A practical method for wireless channel reciprocity exploitation through relative calibration
28 Aug 2005-Vol. 1, pp 403-406
TL;DR: Experimental results confirm the validity of the proposed linear reciprocity model, and of the calibration approach, which lets the transmitter acquire knowledge of the downlink channel state from the uplink channel estimates, through proper modeling and estimation of the RF circuitry impulse responses.
Abstract: We present a relative calibration method for a wireless TDD link, which, after a calibration phase involving feedback, lets the transmitter acquire knowledge of the downlink channel state from the uplink channel estimates, through proper modeling and estimation of the RF circuitry impulse responses. Contrarily to previous methods, relative calibration does not require specific calibration hardware. Experimental results confirm the validity of the proposed linear reciprocity model, and of the calibration approach.
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Book•
03 Jan 2018TL;DR: This monograph summarizes many years of research insights in a clear and self-contained way and providest the reader with the necessary knowledge and mathematical toolsto carry out independent research in this area.
Abstract: Massive multiple-input multiple-output MIMO is one of themost promising technologies for the next generation of wirelesscommunication networks because it has the potential to providegame-changing improvements in spectral efficiency SE and energyefficiency EE. This monograph summarizes many years ofresearch insights in a clear and self-contained way and providesthe reader with the necessary knowledge and mathematical toolsto carry out independent research in this area. Starting froma rigorous definition of Massive MIMO, the monograph coversthe important aspects of channel estimation, SE, EE, hardwareefficiency HE, and various practical deployment considerations.From the beginning, a very general, yet tractable, canonical systemmodel with spatial channel correlation is introduced. This modelis used to realistically assess the SE and EE, and is later extendedto also include the impact of hardware impairments. Owing tothis rigorous modeling approach, a lot of classic "wisdom" aboutMassive MIMO, based on too simplistic system models, is shownto be questionable.
1,352 citations
TL;DR: The paper shows that the precoding matrix used by the base station in one cell becomes corrupted by the channel between that base station and the users in other cells in an undesirable manner and develops a new multi-cell MMSE-based precoding method that mitigates this problem.
Abstract: This paper considers a multi-cell multiple antenna system with precoding used at the base stations for downlink transmission. Channel state information (CSI) is essential for precoding at the base stations. An effective technique for obtaining this CSI is time-division duplex (TDD) operation where uplink training in conjunction with reciprocity simultaneously provides the base stations with downlink as well as uplink channel estimates. This paper mathematically characterizes the impact that uplink training has on the performance of such multi-cell multiple antenna systems. When non-orthogonal training sequences are used for uplink training, the paper shows that the precoding matrix used by the base station in one cell becomes corrupted by the channel between that base station and the users in other cells in an undesirable manner. This paper analyzes this fundamental problem of pilot contamination in multi-cell systems. Furthermore, it develops a new multi-cell MMSE-based precoding method that mitigates this problem. In addition to being linear, this precoding method has a simple closed-form expression that results from an intuitive optimization. Numerical results show significant performance gains compared to certain popular single-cell precoding methods.
1,306 citations
Cites background from "A practical method for wireless cha..."
...However, as we see next, this channel estimate is not without issues that must be addressed before it proves useful....
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Posted Content•
TL;DR: In this paper, a multi-cell multiple antenna system with precoding used at the base stations for downlink transmission is considered, where the precoding matrix used by the base station in one cell becomes corrupted by the channel between that base station and the users in other cells in an undesirable manner.
Abstract: This paper considers a multi-cell multiple antenna system with precoding used at the base stations for downlink transmission. For precoding at the base stations, channel state information (CSI) is essential at the base stations. A popular technique for obtaining this CSI in time division duplex (TDD) systems is uplink training by utilizing the reciprocity of the wireless medium. This paper mathematically characterizes the impact that uplink training has on the performance of such multi-cell multiple antenna systems. When non-orthogonal training sequences are used for uplink training, the paper shows that the precoding matrix used by the base station in one cell becomes corrupted by the channel between that base station and the users in other cells in an undesirable manner. This paper analyzes this fundamental problem of pilot contamination in multi-cell systems. Furthermore, it develops a new multi-cell MMSE-based precoding method that mitigate this problem. In addition to being a linear precoding method, this precoding method has a simple closed-form expression that results from an intuitive optimization problem formulation. Numerical results show significant performance gains compared to certain popular single-cell precoding methods.
