46 research outputs found
On Out-of-Band Emissions of Quantized Precoding in Massive MU-MIMO-OFDM
We analyze out-of-band (OOB) emissions in the massive multi-user (MU)
multiple-input multiple-output (MIMO) downlink. We focus on systems in which
the base station (BS) is equipped with low-resolution digital-to-analog
converters (DACs) and orthogonal frequency-division multiplexing (OFDM) is used
to communicate to the user equipments (UEs) over frequency-selective channels.
We demonstrate that analog filtering in combination with simple
frequency-domain digital predistortion (DPD) at the BS enables a significant
reduction of OOB emissions, but degrades the
signal-to-interference-noise-and-distortion ratio (SINDR) at the UEs and
increases the peak-to-average power ratio (PAR) at the BS. We use Bussgang's
theorem to characterize the tradeoffs between OOB emissions, SINDR, and PAR,
and to study the impact of analog filters and DPD on the error-rate performance
of the massive MU-MIMO-OFDM downlink. Our results show that by carefully tuning
the parameters of the analog filters, one can achieve a significant reduction
in OOB emissions with only a moderate degradation of error-rate performance and
PAR.Comment: Presented at the 2017 Asilomar Conference on Signals, Systems, and
Computers, 6 page
Linear Precoding with Low-Resolution DACs for Massive MU-MIMO-OFDM Downlink
We consider the downlink of a massive multiuser (MU) multiple-input
multiple-output (MIMO) system in which the base station (BS) is equipped with
low-resolution digital-to-analog converters (DACs). In contrast to most
existing results, we assume that the system operates over a frequency-selective
wideband channel and uses orthogonal frequency division multiplexing (OFDM) to
simplify equalization at the user equipments (UEs). Furthermore, we consider
the practically relevant case of oversampling DACs. We theoretically analyze
the uncoded bit error rate (BER) performance with linear precoders (e.g., zero
forcing) and quadrature phase-shift keying using Bussgang's theorem. We also
develop a lower bound on the information-theoretic sum-rate throughput
achievable with Gaussian inputs, which can be evaluated in closed form for the
case of 1-bit DACs. For the case of multi-bit DACs, we derive approximate, yet
accurate, expressions for the distortion caused by low-precision DACs, which
can be used to establish lower bounds on the corresponding sum-rate throughput.
Our results demonstrate that, for a massive MU-MIMO-OFDM system with a
128-antenna BS serving 16 UEs, only 3--4 DAC bits are required to achieve an
uncoded BER of 10^-4 with a negligible performance loss compared to the
infinite-resolution case at the cost of additional out-of-band emissions.
Furthermore, our results highlight the importance of taking into account the
inherent spatial and temporal correlations caused by low-precision DACs
Massive MU-MIMO-OFDM Downlink with One-Bit DACs and Linear Precoding
Massive multiuser (MU) multiple-input multiple- output (MIMO) is foreseen to
be a key technology in future wireless communication systems. In this paper, we
analyze the downlink performance of an orthogonal frequency division
multiplexing (OFDM)-based massive MU-MIMO system in which the base station (BS)
is equipped with 1-bit digital-to-analog converters (DACs). Using Bussgang's
theorem, we characterize the performance achievable with linear precoders (such
as maximal-ratio transmission and zero forcing) in terms of bit error rate
(BER). Our analysis accounts for the possibility of oversampling the
time-domain transmit signal before the DACs. We further develop a lower bound
on the information-theoretic sum-rate throughput achievable with Gaussian
inputs.
Our results suggest that the performance achievable with 1-bit DACs in a
massive MU-MIMO-OFDM downlink are satisfactory provided that the number of BS
antennas is sufficiently large
Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions
Massive MIMO is a compelling wireless access concept that relies on the use
of an excess number of base-station antennas, relative to the number of active
terminals. This technology is a main component of 5G New Radio (NR) and
addresses all important requirements of future wireless standards: a great
capacity increase, the support of many simultaneous users, and improvement in
energy efficiency. Massive MIMO requires the simultaneous processing of signals
from many antenna chains, and computational operations on large matrices. The
complexity of the digital processing has been viewed as a fundamental obstacle
to the feasibility of Massive MIMO in the past. Recent advances on
system-algorithm-hardware co-design have led to extremely energy-efficient
implementations. These exploit opportunities in deeply-scaled silicon
technologies and perform partly distributed processing to cope with the
bottlenecks encountered in the interconnection of many signals. For example,
prototype ASIC implementations have demonstrated zero-forcing precoding in real
time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing
of 8 terminals). Coarse and even error-prone digital processing in the antenna
paths permits a reduction of consumption with a factor of 2 to 5. This article
summarizes the fundamental technical contributions to efficient digital signal
processing for Massive MIMO. The opportunities and constraints on operating on
low-complexity RF and analog hardware chains are clarified. It illustrates how
terminals can benefit from improved energy efficiency. The status of technology
and real-life prototypes discussed. Open challenges and directions for future
research are suggested.Comment: submitted to IEEE transactions on signal processin
Massive Multi-Antenna Communications with Low-Resolution Data Converters
