The Experts below are selected from a list of 7524 Experts worldwide ranked by ideXlab platform
Thomas L Marzetta - One of the best experts on this subject based on the ideXlab platform.
-
interference reduction in multi cell massive mimo systems with large Scale Fading precoding
IEEE Transactions on Information Theory, 2018Co-Authors: Alexei Ashikhmin, Thomas L MarzettaAbstract:A wireless massive multiple-input multiple-output (MIMO) system entails a large number of base station antennas serving a much smaller number of users, with large gains in spectral efficiency and energy efficiency compared with the conventional MIMO technology. Until recently, it was believed that as the number of base station antennas tends to infinity, the performance of such systems is limited by directed inter-cellular interference caused by unavoidable re-use of training sequences (pilot contamination) by users in different cells. We devise a new concept of large-Scale Fading precoding (LSFP) that leads to the effective elimination of inter-cell interference. The main idea of LSFP is that base stations linearly combine messages aimed at users from different cells that re-use the same training sequence. Crucially, the combining coefficients depend only on the large-Scale Fading coefficients between the users and the base stations. These coefficients change slowly and their number does not depend on the number of base station antennas. Thus, the traffic between base stations stays constant even if the number of antennas tends to infinity. Furthermore, we derive a capacity lower bound for massive MIMO systems with LSFP and a finite number of base station antennas. In this regime, mitigation of all types of interference, not only the pilot contamination, is required. We consider optimal and suboptimal LSFP precodings that take into account all sources of interference. Our simulations results show that LSFP provides significant gain even for the case of moderate number of base station antennas.
-
spatially stationary propagating random field model for massive mimo small Scale Fading
International Symposium on Information Theory, 2018Co-Authors: Thomas L MarzettaAbstract:The spatially uncorrelated Rayleigh small-Scale Fading model is a useful stochastic tool for analyzing multiple-antenna wireless communication systems, and, as experiments have shown, it often is a good approximation to physical propagation. However, the assumption that the propagating field is uncorrelated from one point in space to another breaks down when, for example, antenna spacings are smaller than one-half wavelength - a model defect typically addressed by assuming some spatial correlation. Spatial correlation can have huge effects even in the absence of close spacing between antennas. While an ad-hoc correlation versus distance, such as exponential, may add an element of realism to the model, in general it does not capture the peculiar “action at a distance” phenomena associated with the wave equation. The very desirable property of spatial stationarity can be retained, provided the spatial autocorrelation is chosen such that the complex Gaussian small-Scale Fading random field satisfies the homogeneous wave equation. The Fading model that is closest to iid Rayleigh Fading, and that is still consistent with the wave equation, has an autocorrelation equal to sinc(2πR/λ, corresponding to planewaves arriving uniformly from all directions, and having independent, equal variance complex Gaussian amplitudes. The contribution of this paper is twofold: first, a Fourier planewave representation that provides a computationally efficient way to generate samples of the random field, second, an inverse representation that enables the efficient computation of the joint likelihood of noisy measurements of the field over continuous segments of lines, planes, and volumes.
-
uplink interference reduction in large Scale antenna systems
IEEE Transactions on Communications, 2017Co-Authors: Ansuman Adhikary, Alexei Ashikhmin, Thomas L MarzettaAbstract:A massive MIMO system entails a large number (tens or hundreds) of base station antennas serving a much smaller number of terminals. These systems demonstrate large gains in spectral and energy efficiency compared with the conventional MIMO technology. As the number of antennas grows, the performance of a massive MIMO system gets limited by the interference caused by pilot contamination. Ashikhmin and Marzetta proposed (under the name of Pilot Contamination Precoding) large Scale Fading precoding (LSFP) and large Scale Fading decoding (LSFD) based on limited cooperation between base stations. They showed that zero-forcing LSFP and LSFD eliminate pilot contamination entirely and lead to an infinite throughput as the number of antennas grows. In this paper, we focus on the uplink and show that even in the case of a finite number of base station antennas, LSFD yields a very large performance gain. In particular, one of our algorithms gives a more than 140 fold increase in the 5% outage data transmission rate! We show that the performance can be improved further by optimizing the transmission powers of the users. Finally, we present decentralized LSFD that requires limited cooperation only between neighboring cells.
