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1.	Balatsoukas-Stimming, Alexios, et al. (author) Neural-Network Optimized 1-bit Precoding for Massive MU-MIMO 2019 In: IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC. ; 2019-July Conference paper (peer-reviewed)abstract Base station (BS) architectures for massive multiuser (MU) multiple-input multiple-output (MIMO) wireless systems are equipped with hundreds of antennas to serve tens of users on the same time-frequency channel. The immense number of BS antennas incurs high system costs, power, and interconnect bandwidth. To circumvent these obstacles, sophisticated MU precoding algorithms that enable the use of 1-bit DACs have been proposed. Many of these precoders feature parameters that are, traditionally, tuned manually to optimize their performance. We propose to use deep-learning tools to automatically tune such 1-bit precoders. Specifically, we optimize the biConvex 1-bit PrecOding (C2PO) algorithm using neural networks. Compared to the original C2PO algorithm, our neural-network optimized (NNO-)C2PO achieves the same error-rate performance at 2× lower complexity. Moreover, by training NNO-C2PO for different channel models, we show that 1-bit precoding can be made robust to vastly changing propagation conditions.
2.	Becirovic, Ema, 1992- (author) Signal Processing Aspects of Massive MIMO 2022 Doctoral thesis (other academic/artistic)abstract Massive MIMO (multiple-input-multiple-output) is a technology that uses an antenna array with a massive number of antennas at the wireless base station. It has shown widespread benefit and has become an inescapable solution for the future of wireless communication. The mainstream literature focuses on cases when high data rates for a handful of devices are of priority. In reality, due to the diversity of applications, no solution is one-size-fits-all. This thesis provides signal-processing solutions for three challenging situations. The first challenging situation deals with the acquisition of channel estimates when the signal-to-noise-ratio (SNR) is low. The benefits of massive MIMO are unlocked by having good channel estimates. By the virtue of reciprocity in time-division duplex, the estimates are obtained by transmitting pilots on the uplink. However, if the uplink SNR is low, the quality of the channel estimates will suffer and consequently the spectral efficiency will also suffer. This thesis studies two cases where the channel estimates can be improved: one where the device is stationary such that the channel is constant over many coherence blocks and one where the device has access to accurate channel estimates such that it can design its pilots based on the knowledge of the channel. The thesis provides algorithms and methods that exploit the aforementioned structures which improve the spectral efficiency. Next, the thesis considers massive machine-type communications, where a large number of simple devices, such as sensors, are communicating with the base station. This thesis provides a quantitative study on which type of benefits massive MIMO can provide for this communication scenario — many devices can be spatially multiplexed and their battery life can be increased. Further, activity detection is also studied and it is shown that the channel hardening and favorable propagation properties of massive MIMO can be exploited to design efficient detection algorithms. The third part of the thesis studies a more specific application of massive MIMO, namely federated learning. In federated learning, the goal is for the devices to collectively train a machine learning model based on their local data by only transmitting model updates to the base station. Sum channel estimation has been advocated for blind over-the-air federated learning since fewer communication resources are required to obtain such estimates. On the contrary, this thesis shows that individually estimating each device's channel can save a huge number of resources owing to the fact that it allows for individual processing such as gradient sparsification which in turn saves a huge number of resources that compensates for the channel estimation overhead.
3.	Castaneda, Oscar, et al. (author) 1-bit Massive MU-MIMO Precoding in VLSI 2017 In: IEEE Journal on Emerging and Selected Topics in Circuits and Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 2156-3365 .- 2156-3357. ; 7:4, s. 508-522 Journal article (peer-reviewed)abstract Massive multi-user (MU) multiple-input multiple-output (MIMO) will be a core technology in fifth-generation (5G) wireless systems as it offers significant improvements in spectral efficiency compared to existing multi-antenna technologies. The presence of hundreds of antenna elements at the base station (BS), however, results in excessively high hardware costs and power consumption, and requires high interconnect throughput between the baseband-processing unit and the radio unit. Massive MU-MIMO that uses low-resolution analog-to-digital and digital-toanalog converters (DACs) has the potential to address all these issues. In this paper, we focus on downlink precoding for massive MU-MIMO systems with 1-bit DACs at the BS. The objective is to design precoders that simultaneously mitigate MU interference and quantization artifacts. We propose two nonlinear 1-bit precoding algorithms and corresponding very large-scale integration (VLSI) designs. Our algorithms rely on biconvex relaxation, which enables the design of efficient 1-bit precoding algorithms that achieve superior error-rate performance compared with that of linear precoding algorithms followed by quantization. To showcase the efficacy of our algorithms, we design VLSI architectures that enable efficient 1-bit precoding for massive MU-MIMO systems, in which hundreds of antennas serve tens of user equipments. We present corresponding field-programmable gate array (FPGA) reference implementations to demonstrate that 1-bit precoding enables reliable and high-rate downlink data transmission in practical systems.
