57 research outputs found
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
SYMBOL LEVEL PRECODING TECHNIQUES FOR HARDWARE AND POWER EFFICIENT WIRELESS TRANSCEIVERS
Large-scale antennas are crucial for next generation wireless communication
systems as they improve spectral efficiency, reliability and coverage compared to
the traditional ones that are employing antenna arrays of few elements. However,
the large number of antenna elements leads to a big increase in power
consumption of conventional fully digital transceivers due to the one Radio
Frequency (RF) chain / per antenna element requirement. The RF chains include
a number of different components among which are the Digital-to-Analog
Converters (DACs)/Analog-to-Digital Converters (ADCs) that their power consumption
increases exponential with the resolution they support. Motivated by
this, in this thesis, a number of different architectures are proposed with the
view to reduce the power consumption and the hardware complexity of the
transceiver. In order to optimize the transmission of data through them, corresponding
symbol level precoding (SLP) techniques were developed for the proposed
architectures. SLP is a technique that mitigates multi-user interference
(MUI) by designing the transmitted signals using the Channel State Information
and the information-bearing symbols. The cases of both frequency flat and
frequency selective channels were considered.
First, three different power efficient transmitter designs for transmission over
frequency flat channels and their respective SLP schemes are considered. The
considered systems tackle the high hardware complexity and power consumption
of existing SLP techniques by reducing or completely eliminating fully digital
RF chains. The precoding design is formulated as a constrained least squares
problem and efficient algorithmic solutions are developed via the Coordinate
Descent method.
Next, the case of frequency selective channels is considered. To this end,
Constant Envelope precoding in a Multiple Input Multiple Output Orthogonal
Frequency Division Multiplexing system (CE MIMO-OFDM) is considered.
In CE MIMO-OFDM the transmitted signals for each antenna are designed
to have constant amplitude regardless of the channel realization and the information
symbols that must be conveyed to the users. This facilitates the
use of power-efficient components, such as phase shifters and non-linear power
amplifiers. The precoding problem is firstly formulated as a least-squares problem
with a unit-modulus constraint and solved using an algorithm based on
the coordinate descent (CCD) optimization framework and then, after reformulating
the problem into an unconstrained non-linear least squares problem,
a more computationally efficient solution using the Gauss-Newton algorithm is
presented.
Then, CE MIMO-OFDM is considered for a system with low resolution
DACs. The precoding design problem is formulated as a mixed discrete- continuous
least-squares optimization one which is NP-hard. An efficient low complexity
solution is developed based also on the CCD optimization framework.
Finally, a precoding scheme is presented for OFDM transmission in MIMO
systems based on one-bit DACs and ADCs at the transmitter’s and the receiver’s
end, respectively, as a way to reduce the total power consumption. The objective
of the precoding design is to mitigate the effects of one-bit quantization and
the problem is formulated and then is split into two NP hard least squares optimization problems. Algorithmic solutions are developed for the solution of the latter problems, based on the CCD framework
Multi-user Downlink Beamforming using Uplink Downlink Duality with CEQs for Frequency Selective Channels
High-resolution fully digital transceivers are infeasible at millimeter-wave
(mmWave) due to their increased power consumption, cost, and hardware
complexity. The use of low-resolution converters is one possible solution to
realize fully digital architectures at mmWave. In this paper, we consider a
setting in which a fully digital base station with constant envelope quantized
(CEQ) digital-to-analog converters on each radio frequency chain communicates
with multiple single antenna users with individual
signal-to-quantization-plus-interference-plus-noise ratio (SQINR) constraints
over frequency selective channels. We first establish uplink downlink duality
for the system with CEQ hardware constraints and OFDM-based transmission
considered in this paper. Based on the uplink downlink duality principle, we
present a solution to the multi-user multi-carrier beamforming and power
allocation problem that maximizes the minimum SQINR over all users and
sub-carriers. We then present a per sub-carrier version of the originally
proposed solution that decouples all sub-carriers of the OFDM waveform
resulting in smaller sub-problems that can be solved in a parallel manner. Our
numerical results based on 3GPP channel models generated from Quadriga
demonstrate improvements in terms of ergodic sum rate and ergodic minimum rate
over state-of-the-art linear solutions. We also show improved performance over
non-linear solutions in terms of the coded bit error rate with the increased
flexibility of assigning individual user SQINRs built into the proposed
framework.Comment: arXiv admin note: text overlap with arXiv:2206.1442
Efficient Quantized Constant Envelope Precoding for Multiuser Downlink Massive MIMO Systems
Quantized constant envelope (QCE) precoding, a new transmission scheme that
only discrete QCE transmit signals are allowed at each antenna, has gained
growing research interests due to its ability of reducing the hardware cost and
the energy consumption of massive multiple-input multiple-output (MIMO)
systems. However, the discrete nature of QCE transmit signals greatly
complicates the precoding design. In this paper, we consider the QCE precoding
problem for a massive MIMO system with phase shift keying (PSK) modulation and
develop an efficient approach for solving the constructive interference (CI)
based problem formulation. Our approach is based on a custom-designed
(continuous) penalty model that is equivalent to the original discrete problem.
Specifically, the penalty model relaxes the discrete QCE constraint and
penalizes it in the objective with a negative -norm term, which leads
to a non-smooth non-convex optimization problem. To tackle it, we resort to our
recently proposed alternating optimization (AO) algorithm. We show that the AO
algorithm admits closed-form updates at each iteration when applied to our
problem and thus can be efficiently implemented. Simulation results demonstrate
the superiority of the proposed approach over the existing algorithms.Comment: 5 pages, 5 figures, submitted for possible publicatio
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
A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions
IEEE Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area
Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions
Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area
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