-
Performance of cell-free massive MIMO systems with MMSE and LSFD receivers
Conference Record - Asilomar Conference on Signals Systems and Computers, 2017Co-Authors: Elina Nayebi, Alexei Ashikhmin, Thomas L Marzetta, Bhaskar D. RaoAbstract:Cell-Free Massive MIMO comprises a large number of distributed single-antenna access points (APs) serving a much smaller number of users. There is no partitioning into cells and each user is served by all APs. In this paper, the uplink performance of cell-free systems with minimum mean squared error (MMSE) and large Scale Fading decoding (LSFD) receivers is investigated. The main idea of LSFD receiver is to maximize achievable throughput using only large Scale Fading coefficients between APs and users. Capacity lower bounds for MMSE and LSFD receivers are derived. An asymptotic approximation for signal-to-interference-plus-noise ratio (SINR) of MMSE receiver is derived as a function of large Scale Fading coefficients only. The obtained approximation is accurate even for a small number of antennas. MMSE and LSFD receivers demonstrate five-fold and two-fold gains respectively over matched filter (MF) receiver in terms of 5%-outage rate.
-
energy and spectral efficiency of very large multiuser mimo systems
IEEE Transactions on Communications, 2013Co-Authors: Hien Quoc Ngo, Erik G Larsson, Thomas L MarzettaAbstract:A multiplicity of autonomous terminals simultaneously transmits data streams to a compact array of antennas. The array uses imperfect channel-state information derived from transmitted pilots to extract the individual data streams. The power radiated by the terminals can be made inversely proportional to the square-root of the number of base station antennas with no reduction in performance. In contrast if perfect channel-state information were available the power could be made inversely proportional to the number of antennas. Lower capacity bounds for maximum-ratio combining (MRC), zero-forcing (ZF) and minimum mean-square error (MMSE) detection are derived. An MRC receiver normally performs worse than ZF and MMSE. However as power levels are reduced, the cross-talk introduced by the inferior maximum-ratio receiver eventually falls below the noise level and this simple receiver becomes a viable option. The tradeoff between the energy efficiency (as measured in bits/J) and spectral efficiency (as measured in bits/channel use/terminal) is quantified for a channel model that includes small-Scale Fading but not large-Scale Fading. It is shown that the use of moderately large antenna arrays can improve the spectral and energy efficiency with orders of magnitude compared to a single-antenna system.
Alexei Ashikhmin - One of the best experts on this subject based on the ideXlab platform.
-
interference reduction in multi cell massive mimo systems with large Scale Fading precoding
IEEE Transactions on Information Theory, 2018Co-Authors: Alexei Ashikhmin, Thomas L MarzettaAbstract:A wireless massive multiple-input multiple-output (MIMO) system entails a large number of base station antennas serving a much smaller number of users, with large gains in spectral efficiency and energy efficiency compared with the conventional MIMO technology. Until recently, it was believed that as the number of base station antennas tends to infinity, the performance of such systems is limited by directed inter-cellular interference caused by unavoidable re-use of training sequences (pilot contamination) by users in different cells. We devise a new concept of large-Scale Fading precoding (LSFP) that leads to the effective elimination of inter-cell interference. The main idea of LSFP is that base stations linearly combine messages aimed at users from different cells that re-use the same training sequence. Crucially, the combining coefficients depend only on the large-Scale Fading coefficients between the users and the base stations. These coefficients change slowly and their number does not depend on the number of base station antennas. Thus, the traffic between base stations stays constant even if the number of antennas tends to infinity. Furthermore, we derive a capacity lower bound for massive MIMO systems with LSFP and a finite number of base station antennas. In this regime, mitigation of all types of interference, not only the pilot contamination, is required. We consider optimal and suboptimal LSFP precodings that take into account all sources of interference. Our simulations results show that LSFP provides significant gain even for the case of moderate number of base station antennas.
-
uplink interference reduction in large Scale antenna systems
IEEE Transactions on Communications, 2017Co-Authors: Ansuman Adhikary, Alexei Ashikhmin, Thomas L MarzettaAbstract:A massive MIMO system entails a large number (tens or hundreds) of base station antennas serving a much smaller number of terminals. These systems demonstrate large gains in spectral and energy efficiency compared with the conventional MIMO technology. As the number of antennas grows, the performance of a massive MIMO system gets limited by the interference caused by pilot contamination. Ashikhmin and Marzetta proposed (under the name of Pilot Contamination Precoding) large Scale Fading precoding (LSFP) and large Scale Fading decoding (LSFD) based on limited cooperation between base stations. They showed that zero-forcing LSFP and LSFD eliminate pilot contamination entirely and lead to an infinite throughput as the number of antennas grows. In this paper, we focus on the uplink and show that even in the case of a finite number of base station antennas, LSFD yields a very large performance gain. In particular, one of our algorithms gives a more than 140 fold increase in the 5% outage data transmission rate! We show that the performance can be improved further by optimizing the transmission powers of the users. Finally, we present decentralized LSFD that requires limited cooperation only between neighboring cells.