4.	Castaneda, Oscar, et al. (author) Finite-alphabet MMSE equalization for all-digital massive MU-MIMO mmWave communications 2020 In: IEEE Journal on Selected Areas in Communications. - 0733-8716 .- 1558-0008. ; 38:9, s. 2128 -2141 Journal article (peer-reviewed)abstract We propose finite-alphabet equalization, a new paradigm that restricts the entries of the spatial equalization matrix to low-resolution numbers, enabling high-throughput, low-power, and low-cost hardware equalizers. To minimize the performance loss of this paradigm, we introduce FAME, short for finite-alphabet minimum mean-square error (MMSE) equalization, which is able to significantly outperform a naïve quantization of the linear MMSE matrix. We develop efficient algorithms to approximately solve the NP-hard FAME problem and showcase that near-optimal performance can be achieved with equalization coefficients quantized to only 1-3 bits for massive multi-user multiple-input multiple-output (MU-MIMO) millimeter-wave (mmWave) systems. We provide very-large scale integration (VLSI) results that demonstrate a reduction in equalization power and area by at least a factor of 3.9× and 5.8×, respectively.
5.	Castaneda, Oscar, et al. (author) Finite-Alphabet Wiener Filter Precoding for mmWave Massive MU-MIMO Systems 2019 In: Conference Record - Asilomar Conference on Signals, Systems and Computers. - 1058-6393. ; 2019-November, s. 178-183 Conference paper (peer-reviewed)abstract Power consumption of multi-user (MU) precoding is a major concern in all-digital massive MU multiple-input multiple-output (MIMO) base-stations with hundreds of antenna elements operating at millimeter-wave (mmWave) frequencies. We propose to replace part of the linear Wiener filter (WF) precoding matrix by a finite-alphabet WF precoding (FAWP) matrix, which enables the use of low-precision hardware that consumes low power and area. To minimize the performance loss of our approach, we present methods that efficiently compute FAWP matrices that best mimic the WF precoder. Our results show that FAWP matrices approach infinite-precision error-rate and error-vector magnitude performance with only 3-bit precoding weights, even when operating in realistic mmWave channels. Hence, FAWP is a promising approach to substantially reduce power consumption and silicon area in all-digital mmWave massive MU-MIMO systems.
6.	Castañeda, Oscar, et al. (author) Hardware-Friendly Two-Stage Spatial Equalization for All-Digital mmWave Massive MU-MIMO 2020 In: Conference Record - Asilomar Conference on Signals, Systems and Computers. - 1058-6393. ; 2020-November, s. 388-392 Conference paper (peer-reviewed)abstract Next generation wireless communication systems are expected to combine millimeter-wave communication with massive multi-user multiple-input multiple-output technology. All-digital base-station implementations for such systems need to process high-dimensional data at extremely high rates, which results in excessively high power consumption. In this paper, we propose two-stage spatial equalizers that first reduce the problem dimension by means of a hardware-friendly, low-resolution linear transform followed by spatial equalization on a lower-dimensional signal. We consider adaptive and non-adaptive dimensionality reduction strategies and demonstrate that the proposed two-stage spatial equalizers are able to approach the performance of conventional linear spatial equalizers that directly operate on high-dimensional data, while offering the potential to reduce the power consumption of spatial equalization.
7.	Castañeda, Oscar, et al. (author) High-Bandwidth Spatial Equalization for mmWave Massive MU-MIMO with Processing-in-Memory 2020 In: IEEE Transactions on Circuits and Systems II: Express Briefs. - 1549-7747 .- 1558-3791. ; 67:5, s. 891-895 Journal article (peer-reviewed)abstract All-digital basestation (BS) architectures enable superior spectral efficiency compared to hybrid solutions in massive multi-user MIMO systems. However, supporting large bandwidths with all-digital architectures at mmWave frequencies is challenging as traditional baseband processing would result in excessively high power consumption and large silicon area. The recently-proposed concept of finite-alphabet equalization is able to address both of these issues by using equalization matrices that contain low-resolution entries to lower the power and complexity of high-throughput matrix-vector products in hardware. In this brief, we explore two different finite-alphabet equalization hardware implementations that tightly integrate the memory and processing elements: (i) a parallel array of multiply-accumulate (MAC) units and (ii) a bit-serial processing-in-memory (PIM) architecture. Our all-digital VLSI implementation results in 28nm CMOS show that the bit-serial PIM architecture reduces the area and power consumption up to a factor of 2× and 3×, respectively, when compared to a parallel MAC array that operates at the same throughput.
8.	Castañeda, Oscar, et al. (author) Resolution-Adaptive All-Digital Spatial Equalization for mmWave Massive MU-MIMO 2021 In: IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC. ; 2021-September, s. 386-390 Conference paper (peer-reviewed)abstract All-digital basestation (BS) architectures for millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO), which equip each radio-frequency chain with dedicated data converters, have advantages in spectral efficiency, flexibility, and baseband-processing simplicity over hybrid analog-digital solutions. For all-digital architectures to be competitive with hybrid solutions in terms of power consumption, novel signal-processing methods and baseband architectures are necessary. In this paper, we demonstrate that adapting the resolution of the analog-to-digital converters (ADCs) and spatial equalizer of an all-digital system to the communication scenario (e.g., the number of users, modulation scheme, and propagation conditions) enables orders-of-magnitude power savings for realistic mmWave channels. For example, for a 256-BS-antenna 16-user system supporting 1 GHz bandwidth, a traditional baseline architecture designed for a 64-user worst-case scenario would consume 23 W in 28 nm CMOS for the ADC array and the spatial equalizer, whereas a resolution-adaptive architecture is able to reduce the power consumption by 6.7×.