Massive multi-user (MU) multiple-input multiple-output (MIMO) will be a core technology in future cellular communication systems. In massive MU-MIMO systems, the number of antennas at the base station (BS) is scaled up by several orders of magnitude compared to traditional multi-antenna systems with the goals of enabling large gains in capacity and energy efficiency. However, scaling up the number of active antenna elements at the BS will lead to significant increases in power consumption and system costs unless power-efficient and low-cost hardware components are used. In this thesis, we investigate the performance of massive MU-MIMO systems for the case when the BS is equipped with low-resolution data converters.First, we consider the massive MU-MIMO uplink for the case when the BS uses low-resolution analog-to-digital converters (ADCs) to convert the received signal into the digital domain. Our focus is on the case where neither the transmitter nor the receiver have any a priori channel state information (CSI), which implies that the channel realizations have to be learned through pilot transmission followed by BS-side channel estimation, based on coarsely quantized observations. We derive a low-complexity channel estimator and present lower bounds and closed-form approximations for the information-theoretic rates achievable with the proposed channel estimator together with conventional linear detection algorithms. Second, we consider the massive MU-MIMO downlink for the case when the BS uses low-resolution digital-to-analog converters (DACs) to generate the transmit signal. We derive lower bounds and closed-form approximations for the achievable rates with linear precoding under the assumption that the BS has access to perfect CSI. We also propose novel nonlinear precoding algorithms that are shown to significantly outperform linear precoding for the extreme case of 1-bit DACs. Specifically, for the case of symbol-rate 1-bit DACs and frequency-flat channels, we develop a multitude of nonlinear precoders that trade between performance and complexity. We then extend the most promising nonlinear precoders to the case of oversampling 1-bit DACs and orthogonal frequency-division multiplexing for operation over frequency-selective channels.Third, we extend our analysis to take into account other hardware imperfections such as nonlinear amplifiers and local oscillators with phase noise.The results in this thesis suggest that the resolution of the ADCs and DACs in massive MU-MIMO systems can be reduced significantly compared to what is used in today\u27s state-of-the-art communication systems, without significantly reducing the overall system performance
Massive multiuser MIMO downlink with low- resolution converters
In this review paper, we analyze the downlink of a massive multiuser multiple-input multiple-output system in which the base station is equipped with low-resolution digital-to-analog converters (DACs). Using Bussgang’s theorem, we characterize the sum-rate achievable with a Gaussian codebook and scaled nearestneighbor decoding at the user equipments (UE). For the case of 1-bit DACs, we show how to evaluate the sum-rate using Van Vleck’s arcsine law. For the case of multi-bit DACs, for which the sum-rate cannot be expressed in closed-form, we present two approximations. The first one, which is obtained by ignoring the overload (or clipping) distortion caused by the DACs, turns out to be accurate provided that one can adapt the dynamic range of the quantizer to the received-signal strength so as to avoid clipping. The second approximation, which is obtained by modeling the distortion noise as a white process, both in time and space, is accurate whenever the resolution of the DACs is sufficiently high and when the oversampling ratio is small. We conclude the paper by discussing extensions to orthogonal frequency-division multiplexing systems; we also touch upon the problem of out-of-band emissions in lowprecision-DAC architectures
A Spatial Sigma-Delta Approach to Mitigation of Power Amplifier Distortions in Massive MIMO Downlink
In massive multiple-input multiple-output (MIMO) downlink systems, the
physical implementation of the base stations (BSs) requires the use of cheap
and power-efficient power amplifiers (PAs) to avoid high hardware cost and high
power consumption. However, such PAs usually have limited linear amplification
ranges. Nonlinear distortions arising from operation beyond the linear
amplification ranges can significantly degrade system performance. Existing
approaches to handle the nonlinear distortions, such as digital predistortion
(DPD), typically require accurate knowledge, or acquisition, of the PA transfer
function. In this paper, we present a new concept for mitigation of the PA
distortions. Assuming a uniform linear array (ULA) at the BS, the idea is to
apply a Sigma-Delta () modulator to spatially shape the PA
distortions to the high-angle region. By having the system operating in the
low-angle region, the received signals are less affected by the PA distortions.
To demonstrate the potential of this spatial approach, we study
the application of our approach to the multi-user MIMO-orthogonal frequency
division modulation (OFDM) downlink scenario. A symbol-level precoding (SLP)
scheme and a zero-forcing (ZF) precoding scheme, with the new design
requirement by the spatial approach being taken into account,
are developed. Numerical simulations are performed to show the effectiveness of
the developed precoding schemes
Two-step multiuser equalization for hybrid mmWave massive MIMO GFDM systems
Although millimeter-wave (mmWave) and massive multiple input multiple output
(mMIMO) can be considered as promising technologies for future mobile communications (beyond
5G or 6G), some hardware limitations limit their applicability. The hybrid analog-digital architecture
has been introduced as a possible solution to avoid such issues. In this paper, we propose a two-step
hybrid multi-user (MU) equalizer combined with low complexity hybrid precoder for wideband
mmWave mMIMO systems, as well as a semi-analytical approach to evaluate its performance.
The new digital non-orthogonal multi carrier modulation scheme generalized frequency division
multiplexing (GFDM) is considered owing to its efficient performance in terms of achieving higher
spectral efficiency, better control of out-of-band (OOB) emissions, and lower peak to average power
ratio (PAPR) when compared with the orthogonal frequency division multiplexing (OFDM) access
technique. First, a low complexity analog precoder is applied on the transmitter side. Then, at the
base station (BS), the analog coefficients of the hybrid equalizer are obtained by minimizing the
mean square error (MSE) between the hybrid approach and the full digital counterpart. For the
digital part, zero-forcing (ZF) is used to cancel the MU interference not mitigated by the analog
part. The performance results show that the performance gap of the proposed hybrid scheme to the
full digital counterpart reduces as the number of radio frequency (RF) chains increases. Moreover,
the theoretical curves almost overlap with the simulated ones, which show that the semi-analytical
approach is quite accurate.publishe