-
Performance of cell-free massive MIMO systems with MMSE and LSFD receivers
Conference Record - Asilomar Conference on Signals Systems and Computers, 2017Co-Authors: Elina Nayebi, Alexei Ashikhmin, Thomas L Marzetta, Bhaskar D. RaoAbstract:Cell-Free Massive MIMO comprises a large number of distributed single-antenna access points (APs) serving a much smaller number of users. There is no partitioning into cells and each user is served by all APs. In this paper, the uplink performance of cell-free systems with minimum mean squared error (MMSE) and large Scale Fading decoding (LSFD) receivers is investigated. The main idea of LSFD receiver is to maximize achievable throughput using only large Scale Fading coefficients between APs and users. Capacity lower bounds for MMSE and LSFD receivers are derived. An asymptotic approximation for signal-to-interference-plus-noise ratio (SINR) of MMSE receiver is derived as a function of large Scale Fading coefficients only. The obtained approximation is accurate even for a small number of antennas. MMSE and LSFD receivers demonstrate five-fold and two-fold gains respectively over matched filter (MF) receiver in terms of 5%-outage rate.
Theodore S Rappaport - One of the best experts on this subject based on the ideXlab platform.
-
28 GHz Millimeter-Wave Ultrawideband Small-Scale Fading Models in Wireless Channels
2016 IEEE 83rd Vehicular Technology Conference (VTC Spring), 2016Co-Authors: Mathew Khalil Samimi, George R Maccartney, Theodore S RappaportAbstract:This paper presents small-Scale Fading measurements for 28 GHz outdoor millimeter-wave ultrawideband channels using directional horn antennas at the transmitter and receiver. Power delay profiles were measured at half-wavelength spatial increments over a local area (33 wavelengths) on a linear track in two orthogonal receiver directions in a typical base-to-mobile scenario with fixed transmitter and receiver antenna beam pointing directions. The voltage path amplitudes are shown to follow a Rician distribution, with K-factor ranging from 9 - 15 dB and 5 - 8 dB in line of sight (LOS) and non-line of sight (NLOS) for a vertical-to-vertical co- polarized antenna scenario, respectively, and from 3 - 7 dB in both LOS and NLOS vertical-to- horizontal cross-polarized antenna scenario. The average spatial autocorrelation functions of individual multipath components reveal that signal amplitudes reach a correlation of 0 after 2 and 5 wavelengths in LOS and NLOS co-polarized V-V antenna scenarios. The models provided are useful for recreating path gain statistics of millimeter- wave wideband channel impulse responses over local areas, for the study of multi-element antenna simulations and channel estimation algorithms.
-
theory of multipath shape factors for small Scale Fading wireless channels
IEEE Transactions on Antennas and Propagation, 2000Co-Authors: Gregory D Durgin, Theodore S RappaportAbstract:This paper presents a new theory of multipath shape factors that greatly simplifies the description of small-Scale Fading statistics of a wireless receiver. A method is presented for reducing a multipath channel with arbitrary spatial complexity to three shape factors that have simple intuitive geometrical interpretations. Furthermore, these shape factors are shown to describe the statistics of received signal fluctuations in a Fading multipath channel. Analytical expressions for level-crossing rate, average fade duration, envelope autocovariance, and coherence distance are all derived using the new shape factor theory and then applied to several classical examples for comparison.
-
basic relationship between multipath angular spread and narrowband Fading in wireless channels
Electronics Letters, 1998Co-Authors: Gregory D Durgin, Theodore S RappaportAbstract:A novel relationship between the azimuthal distribution of multipath power and narrowband small-Scale Fading characteristics is developed. The fundamental relationship is useful for studying adaptive arrays, smart antennas, equalisation, diversity, and any other wireless technology or concept that depends on the spatial characteristics of radiowave and microwave propagation.