9.	Castañeda, Oscar, et al. (author) Soft-Output Finite Alphabet Equalization for mmWave Massive MIMO 2020 In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. ; 2020-May, s. 1764-1767 Conference paper (peer-reviewed)abstract Nxt-generation wireless systems are expected to combine millimeter-wave (mmWave) and massive multi-user multiple-input multiple-output (MU-MIMO) technologies to deliver high data-rates. These technologies require the basestations (BSs) to process high-dimensional data at extreme rates, which results in high power dissipation and system costs. Finite-alphabet equalization has been proposed recently to reduce the power consumption and silicon area of uplink spatial equalization circuitry at the BS by coarsely quantizing the equalization matrix. In this work, we improve upon finite-alphabet equalization by performing unbiased estimation and soft-output computation for coded systems. By simulating a massive MU-MIMO system that uses orthogonal frequency-division multiplexing and per-user convolutional coding, we show that soft-output finite-alphabet equalization delivers competitive error-rate performance using only 1 to 3 bits per entry of the equalization matrix, even for challenging mmWave channels.
10.	Castaneda, Oscar, et al. (author) VLSI Design of a 3-bit Constant-Modulus Precoder for Massive MU-MIMO 2018 In: Proceedings - IEEE International Symposium on Circuits and Systems. - 0271-4310. ; 2018-May Conference paper (peer-reviewed)abstract Fifth-generation (5G) cellular systems will build on massive multi-user (MU) multiple-input multiple-output (MIMO) technology to attain high spectral efficiency. However, having hundreds of antennas and radio-frequency (RF) chains at the base station (BS) entails prohibitively high hardware costs and power consumption. This paper proposes a novel nonlinear precoding algorithm for the massive MU-MIMO downlink in which each RF chain contains an 8-phase (3-bit) constantmodulus transmitter, enabling the use of low-cost and powerefficient analog hardware. We present a high-throughput VLSI architecture and show implementation results on a Xilinx Virtex-7 FPGA. Compared to a recently-reported nonlinear precoder for BS designs that use two 1 -bit digital-to-analog converters per RF chain, our design enables up to 3:75 dB transmit power reduction at no more than a 2.7x increase in FPGA resources.
11.	Ettefagh, Yasaman, 1989, et al. (author) All-Digital Massive MIMO Uplink and Downlink Rates under a Fronthaul Constraint 2019 In: Conference Record - Asilomar Conference on Signals, Systems and Computers. - 1058-6393. - 9781728143002 ; 2019-November, s. 416-420 Conference paper (peer-reviewed)abstract We characterize the rate achievable in a bidirectional quasi-static link where several user equipments communicate with a massive multiple-input multiple-output base station (BS). In the considered setup, the BS operates in full-digital mode, the physical size of the antenna array is limited, and there exists a rate constraint on the fronthaul interface connecting the (possibly remote) radio head to the digital baseband processing unit. Our analysis enables us to determine the optimal resolution of the analog-todigital and digital-to-analog converters as well as the optimal number of active antenna elements to be used in order to maximize the transmission rate on the bidirectional link, for a given constraint on the outage probability and on the fronthaul rate. We investigate both the case in which perfect channel-state information is available, and the case in which channel-state information is acquired through pilot transmission, and is, hence, imperfect. For the second case, we present a novel rate expression that relies on the generalized mutual-information framework.
12.	Ettefagh, Yasaman, 1989, et al. (author) Performance of Quantized Massive MIMO with Fronthaul Rate Constraint over Quasi-Static Channels 2023 In: IEEE Access. - 2169-3536 .- 2169-3536. ; 11, s. 56935-56950 Journal article (peer-reviewed)abstract We provide a rigorous framework for characterizing and numerically evaluating the error probability achievable in the uplink and downlink of a fully digital quantized multiuser multiple-input multiple-output (MIMO) system. We assume that the system operates over a quasi-static channel that does not change across the finite-length transmitted codewords, and only imperfect channel state information (CSI) is available at the base station (BS) and at the user equipments. The need for the novel framework developed in this paper stems from the fact that, for the quasi-static scenario, commonly used signal-to-interference-and-distortion-ratio expressions that depend on the variance of the channel estimation error are not relatable to any rigorous information-theoretic achievable-rate bound. We use our framework to investigate how the performance of a fully digital massive MIMO system subject to a fronthaul rate constraint, which imposes a limit on the number of samples per second produced by the analog-to-digital and digital-to-analog converters (ADCs and DACs), depends on the number of BS antennas and on the precision of the ADCs and DACs. In particular, we characterize, for a given fronthaul constraint, the trade-off between the number of antennas and the resolution of the data converters, and discuss how this trade-off is influenced by the accuracy of the available CSI. Our framework captures explicitly the cost, in terms of spectral efficiency, of pilot transmission—an overhead that the outage capacity, the classic asymptotic metric used in this scenario, cannot capture. We present extensive numerical results that validate the accuracy of the proposed framework and allow us to characterize, for a given fronthaul constraint, the optimal number of antennas and the optimal resolution of the converters as a function of the transmitted power and of the available CSI.
