97 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
Performance Analysis for Time-of-Arrival Estimation with Oversampled Low-Complexity 1-bit A/D Conversion
Analog-to-digtial (A/D) conversion plays a crucial role when it comes to the
design of energy-efficient and fast signal processing systems. As its
complexity grows exponentially with the number of output bits, significant
savings are possible when resorting to a minimum resolution of a single bit.
However, then the nonlinear effect which is introduced by the A/D converter
results in a pronounced performance loss, in particular for the case when the
receiver is operated outside the low signal-to-noise ratio (SNR) regime. By
trading the A/D resolution for a moderately faster sampling rate, we show that
for time-of-arrival (TOA) estimation under any SNR level it is possible to
obtain a low-complexity -bit receive system which features a smaller
performance degradation then the classical low SNR hard-limiting loss of
( dB). Key to this result is the employment of a lower bound for
the Fisher information matrix which enables us to approximate the estimation
performance for coarsely quantized receivers with correlated noise models in a
pessimistic way
Performance Analysis for Time-of-Arrival Estimation with Oversampled Low-Complexity 1-bit A/D Conversion
Analog-to-digtial (A/D) conversion plays a crucial role when it comes to the
design of energy-efficient and fast signal processing systems. As its
complexity grows exponentially with the number of output bits, significant
savings are possible when resorting to a minimum resolution of a single bit.
However, then the nonlinear effect which is introduced by the A/D converter
results in a pronounced performance loss, in particular for the case when the
receiver is operated outside the low signal-to-noise ratio (SNR) regime. By
trading the A/D resolution for a moderately faster sampling rate, we show that
for time-of-arrival (TOA) estimation under any SNR level it is possible to
obtain a low-complexity -bit receive system which features a smaller
performance degradation then the classical low SNR hard-limiting loss of
( dB). Key to this result is the employment of a lower bound for
the Fisher information matrix which enables us to approximate the estimation
performance for coarsely quantized receivers with correlated noise models in a
pessimistic way
Channel Estimation and Uplink Achievable Rates in One-Bit Massive MIMO Systems
This paper considers channel estimation and achievable rates for the uplink
of a massive multiple-input multiple-output (MIMO) system where the base
station is equipped with one-bit analog-to-digital converters (ADCs). By
rewriting the nonlinear one-bit quantization using a linear expression, we
first derive a simple and insightful expression for the linear minimum
mean-square-error (LMMSE) channel estimator. Then employing this channel
estimator, we derive a closed-form expression for the lower bound of the
achievable rate for the maximum ratio combiner (MRC) receiver. Numerical
results are presented to verify our analysis and show that our proposed LMMSE
channel estimator outperforms the near maximum likelihood (nML) estimator
proposed previously.Comment: 5 pages, 2 figures, the Ninth IEEE Sensor Array and Multichannel
Signal Processing Worksho
Limited Feedback in Multiple-Antenna Systems with One-Bit Quantization
Communication systems with low-resolution analog-to-digital-converters (ADCs)
can exploit channel state information at the transmitter (CSIT) and receiver.
This paper presents initial results on codebook design and performance analysis
for limited feedback systems with one-bit ADCs. Different from the
high-resolution case, the absolute phase at the receiver is important to align
the phase of the received signals when the received signal is sliced by one-bit
ADCs. A new codebook design for the beamforming case is proposed that
separately quantizes the channel direction and the residual phase.Comment: Asilomar Conference on Signals, Systems, and Computers 201
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