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Iterative Time-Variant Channel Estimation for 802.11p Using Generalized Discrete Prolate Spheroidal Sequences
- IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
, 2012
"... This paper deals with channel-estimation for orthogonal frequency division multiplexing (OFDM) in time-variant wireless propagation channels. We particularly consider the challenges of the IEEE 802.11p standard, the world-wide dominant system for vehicular communications. For historic reasons, 802.1 ..."
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Cited by 11 (7 self)
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This paper deals with channel-estimation for orthogonal frequency division multiplexing (OFDM) in time-variant wireless propagation channels. We particularly consider the challenges of the IEEE 802.11p standard, the world-wide dominant system for vehicular communications. For historic reasons, 802.11p uses a pilot pattern that is identical to the one used in 802.11a, which was initially designed for the estimation of indoor channels with no or little time variations. Therefore, this pilot pattern violates the sampling theorem for channels with both, large delay spread and large Doppler spread, as often occurs in vehicular communications. To remedy this problem, we design a robust iterative channel estimator based on a two-dimensional subspace spanned by generalized discrete prolate spheroidal sequences. Due to the tight subspace design the iterative receiver is able to converge to the same bit error rate as a receiver with perfect channel knowledge. Furthermore, we propose a backward compatible modification of the 802.11p pilot pattern such that the number of iterations sufficient for convergence can be reduced by a factor of two to three, strongly reducing implementation complexity.
Adaptive Reduced-Rank Estimation of Non-Stationary Time-Variant Channels Using Subspace Selection
- IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, TO BE PUBLISHED
, 2012
"... In this work we focus on adaptive time-variant channel estimation for vehicle-to-vehicle (V2V) communications in intelligent transportation systems using the IEEE 802.11p physical layer. The IEEE 802.11p pilot pattern is identical to the one in the well-known IEEE 802.11a/g (WiFi) standard, which wa ..."
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Cited by 9 (6 self)
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In this work we focus on adaptive time-variant channel estimation for vehicle-to-vehicle (V2V) communications in intelligent transportation systems using the IEEE 802.11p physical layer. The IEEE 802.11p pilot pattern is identical to the one in the well-known IEEE 802.11a/g (WiFi) standard, which was initially designed for indoor environments with little or no mobility. However, in a V2V drive-by situation the channel impulse response changes rapidly due to the high relative velocity between transmitter and receiver as well as changes in the scattering environment. Hence, for such V2V channels, advanced decision directed channel estimation methods are needed to reach a frame error rate (FER) smaller than 10 −1. Even more importantly, the channels are non-stationary, which implies that the Doppler power spectral density (DSD) and the power-delay profile (PDP) change on a timescale comparable to the frame
VALIDATION OF MINIMUM-ENERGY BAND-LIMITED PREDICTION USING VEHICULAR CHANNEL MEASUREMENTS
"... We demonstrate that minimum-energy (ME) band-limited prediction shows the same robust performance for vehicular channel measurements as well as for the numeric Clarke channel model. By contrast, channel prediction based on sinusoidal modelling presented by Chen et al., 2007, shows poor performance f ..."
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Cited by 2 (1 self)
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We demonstrate that minimum-energy (ME) band-limited prediction shows the same robust performance for vehicular channel measurements as well as for the numeric Clarke channel model. By contrast, channel prediction based on sinusoidal modelling presented by Chen et al., 2007, shows poor performance for a small percentage of measured channel realizations. This increases the mean square error dramatically, hence outlier removal is required. The ME band-limited predictor introduced by Zemen et al., 2007, is based on a subspace spanned by time-concentrated and band-limited sequences. The time-concentration of these sequences is matched to the length of the observation interval and the band-limitation is determined by the support of the Doppler power spectral density of the fading process. The low-complexity time-variant flat-fading channel predictor dynamically selects a predefined subspace from a small set such that the prediction error is minimized. We validate the ME band-limited predictor using channel measurements from an alpine region. The predictor performance with measured channels is comparable to the one obtained with Clarke’s channel model for non line-of-sight situations. For line-of-sight situations the performance is better than for Clarke’s model. We present results in terms of mean square error averaged over all measured snapshots. 1.