13.	Gustavsson, Ulf, 1975, et al. (author) Implementation challenges and opportunities in beyond-5G and 6G communication 2021 In: IEEE Journal of Microwaves. - 2692-8388. ; 1:1, s. 86-100 Journal article (peer-reviewed)abstract As 5G New Radio (NR) is being rolled out, research effort is being focused on the evolution of what is to come in the post-5G era. In order to meet the diverse requirements of future wireless communication in terms of increased capacity and reduced latency, technologies such as distributed massive Multiple-Input Multiple-Output (MIMO), sub-millimeter wave and Tera-hertz spectrum become technology components of interest. Furthermore, to meet the demands on connectivity anywhere at anytime, non-terrestrial satellite networks will be needed, which brings about challenges both in terms of implementation as well as deployment. Finally, scaling up massive Internet-of-Things (IoT), energy harvesting and Simultaneous Wireless Information and Power Transfer (SWIPT) is foreseen to become important enablers when deploying a large amount of small, low-power radios. In this paper, we will discuss some of the important opportunities these technologies bring, and the challenges faced by the microwave and wireless communication communities.
14.	Hu, Anzhong, et al. (author) EVM Analysis of Distributed Massive MIMO with 1-Bit Radio-Over-Fiber Fronthaul 2024 In: IEEE Transactions on Communications. - 0090-6778 .- 1558-0857. ; In Press Journal article (peer-reviewed)abstract We analyze the uplink performance of a distributed massive multiple-input multiple-output (MIMO) architecture in which the remotely located access points (APs) are connected to a central processing unit via a fiber-optical fronthaul carrying a dithered and 1-bit quantized version of the received radio-frequency (RF) signal. The innovative feature of the proposed architecture is that no down-conversion is performed at the APs. This eliminates the need to equip the APs with local oscillators, which may be difficult to synchronize. Under the assumption that a constraint is imposed on the amount of data that can be exchanged across the fiber-optical fronthaul, we investigate the tradeoff between spatial oversampling, defined in terms of the total number of APs, and temporal oversampling, defined in terms of the oversampling factor selected at the central processing unit, to facilitate the recovery of the transmitted signal from 1-bit samples of the RF received signal. Using the so-called error-vector magnitude (EVM) as performance metric, we shed light on the optimal design of the dither signal, and quantify, for a given number of APs, the minimum fronthaul rate required for our proposed distributed massive MIMO architecture to outperform a standard co-located massive MIMO architecture in terms of EVM.
15.	Jacobsson, Sven, 1990, et al. (author) All-digital massive MIMO with a fronthaul constraint 2018 In: IEEE Workshop Stat. Signal Process. (SSP). Conference paper (peer-reviewed)
16.	Jacobsson, Sven, 1990, et al. (author) Linear Precoding With Low-Resolution DACs for Massive MU-MIMO-OFDM Downlink 2019 In: IEEE Transactions on Wireless Communications. - 1558-2248 .- 1536-1276. ; 18:3, s. 1595-1609 Journal article (peer-reviewed)abstract 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 the 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 considering the inherent spatial and temporal correlations caused by low-precision DACs.
17.	Jacobsson, Sven, 1990, et al. (author) Massive MU-MIMO-OFDM Downlink with One-Bit DACs and Linear Precoding 2018 In: Proceedings - IEEE Global Communications Conference, GLOBECOM. - 2334-0983 .- 2576-6813. ; 2018-January, s. 1-6 Conference paper (peer-reviewed)abstract 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.
18.	Jacobsson, Sven, 1990, et al. (author) Massive MU-MIMO-OFDM uplink with direct RF-sampling and 1-Bit ADCs 2019 In: 2019 IEEE Globecom Workshops, GC Wkshps 2019 - Proceedings. Conference paper (peer-reviewed)abstract Advances in analog-to-digital converter (ADC) technology have opened up the possibility to directly digitize wideband radio frequency (RF) signals, avoiding the need for analog down- conversion. In this work, we consider an orthogonal frequency- division multiplexing (OFDM)-based massive multi-user (MU) multiple-input multiple-output (MIMO) uplink system that relies on direct RF-sampling at the base station and digitizes the received RF signals with 1-bit ADCs. Using Bussgang's theorem, we provide an analytical expression for the error-vector magnitude (EVM) achieved by digital down-conversion and zero-forcing combining. Our results demonstrate that direct RF-sampling 1-bit ADCs enables low EVM and supports high-order constellations in the massive MU-MIMO- OFDM uplink.
19.	Jacobsson, Sven, 1990, et al. (author) Massive MU-MIMO-OFDM Uplink with Hardware Impairments: Modeling and Analysis 2018 In: Conference Record - Asilomar Conference on Signals, Systems and Computers. - 1058-6393. ; 2018-October, s. 1829-1835 Conference paper (peer-reviewed)abstract © 2018 IEEE. We study the impact of hardware impairments at the base station (BS) of an orthogonal frequency-division multiplexing (OFDM)-based massive multiuser (MU) multiple-input multiple-output (MIMO) uplink system. We leverage Bussgang's theorem to develop accurate models for the distortions caused by nonlinear low-noise amplifiers, local oscillators with phase noise, and oversampling finite-resolution analog-to-digital converters. By combining the individual effects of these hardware models, we obtain a composite model for the BS-side distortion caused by nonideal hardware that takes into account its inherent correlation in time, frequency, and across antennas. We use this composite model to analyze the impact of BS-side hardware impairments on the performance of realistic massive MU-MIMO-OFDM uplink systems.