1,040 citations
22 Aug 2012
TL;DR: This work presents the design, realization, and evaluation of Argos, the first reported base station architecture that is capable of serving many terminals simultaneously through MUBF with a large number of antennas (M >> 10), and reports an Argos prototype with 64 antennas and capable ofserving 15 clients simultaneously.
Abstract: Multi-user multiple-input multiple-output theory predicts manyfold capacity gains by leveraging many antennas on wireless base stations to serve multiple clients simultaneously through multi-user beamforming (MUBF). However, realizing a base station with a large number antennas is non-trivial, and has yet to be achieved in the real-world. We present the design, realization, and evaluation of Argos, the first reported base station architecture that is capable of serving many terminals simultaneously through MUBF with a large number of antennas (M >> 10). Designed for extreme flexibility and scalability, Argos exploits hierarchical and modular design principles, properly partitions baseband processing, and holistically considers real-time requirements of MUBF. Argos employs a novel, completely distributed, beamforming technique, as well as an internal calibration procedure to enable implicit beamforming with channel estimation cost independent of the number of base station antennas. We report an Argos prototype with 64 antennas and capable of serving 15 clients simultaneously. We experimentally demonstrate that by scaling from 1 to 64 antennas the prototype can achieve up to 6.7 fold capacity gains while using a mere 1/64th of the transmission power.
730 citations
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Proceedings Article•
16 Mar 2016TL;DR: Chronos, a system that enables a single WiFi access point to localize clients to within tens of centimeters, demonstrates that Chronos's accuracy is comparable to state-of-the-art localization systems, which use four or five access points.
Abstract: We present Chronos, a system that enables a single WiFi access point to localize clients to within tens of centimeters. Such a system can bring indoor positioning to homes and small businesses which typically have a single access point.
The key enabler underlying Chronos is a novel algorithm that can compute sub-nanosecond time-of-flight using commodity WiFi cards. By multiplying the time-of-flight with the speed of light, a MIMO access point computes the distance between each of its antennas and the client, hence localizing it. Our implementation on commodity WiFi cards demonstrates that Chronos's accuracy is comparable to state-of-the-art localization systems, which use four or five access points.
669 citations
References
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TL;DR: In this article, a single-antenna reciprocity relation for the time domain is derived for the antenna on transmission; next, the same antenna is considered when it is receiving an incident plane wave.
Abstract: In this paper, a single-antenna reciprocity relation is derived for the time domain. First, the antenna is considered on transmission; next, the same antenna is considered when it is receiving an incident plane wave. The two states, transmission and reception, are related by the application of a modified form of the reciprocity theorem for electromagnetic fields with general time dependence due to Cheo. The derivation of the reciprocity relation for the antenna makes use of simple geometric arguments to evaluate the spatial/temporal integrals that occur in the theorem. A few extensions of the reciprocity relation are also described.
156 citations
08 Sep 2003
TL;DR: In this article, the non-reciprocity of the base station analog hardware, which is part of the channel, introduces a very high level of multi-user interference and quantify the effect of the nonreciprocal by means of simulations.
Abstract: Channel reciprocity is needed in SDMA or MIMO downlink pre-filtering when the channel knowledge is acquired in the uplink. We first show analytically that the non-reciprocity of the base station analog hardware, which is part of the channel, introduces a very high level of multi-user interference and quantify the effect of the non-reciprocity by means of simulations. We then propose a novel calibration technique at the base station that enables to compensate for the non-reciprocity and reduce the MUI to a negligible value while having a low implementation cost.
136 citations
01 Jan 2003
TL;DR: A novel calibration technique is proposed at the base station that enables to compensate for the non-reciprocity and reduce the MUI to a negligible value while having a low implementation cost.