-
wireless communications principles and practice
1996Co-Authors: Theodore S RappaportAbstract:From the Publisher: The indispensable guide to wireless communicationsnow fully revised and updated! Wireless Communications: Principles and Practice, Second Edition is the definitive modern text for wireless communications technology and system design. Building on his classic first edition, Theodore S. Rappaport covers the fundamental issues impacting all wireless networks and reviews virtually every important new wireless standard and technological development, offering especially comprehensive coverage of the 3G systems and wireless local area networks (WLANs) that will transform communications in the coming years. Rappaport illustrates each key concept with practical examples, thoroughly explained and solved step by step. Coverage includes: An overview of key wireless technologies: voice, data, cordless, paging, fixed and mobile broadband wireless systems, and beyond Wireless system design fundamentals: channel assignment, handoffs, trunking efficiency, interference, frequency reuse, capacity planning, large-Scale Fading, and more Path loss, small-Scale Fading, multipath, reflection, diffraction, scattering, shadowing, spatial-temporal channel modeling, and microcell/indoor propagation Modulation, equalization, diversity, channel coding, and speech coding New wireless LAN technologies: IEEE 802.11a/b, HIPERLAN, BRAN, and other alternatives New 3G air interface standards, including W-CDMA, cdma2000, GPRS, UMTS, and EDGE Bluetooth wearable computers, fixed wireless and Local Multipoint Distribution Service (LMDS), and other advanced technologies Updated glossary of abbreviations and acronyms, and a thorolist of references Dozens of new examples and end-of-chapter problems Whether you're a communications/network professional, manager, researcher, or student, Wireless Communications: Principles and Practice, Second Edition gives you an in-depth understanding of the state of the art in wireless technologytoday's and tomorrow's.
W. Whit Smith - One of the best experts on this subject based on the ideXlab platform.
-
Measurements of small-Scale Fading and path loss for long range RF tags
IEEE Transactions on Antennas and Propagation, 2003Co-Authors: Daeyoung Kim, Mary Ann Ingram, W. Whit SmithAbstract:RF modulated backscatter (RFMB), also known as modulated radar cross section or sigma modulation, is a RF transmission technique useful for short-range, low-data-rate applications, such as nonstop toll collection, electronic shelf tags, freight container identification and chassis identification in automobile manufacturing, that are constrained to have extremely low power requirements. The small-Scale Fading observed on the backscattered signal has deeper fades than the signal from a traditional one-way link of the same range in the same environment because the Fading on the backscattered signal is the product of the Fading on the off-board-generated carrier times the Fading on the reflected signal. This paper considers the continuous wave (CW) type of RFMB, in which the interrogator transmitter and receiver antennas are different. This two-way link also doubles the path loss exponent of the one-way link. This paper presents the cumulative distribution functions for the measured small-Scale Fading and the measured path loss for short ranges in an indoor environment at 2.4 GHz over this type of link.
-
small Scale Fading for an indoor wireless channel with modulated backscatter
Vehicular Technology Conference, 2001Co-Authors: Daeyoung Kim, Mary Ann Ingram, W. Whit SmithAbstract:Modulated backscatter is an RF transmission technique useful for short-range, low-data-rate applications constrained to have extremely low power requirements, such as electronic shelf tags, RF tags, and some sensor applications. The small-Scale Fading observed on the backscattered signal has deeper fades than a signal from a traditional one-way link of the same range in the same environment because the Fading on the backscattered signal is a product of the Fading on the off-board generated carrier times the Fading on the reflected signal. We present the first published reports of measured cumulative distribution functions for the small-Scale Fading at 2.4 GHz over this type of link.
Björnson Emil - One of the best experts on this subject based on the ideXlab platform.