20.	Jacobsson, Sven, 1990, et al. (author) Massive multiuser MIMO downlink with low- resolution converters 2018 In: International Zurich Seminar on Information and Communication (IZS 2018) Proceedings. Conference paper (peer-reviewed)abstract 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.
21.	Jacobsson, Sven, 1990, et al. (author) MSE-Optimal 1-Bit Precoding for Multiuser MIMO Via Branch and Bound 2018 In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. ; 2018-April, s. 3589-3593 Conference paper (peer-reviewed)abstract In this paper, we solve the sum mean-squared error (MSE)-optimal 1-bit quantized precoding problem exactly for small-to-moderate sized multiuser multiple-input multiple-output (MU-MIMO) systems via branch and bound. To this end, we reformulate the original NP-hard precoding problem as a tree search and deploy a number of strategies that improve the pruning efficiency without sacrificing optimality. We evaluate the error-rate performance and the complexity of the resulting 1-bit branch-and-bound (BB-1) precoder, and compare its efficacy to that of existing, suboptimal algorithms for 1-bit precoding in MU-MIMO systems.
22.	Jacobsson, Sven, 1990, et al. (author) Nonlinear 1-bit precoding for massive MU-MIMO with higher-order modulation 2017 In: Conference Record - Asilomar Conference on Signals, Systems and Computers. - 1058-6393. ; , s. 763-767 Conference paper (peer-reviewed)abstract Massive multi-user (MU) multiple-input multiple-output (MIMO) is widely believed to be a core technology for the upcoming fifth-generation (5G) wireless communication standards. The use of low-precision digital-to-analog converters (DACs) in MU-MIMO base stations is of interest because it reduces the power consumption, system costs, and raw baseband data rates. In this paper, we develop novel algorithms for downlink precoding in massive MU-MIMO systems with 1-bit DACs that support higher-order modulation schemes such as 8-PSK or 16-QAM. Specifically, we present low-complexity nonlinear precoding algorithms that achieve low error rates when combined with blind or training-based channel-estimation algorithms at the user equipment. These results are in stark contrast to linear-quantized precoding algorithms, which suffer from a high error floor if used with high-order modulation schemes and 1-bit DACs
23.	Jacobsson, Sven, 1990, et al. (author) Nonlinear Precoding for Phase-Quantized Constant-Envelope Massive MU-MIMO-OFDM 2018 In: 2018 25TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS (ICT). - 9781538623213 ; , s. 367-372 Conference paper (peer-reviewed)abstract We propose a nonlinear phase-quantized constant-envelope precoding algorithm for the massive multi-user (MU) multiple-input multiple-output (MIMO) downlink. Specifically, we adapt the squared-infinity norm Douglas-Rachford splitting (SQUID) precoder to systems that use oversampling digital-to-analog converters (DACs) at the base station (BS) and orthogonal frequency-division multiplexing (OFDM) to communicate over frequency-selective channels. We demonstrate that the proposed SQUID-OFDM precoder is able to generate transmit signals that are constrained to constant envelope, which enables the use of power-efficient analog radio-frequency circuitry at the BS. By quantizing the phase of the resulting constant-envelope signal, we obtain a finite-cardinality transmit signal that can be synthesized by low-resolution (e.g., 1-bit) DACs. We use error-rate simulations to demonstrate the superiority of SQUID-OFDM over linear-quantized precoders for massive MU-MIMO-OFDM systems.
24.	Jacobsson, Sven, 1990, et al. (author) On Out-of-Band Emissions of Quantized Precoding in Massive MU-MIMO-OFDM 2017 In: Conference Record of the Asilomar Conference on Signals Systems and Computers. - 1058-6393. - 9781538618233 ; 2017-October, s. 21-26 Conference paper (peer-reviewed)abstract 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 perfor- mance 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.
25.	Jacobsson, Sven, 1990, et al. (author) One-Bit Massive MIMO: Channel Estimation and High-Order Modulations 2015 In: 2015 IEEE International Conference on Communication Workshop, ICCW 2015. - 9781467363051 ; , s. 1304-1309 Conference paper (peer-reviewed)abstract We investigate the information-theoretic throughout achievable on a fading communication link when the receiver is equipped with one-bit analog-to-digital converters (ADCs). The analysis is conducted for the setting where neither the transmitter nor the receiver have a priori information on the realization of the fading channels. This means that channel-state information needs to be acquired at the receiver on the basis of the one-bit quantized channel outputs. We show that least-squares (LS) channel estimation combined with joint pilot and data processing is capacity achieving in the single-user, single-receive-antenna case. We also investigate the achievable uplink throughput in a massive multiple-input multiple-output system where each element of the antenna array at the receiver base-station feeds a one-bit ADC. We show that LS channel estimation and maximum-ratio combining are sufficient to support both multiuser operation and the use of high-order constellations. This holds in spite of the severe nonlinearity introduced by the one-bit ADCs.