Iterative Non-Stationary Channel Estimation for LTE Downlink Communications
"... Abstract—Intelligent transport systems (ITS) require low-latency dependable wireless communication links between trans-mitter and receiver. In vehicular communication scenarios com-munication channels are highly dispersive which makes the design of appropriate channel estimators especially difficult ..."
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Abstract—Intelligent transport systems (ITS) require low-latency dependable wireless communication links between trans-mitter and receiver. In vehicular communication scenarios com-munication channels are highly dispersive which makes the design of appropriate channel estimators especially difficult. In this paper we address the problem of non-stationary vehicular channel estimation for 3GPP long term evolution (LTE) which is recently investigated for its usability in ITS applications. We present an iterative reduced-rank channel estimator for the LTE downlink utilizing a subspace representation based on discrete prolate spheroidal sequences. The subspace is adapted to the time-varying delay and Doppler-spread for each received frame with a hypothesis test. This hypothesis test is adapted to the specific pilot grid in LTE. With this setup we can achieve a twofold reduction in the number of required iterations to achieve a frame error rate (FER) below 10−1 for a relative velocity range of 0 to 400 km/h, a delay spread of 0 to 4.7 µs at a signal-to-noise ratio (SNR) of 13 dB. Index Terms—long term evolution, discrete prolate spheroidal sequences, iterative channel estimation, D2D communication I.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, ACCEPTED FOR PUBLICATION 1 Receive Antenna Selection for Time-Varying Channels Using Discrete Prolate Spheroidal Sequences
"... Abstract—Receive antenna selection (AS) has been shown to maintain the diversity benefits of multiple antennas while potentially reducing hardware costs. However, the promised diversity gains of receive AS depend on the assumptions of perfect channel knowledge at the receiver and slowly time-varying ..."
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Abstract—Receive antenna selection (AS) has been shown to maintain the diversity benefits of multiple antennas while potentially reducing hardware costs. However, the promised diversity gains of receive AS depend on the assumptions of perfect channel knowledge at the receiver and slowly time-varying fading. By explicitly accounting for practical constraints imposed by the next-generation wireless standards such as training, packetization and antenna switching time, we propose a single receive AS method for time-varying fading channels. The method exploits the low training overhead and accuracy possible from the use of discrete prolate spheroidal (DPS) sequences based reduced rank subspace projection techniques. It only requires knowledge of the Doppler bandwidth, and does not require detailed correlation knowledge. Closed-form expressions for the channel prediction and estimation error as well as symbol error probability (SEP) of M-ary phase-shift keying (MPSK) for symbol-by-symbol receive AS are also derived. It is shown that the proposed AS scheme, after accounting for the practical limitations mentioned above, outperforms the ideal conventional single-input single-output (SISO) system with perfect CSI and no AS at the receiver and AS with conventional estimation based on complex exponential basis functions. Index Terms—Antenna selection, time-varying fading, discrete prolate spheroidal sequences, Slepian basis expansion. I.
IEEE ICC 2012- Wireless Communications Symposium Antenna Selection For Time-Varying Channels Based on Slepian Subspace Projections
"... Abstract—Single receive antenna selection (AS) allows singleinput single-output (SISO) systems to retain the diversity benefits of multiple antennas with minimum hardware costs. We propose a single receive AS method for time-varying channels, in which practical limitations imposed by next-generation ..."
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Abstract—Single receive antenna selection (AS) allows singleinput single-output (SISO) systems to retain the diversity benefits of multiple antennas with minimum hardware costs. We propose a single receive AS method for time-varying channels, in which practical limitations imposed by next-generation wireless standards such as training, packetization and antenna switching time are taken into account. The proposed method utilizes low-complexity subspace projection techniques spanned by discrete prolate spheroidal (DPS) sequences. It only uses Doppler bandwidth knowledge, and does not need detailed correlation knowledge. Results show that the proposed AS method outperforms ideal conventional SISO systems with perfect CSI but no AS at the receiver and AS using the conventional Fourier estimation/prediction method. A closed-form expression for the symbol error probability (SEP) of phase-shift keying (MPSK) with symbol-by-symbol receive AS is derived. I.
doi:10.1155/2007/95281 Research Article Low-Complexity Geometry-Based MIMO Channel Simulation
"... The simulation of electromagnetic wave propagation in time-variant wideband multiple-input multiple-output mobile radio channels using a geometry-based channel model (GCM) is computationally expensive. Due to multipath propagation, a large number of complex exponentials must be evaluated and summed ..."
