of the sub-band IIR
all-pass filter is based on minimizing the mean square error (MSE) in group
delay and phase cost functions in an optimization framework. Necessary
conditions are derived and incorporated in a multi-step and multi-band
optimization framework to ensure the stability of the resulting IIR filter. It
is shown that the complexity of the proposed method grows logarithmically with
the channel memory, therefore, larger CD values can be tolerated with our
approach
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