26.	Jacobsson, Sven, 1990, et al. (author) Quantized Precoding for Massive MU-MIMO 2017 In: IEEE Transactions on Communications. - 0090-6778 .- 1558-0857. ; 65:11, s. 4670-4684 Journal article (peer-reviewed)abstract Massive multiuser (MU) multiple-input multiple-output (MIMO) is foreseen to be one of the key technologies in fifth-generation wireless communication systems. In this paper, we investigate the problem of downlink precoding for a narrowband massive MU-MIMO system with low-resolution digital-to-analog converters (DACs) at the base station (BS). We analyze the performance of linear precoders, such as maximal-ratio transmission and zero-forcing, subject to coarse quantization. Using Bussgang's theorem, we derive a closed-form approximation on the rate achievable under such coarse quantization. Our results reveal that the performance attainable with infinite-resolution DACs can be approached using DACs having only 3-4 bits of resolution, depending on the number of BS antennas and the number of user equipments (UEs). For the case of 1-bit DACs, we also propose novel nonlinear precoding algorithms that significantly outperform linear precoders at the cost of an increased computational complexity. Specifically, we show that nonlinear precoding incurs only a 3 dB penalty compared with the infinite-resolution case for an uncoded bit-error rate of 10-3, in a system with 128 BS antennas that uses 1-bit DACs and serves 16 single-antenna UEs. In contrast, the penalty for linear precoders is about 8dB.
27.	Jacobsson, Sven, 1990, et al. (author) Throughput Analysis of Massive MIMO Uplink With Low-Resolution ADCs 2017 In: IEEE Transactions on Wireless Communications. - 1558-2248 .- 1536-1276. ; 16:6, s. 4038-4051 Journal article (peer-reviewed)abstract We investigate the uplink throughput achievable by a multiple-user (MU) massive multiple-input multiple-output (MIMO) system, in which the base station is equipped with a large number of low-resolution analog-to-digital converters (ADCs). Our focus is on the case where neither the transmitter nor the receiver have any a priori channel state information. This implies that the fading realizations have to be learned through pilot transmission followed by channel estimation at the receiver, based on coarsely quantized observations. We propose a novel channel estimator, based on Bussgang's decomposition, and a novel approximation to the rate achievable with finite-resolution ADCs, both for the case of finite-cardinality constellations and of Gaussian inputs, that is accurate for a broad range of system parameters. Through numerical results, we illustrate that, for the 1-bit quantized case, pilot-based channel estimation together with maximal-ratio combing, or zero-forcing detection enables reliable multi-user communication with high-order constellations, in spite of the severe nonlinearity introduced by the ADCs. Furthermore, we show that the rate achievable in the infinite-resolution (no quantization) case can be approached using ADCs with only a few bits of resolution. We finally investigate the robustness of low-ADC-resolution MU-MIMO uplink against receive power imbalances between the different users, caused for example by imperfect power control.
28.	Jacobsson, Sven, 1990, et al. (author) Timing and Frequency Synchronization for 1-bit Massive MU-MIMO-OFDM Downlink 2019 In: IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC. - 9781538665282 ; 2019-July Conference paper (peer-reviewed)abstract We consider timing and frequency synchronization for the massive multiuser (MU) multiple-input multiple-output (MIMO) downlink where 1-bit digital-to-analog converters (DACs) are used at the base station (BS). We focus on the practically relevant scenario in which orthogonal-frequency division multiplexing (OFDM) is used to communicate over frequency-selective channels. Our contributions are twofold. First, we use Bussgang's theorem to analyze the impact on performance caused by timing and frequency offsets in the presence of 1-bit DACs at the BS. Second, we demonstrate the efficacy of the widely used Schmidl-Cox synchronization algorithm. Our results demonstrate that the 1-bit massive MU-MIMO-OFDM downlink is resilient against timing and frequency offsets.
29.	Kaja, Magdalena, et al. (author) Resonant laser ionization of neptunium: investigation on excitation schemes and the first ionization potential 2024 In: EUROPEAN PHYSICAL JOURNAL D. - 1434-6060 .- 1434-6079. ; 78:5 Journal article (peer-reviewed)abstract The atomic structure of neptunium (Np) was investigated by two-step resonance ionization spectroscopy. The study involved exploring ground-state transitions as well as following transitions to high-lying states just below the ionization potential (IP) or auto-ionizing states above the IP. That resulted in the identification of two-step ionization schemes, suitable for trace analysis and nuclear structure investigations. The lifetimes of two excited states located at 25,342.48 cm(-1) and 25,277.64 cm(-1) were determined as 230(12) ns and 173(9) ns, respectively. Because of the absence of Rydberg series in wide-ranging spectra recorded, the first IP was determined through the field ionization of high-lying, weakly-bound states using a well-controlled static electric field. By applying the saddle-point model, an IP value of 50,535.54(15) cm(-1) [6.265608(19) eV] was derived. This value agrees with the current literature value of 50,535(2) cm(-1), while providing a more than ten times higher precision.