Abstract: AEISTRACI Channel reciprocity is needed in SDMA or MIMO downlink pre-filtering when the channel knowledge is acquired in the n link We first show analytically that the non-reci roeity ofthe .&e station anal hardware which is part of the channel, introduces a veqxgh level ok multiuser interference and quantify the effect of the nonreciproeit by means of simulations We then prop a novel caliiratinn technique at the base station that enables to compensate for the non-reciprocity and reduce the MU to a negligible value while having a low implementation cat I. INTRODUIXION OFDM-SDMA is an attractive technique to enhance the capacity of future wireless LANs since it allows mitigating the frequency selective channel fading (OFWM) and increasing the spectral efficiency by accommodating several users in the same time-frequency slots (SDMA). In the downlink, pre-filtering at the base station (BS) side allows to pre-compensate the phase (and amplitude) of the channel in such a manner that all simultaneous users receive their own signal free of MLn 01, [4l. It is in fact this interference Cancellation property that makes SDMA possible in the downlink. Since the terminals have only one antenna, they have no means IO mitigate the spatial MUI. When the channel is estimated in the uplink, the downlink channel matrix is just the transpose of the uplink matrix, assuming the channel is reciprocal. However, the "channel" is actually made up of the propagation channel (the medium between the antennas), the antennas and the transceiver RF, IF and baseband circuits at both sides of the link. The transceiver circuits are usually not reciprml (the TX and RX frequency responses are different) and this can jeopardise the performance of the SDMA system. In this paper, we depart from the reciprocity assumption, analyse the impact of channel non-reciprocity and propose a mitigation method. The document is organised as fdlows. Section 2 introduces the OFDM-SDMA Uplink and Downlink model, including the impact of the composite channel. In section 3, the effects of non-reciprocities are estimated by simulations. Seaion 4 proposes a simple yet effective calibration method with minimal additional hardware requirement. Then, the conclusions are drawn. 11. SYSTEM MODEL
105 citations
"A practical method for wireless cha..." refers background in this paper
...to let them learn and compensate for the characteristics of their own circuitry [2]....
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TL;DR: A fast algorithm for the basic deconvolution problem is developed due to the low displacement rank of the involved matrices and the sparsity of the generators and Monte-Carlo simulations indicate the superior statistical performance of the structured total least squares estimator compared to other estimators such as the ordinary total least square estimator.
Abstract: In this paper we develop a fast algorithm for the basic deconvolution problem. First we show that the kernel problem to be solved in the basic deconvolution problem is a so-called structured total least squares problem. Due to the low displacement rank of the involved matrices and the sparsity of the generators, we are able to develop a fast algorithm. We apply the new algorithm on a deconvolution problem arising in a medical application in renography. By means of this example, we show the increased computational performance of our algorithm as compared to other algorithms for solving this type of structured total least squares problem. In addition, Monte-Carlo simulations indicate the superior statistical performance of the structured total least squares estimator compared to other estimators such as the ordinary total least squares estimator.
68 citations
"A practical method for wireless cha..." refers methods in this paper
..., the ML (Maximum-Likelihood) solution of (6) can be obtained numerically, since this formulation defines a Structured Total Least-Squares (STLS) problem, as recognized by Mastronardi [4]....
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...Under the assumption that the noise is Gaussian i.i.d., the ML (Maximum-Likelihood) solution of (6) can be obtained numerically, since this formulation defines a Structured Total Least-Squares (STLS) problem, as recognized by Mastronardi [4]....
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...[4] Nicola Mastronardi, Philippe Lemmerling, and Sabine Van Huffel, “Fast structured total least squares algorithm for solving the basic deconvolution problem,”SIAM Journal on Matrix Analysis and Applications, vol. 22, pp. 533–553, 2000....
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20 Jun 2004
TL;DR: In this article, the authors proposed a new transceiver design suitable for the application of advanced smart antenna and MIMO techniques as joint transmission, channel inversion and Tomlinson-Harashima pre-coding in future radio systems.
Abstract: For the application of advanced smart antenna and MIMO techniques as joint transmission, channel inversion and Tomlinson-Harashima pre-coding in future radio systems, channel side information is required at the transmitter. In the time-division duplex mode, the reciprocal channel coefficients estimated in the uplink may in principle be reused in the downlink. In practice, the reciprocity must not be limited to the radio frequency channel between the antennas but it should be available also at the transceiver interfaces to the baseband signal processing. Here we propose a new transceiver design suitable for the application of these advanced techniques.
40 citations
"A practical method for wireless cha..." refers methods in this paper
...Another method [3] aims at ensuring the reciprocity of the electronic circuitry through a specially crafted transceiver where the same op-amp is used for both transmitting and receiving, thus lifting the requirement of calibration at the expense of design complexity....
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