-
Large-Scale Fading Precoding for Maximizing the Product of SINRs
2020Co-Authors: Demir, Özlem Tugfe, Björnson EmilAbstract:This paper considers the large-Scale Fading precoding design for mitigating the pilot contamination in the downlink of multi-cell massive MIMO (multiple-input multiple-output) systems. Rician Fading with spatially correlated channels are considered where the line-of-sight (LOS) components of the channels are randomly phase-shifted in each coherence block. The large-Scale Fading precoding weights are designed based on maximizing the product of the signal-to-interference-plus-noise ratios (SINRs) of the users, which provides a good balance between max-min fairness and sum rate maximization. The spectral efficiency (SE) is derived based on the Scaled least squares (LS) estimates of the channels, which only utilize the despreaded pilot signals without any matrix inversion. Simulation results show that the two-layer large-Scale Fading precoding improves the SE of almost all users compared to the conventional single-layer precoding.Comment: To appear at the 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), 5 pages, 2 figure
-
Large-Scale Fading Precoding for Spatially Correlated Rician Fading with Phase Shifts
2020Co-Authors: Demir, Özlem Tugfe, Björnson EmilAbstract:We consider large-Scale Fading precoding (LSFP), which is a two-layer precoding scheme in the downlink of multi-cell massive MIMO (multiple-input multiple-output) systems to suppress inter-cell interference. We obtain the closed-form spectral efficiency (SE) with LSFP at the central network controller and maximum ratio precoding at the base stations (BSs) using the linear minimum mean-squared error or least squares channel estimators. The LSFP weights are designed based on the long-term channel statistics and two important performance metrics are optimized under the per-BS transmit power constraints. These metrics are sum SE and proportional fairness, where the resulting optimization problems are non-convex. Two efficient algorithms are developed to solve these problems by using the weighted minimum mean-squared error and the alternating direction method of multipliers methods. Moreover, two partial LSFP schemes are proposed to reduce the fronthaul signaling requirements. Simulations quantify the performance improvement of LSFP over standard single-layer precoding schemes and identify the specific advantage of each optimization problem.Comment: Submitted to IEEE Transactions on Communications, 30 pages, 7 figure
-
Large-Scale-Fading decoding in cellular Massive MIMO systems with spatially correlated channels
'Institute of Electrical and Electronics Engineers (IEEE)', 2019Co-Authors: Van Chien Trinh, Mollén Christopher, Björnson EmilAbstract:Massive multiple-input–multiple-output (MIMO) systems can suffer from coherent intercell interference due to the phenomenon of pilot contamination. This paper investigates a two-layer decoding method that mitigates both coherent and non-coherent interference in multi-cell Massive MIMO. To this end, each base station (BS) first estimates the channels to intra-cell users using either minimum mean-squared error (MMSE) or element-wise MMSE estimation based on uplink pilots. The estimates are used for local decoding on each BS followed by a second decoding layer where the BSs cooperate to mitigate inter-cell interference. An uplink achievable spectral efficiency (SE) expression is computed for arbitrary two-layer decoding schemes. A closed form expression is then obtained for correlated Rayleigh Fading, maximum-ratio combining, and the proposed large-Scale Fading decoding (LSFD) in the second layer. We also formulate a sum SE maximization problem with both the data power and LSFD vectors as optimization variables. Since this is an NP-hard problem, we develop a low-complexity algorithm based on the weighted MMSE approach to obtain a local optimum. The numerical results show that both data power control and LSFD improve the sum SE performance over single-layer decoding multi-cell Massive MIMO systems.Funding agencies: European Unions Horizon 2020 Research and Innovation Programme [641985]; ELLIIT; CENIIT
-
Large-Scale-Fading Decoding in Cellular Massive MIMO Systems with Spatially Correlated Channels
'Institute of Electrical and Electronics Engineers (IEEE)', 2019Co-Authors: Van Chien Trinh, Mollén Christopher, Björnson EmilAbstract:Massive multiple-input--multiple-output (MIMO) systems can suffer from coherent intercell interference due to the phenomenon of pilot contamination. This paper investigates a two-layer decoding method that mitigates both coherent and non-coherent interference in multi-cell Massive MIMO. To this end, each base station (BS) first estimates the channels to intra-cell users using either minimum mean-squared error (MMSE) or element-wise MMSE (EW-MMSE) estimation based on uplink pilots. The estimates are used for local decoding on each BS followed by a second decoding layer where the BSs cooperate to mitigate inter-cell interference. An uplink achievable spectral efficiency (SE) expression is computed for arbitrary two-layer decoding schemes. A closed-form expression is then obtained for correlated Rayleigh Fading, maximum-ratio combining, and the proposed large-Scale Fading decoding (LSFD) in the second layer. We also formulate a sum SE maximization problem with both the data power and LSFD vectors as optimization variables. Since this is an NP-hard problem, we develop a low-complexity algorithm based on the weighted MMSE approach to obtain a local optimum. The numerical results show that both data power control and LSFD improves the sum SE performance over single-layer decoding multi-cell Massive MIMO systems.Comment: 17 pages; 10 figures; Accepted for publication in IEEE Transactions on Communication