30.	Kant, Shashi (author) Optimization and Learning for Large-Scale MIMO-OFDM Wireless Systems : Theory, Algorithms, and Applications 2022 Doctoral thesis (other academic/artistic)abstract The requirements for next-generation wireless communications networks, particularly fifth-generation (5G) and beyond, are driven by at least three broad use cases. These include enhanced mobile broadband services to support extremely high data rates in terms of network or per user in both uplink and downlink, massive machine-type communications to accommodate massive internet-of-things applications, and critical machine-type communications to handle mission-critical applications that require ultra-high reliability and low latency.These new-generation wireless communication systems adopt orthogonal frequency division multiplexing (OFDM) with cyclic prefix and multiple antennas at the transmitter and receiver (MIMO). There are many attractive characteristics of OFDM, namely robustness to the adverse effects of time dispersion due to multipath fading, simplicity in equalization, and flexibility in supporting both low and high symbol rates---thereby supporting a variety of various quality-of-service requirements.It has been known for a long time that OFDM has problems with high out-of-band emissions (OOBE) and high peak-to-average-power ratio (PAPR). The OOBE must be adequately suppressed since high OOBE causes significant interference in the adjacent channels. Furthermore, high PAPR typically requires expensive linear radio frequency (RF) transmitter components and consequently costly digital predistortion to manage and mitigate OOBE resulting from the distortion caused by RF components, e.g., power amplifiers. Additionally, there are practical 5G standard constraints, which necessitate using only data-carrying subcarriers for OOBE and PAPR reduction. Hence, it is of utmost importance to reduce OOBE and PAPR for MIMO-OFDM-based systems and mitigate/minimize the signal distortion at the receiver(s) to meet the new generation systems’ requirements encompassing various use cases.In this thesis, we seek principled approaches to tackle the distortion-based OOBE and PAPR reduction problems. More specifically, we present optimization formulations for these well-known issues in large-scale MIMO-OFDM-based systems, such as 5G New Radio (NR), and future extensions thereof. Unfortunately, these problems cannot be solved via a general-purpose optimization solver since these off-the-shelf solvers typically employ interior-point-based methods, which have prohibitive complexity for state-of-the-art radio hardware systems. Hence, we propose large-scale optimization techniques to tackle these problems resulting in implementation-friendly algorithms. More concretely, we develop (near) optimal and computationally-efficient data-dependent solutions by proposing a type of three-operator alternating direction method of multipliers (ADMM) method that essentially employs a divide-and-conquer approach to solve the huge and cumbersome OOBE and PAPR reduction problems in large-scale MIMO-OFDM-based systems. Moreover, in the last part of the thesis, we also investigate the application of our proposed three-operator ADMM (TOP-ADMM) for federated learning (FL) over networks that capitalize on the potentially rich datasets generated at the physical layer and/or RF hardware of a base station located near an edge server.In summary, this thesis develops principled, implementation-friendly, and standards-agnostic algorithms for distortion-based OOBE and PAPR reduction algorithms using first-order optimization algorithms, which provide insights into the trade-off between computational complexities and in-band and out-of-band performance. Furthermore, we develop a novel yet simple TOP-ADMM first-order algorithm suitable for tackling centralized and distributed optimization problems. Additionally, this thesis studies the feasibility of the TOP-ADMM algorithm for edge FL exploiting rich datasets available at the base station(s) besides (private) datasets at the users. Finally, this thesis may provide input to the systemization and implementation of large-scale MIMO-OFDM-based wireless communication systems.
31.	Marti, Gian, et al. (author) Hybrid Jammer Mitigation for All-Digital mmWave Massive MU-MIMO 2021 In: Conference Record - Asilomar Conference on Signals, Systems and Computers. - 1058-6393. - 9781665458283 ; 2021-October Conference paper (peer-reviewed)abstract Low-resolution analog-to-digital converters (ADCs) simplify the design of millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO) base-stations, but increase vulnerability to jamming attacks. As a remedy, we propose HERMIT (short for Hybrid jammER MITigation), a method that combines a hardware-friendly adaptive analog transform with a corresponding digital equalizer: The analog transform removes most of the jammer’s energy prior to data conversion; the digital equalizer suppresses jammer residues while detecting the legitimate transmit data. We provide theoretical results that establish the optimal analog transform as a function of the user equipments' and the jammer’s channels. Using simulations with mmWave channel models, we demonstrate the superiority of HERMIT compared both to purely digital jammer mitigation as well as to a recent hybrid method that mitigates jammer interference with a nonadaptive analog transform.
32.	Pope, Graeme, et al. (author) Real-Time Principal Component Pursuit 2011 In: Proc. Asilomar Conf. Signals, Syst., Comput. Pacific Grove CA, U.S.A., Nov. 2011. Conference paper (peer-reviewed)abstract Robust principal component analysis (RPCA) deals with the decomposition of a matrix into a low-rank matrix and a sparse matrix. Such a decomposition finds, for example, applica- tions in video surveillance or face recognition. One effective way to solve RPCA problems is to use a convex optimization method known as principal component pursuit (PCP). The corresponding algorithms have, however, prohibitive computational complexity for certain applications that require real-time processing. In this paper we propose a variety of methods that significantly reduce the computational complexity. Furthermore, we perform a systematic analysis of the performance/complexity tradeoffs underlying PCP. For synthetic data, we show that our methods re- sult in a speedup of more than 365 times compared to a reference C implementation at only a small loss in terms of recovery error. To demonstrate the effectiveness of our approach, we consider foreground/background separation for video surveillance, where our methods enable real-time processing of a 640×480 color video stream at 12 frames per second (fps) using a quad-core CPU.
33.	Seethaler, Dominik, et al. (author) On the Complexity Distribution of Sphere Decoding 2011 In: IEEE Transactions on Information Theory. - : IEEE. - 0018-9448 .- 1557-9654. ; 57:9, s. 5754-5768 Journal article (peer-reviewed)abstract We analyze the (computational) complexity distribution of sphere decoding (SD) for random infinite lattices. In particular, we show that under fairly general assumptions on the statistics of the lattice basis matrix, the tail behavior of the SD complexity distribution is fully determined by the inverse volume of the fundamental regions of the underlying lattice. Particularizing this result to N x M, N ≥ M, i.i.d. circularly symmetric complex Gaussian lattice basis matrices, we find that the corresponding complexity distribution is of Pareto-type with tail exponent given by N-M+1. A more refined analysis reveals that the corresponding average complexity of SD is infinite for N = M and finite for N >; M. Finally, for i.i.d. circularly symmetric complex Gaussian lattice basis matrices, we analyze SD preprocessing techniques based on lattice-reduction (such as the LLL algorithm or layer-sorting according to the V-BLAST algorithm) and regularization. In particular, we show that lattice-reduction does not improve the tail exponent of the complexity distribution while regularization results in a SD complexity distribution with tails that decrease faster than polynomial.
34.	Studer, Christoph, et al. (author) PAR-Aware Large-Scale Multi-User MIMO-OFDM Downlink 2013 In: IEEE Journal on Selected Areas in Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 0733-8716 .- 1558-0008. ; 31:2, s. 303-313 Journal article (peer-reviewed)abstract We investigate an orthogonal frequency-division multiplexing (OFDM)-based downlink transmission scheme for large-scale multi-user (MU) multiple-input multiple-output (MIMO) wireless systems. The use of OFDM causes a high peak-to-average (power) ratio (PAR), which necessitates expensive and power-inefficient radio-frequency (RF) components at the base station. In this paper, we present a novel downlink transmission scheme, which exploits the massive degrees-of-freedom available in large-scale MU-MIMO-OFDM systems to achieve low PAR. Specifically, we propose to jointly perform MU precoding, OFDM modulation, and PAR reduction by solving a convex optimization problem. We develop a corresponding fast iterative truncation algorithm (FITRA) and show numerical results to demonstrate tremendous PAR-reduction capabilities. The significantly reduced linearity requirements eventually enable the use of low-cost RF components for the large-scale MU-MIMO-OFDM downlink.
35.	Studer, Christoph, et al. (author) PAR-aware multi-user precoder for the large-scale MIMO-OFDM downlink 2012 Conference paper (peer-reviewed)abstract We consider an orthogonal frequency-division multiplexing (OFDM)-based downlink transmission scheme for large-scale multi-user (MU) multiple-input multiple-output (MIMO) wireless systems. In order to transmit signals with low peak-to-average (power) ratio (PAR), we propose to exploit the massive degrees-of-freedom available in large-scale MU-MIMO-OFDM systems. Specifically, we jointly perform MU precoding, OFDM modulation, and PAR reduction by solving a convex optimization problem at the base station. Numerical results demonstrate tremendous PAR-reduction capabilities of the proposed method, which eventually enables us to use low-cost RF components for the large-scale MU-MIMO-OFDM downlink.
36.	Studer, Christoph, et al. (author) Quantized Massive MU-MIMO-OFDM Uplink 2016 In: IEEE Transactions on Communications. - 0090-6778 .- 1558-0857. ; 64:6, s. 2387-2399 Journal article (peer-reviewed)abstract Coarse quantization at the base station (BS) of a massive multi-user (MU) multiple-input multiple-output (MIMO) wireless system promises significant power and cost savings. Coarse quantization also enables significant reductions of the raw analog-to-digital converter data that must be transferred from a spatially separated antenna array to the baseband processing unit. The theoretical limits as well as practical transceiver algorithms for such quantized MU-MIMO systems operating over frequency-flat, narrowband channels have been studied extensively. However, the practically relevant scenario where such communication systems operate over frequency-selective, wideband channels is less well understood. This paper investigates the uplink performance of a quantized massive MU-MIMO system that deploys orthogonal frequency-division multiplexing (OFDM) for wideband communication. We propose new algorithms for quantized maximum a posteriori channel estimation and data detection, and we study the associated performance/quantization tradeoffs. Our results demonstrate that coarse quantization (e.g., four to six bits, depending on the ratio between the number of BS antennas and the number of users) in massive MU-MIMO-OFDM systems entails virtually no performance loss compared with the infinite-precision case at no additional cost in terms of baseband processing complexity.
37.	Zhang, Chuan, et al. (author) Guest Editorial Circuits, Systems, and Algorithms for Beyond 5G and Toward 6G 2021 In: IEEE Open Journal of Circuits and Systems. - 2644-1225. ; 2, s. 223-225 Journal article (other academic/artistic)abstract This special section of the IEEE OPEN JOURNAL OF CIRCUITS AND SYSTEMS (OJCAS) is dedicated to highlight the state-of-the-art research progress on circuits, systems, and algorithms associated with the design of beyond 5G (B5G) and 6G wireless systems.

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