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The simulation of electromagnetic wave propagation in time-variant wideband multiple-input multiple-output mobile radio channels using a geometry-based channel model (GCM) is computationally expensive. Due to multipath propagation, a large number of complex exponentials must be evaluated and summed up. We present a low-complexity algorithm for the implementation of a GCM on a hardware channel simulator. Our algorithm takes advantage of the limited numerical precision of the channel simulator by using a truncated subspace representation of the channel transfer function based on multidimensional discrete prolate spheroidal (DPS) sequences. The DPS subspace representation offers two advantages. Firstly, only a small subspace dimension is required to achieve the numerical accuracy of the hardware channel simulator. Secondly, the computational complexity of the subspace representation is independent of the number of multipath components (MPCs). Moreover, we present an algorithm for the projection of each MPC onto the DPS subspace in O(1) operations. Thus the computational complexity of the DPS subspace algorithm compared to a conventional implementation is reduced by more than one order of magnitude on a hardware channel simulator with 14-bit precision. Copyright © 2007 Florian Kaltenberger et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1.
9 Multi-User MIMO Receiver Processing for Time-Varying Channels
"... Wireless broadband communications for mobile users at vehicular speed is the cornerstone of future 4th generation systems. This chapter deals with joint iterative channel estimation and multi-user detection for the uplink of a multi-carrier (MC) code division multiple access (CDMA) system. MC-CDMA i ..."
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Wireless broadband communications for mobile users at vehicular speed is the cornerstone of future 4th generation systems. This chapter deals with joint iterative channel estimation and multi-user detection for the uplink of a multi-carrier (MC) code division multiple access (CDMA) system. MC-CDMA is based on orthogonal frequency division multiplexing
On the Optimum Number of Hypotheses for Adaptive Reduced-Rank Subspace Selection
"... Abstract—Intelligent transport systems (ITS) require low-latency dependable wireless communication links inbetween ve-hicles as well as between vehicles and the infrastructure. In vehicular communication scenarios communication channels are time- and frequency (doubly) dispersive and the channel sta ..."
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Abstract—Intelligent transport systems (ITS) require low-latency dependable wireless communication links inbetween ve-hicles as well as between vehicles and the infrastructure. In vehicular communication scenarios communication channels are time- and frequency (doubly) dispersive and the channel statistics are non-stationary, i.e., they change over time. Hence, the design of appropriate channel estimators is challenging. Recently an adaptive reduced-rank channel estimation technique for non-stationary time-variant channel estimation was introduced by Zemen and Molisch, 2012. This technique uses a hypothesis test to obtain an estimate of the current channel statistics on a per frame basis. The optimum number of hypotheses is not known. In this paper we present new empirical insights on the optimum choice of the number of hypotheses for the hypothesis test for non-stationary time-variant channel estimation. With these considerations the complexity of an adaptive reduced-rank channel estimator can be reduced and its performance improved. I.
Antenna Selection For Time-Varying Channels Based on Slepian Subspace Projections
"... Abstract—Single receive antenna selection (AS) allows single-input single-output (SISO) systems to retain the diversity ben-efits of multiple antennas with minimum hardware costs. We propose a single receive AS method for time-varying chan-nels, in which practical limitations imposed by next-generat ..."
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Abstract—Single receive antenna selection (AS) allows single-input single-output (SISO) systems to retain the diversity ben-efits of multiple antennas with minimum hardware costs. We propose a single receive AS method for time-varying chan-nels, in which practical limitations imposed by next-generation wireless standards such as training, packetization and antenna switching time are taken into account. The proposed method utilizes low-complexity subspace projection techniques spanned by discrete prolate spheroidal (DPS) sequences. It only uses Doppler bandwidth knowledge, and does not need detailed cor-relation knowledge. Results show that the proposed AS method outperforms ideal conventional SISO systems with perfect CSI but no AS at the receiver and AS using the conventional Fourier estimation/prediction method. A closed-form expression for the symbol error probability (SEP) of phase-shift keying (MPSK) with symbol-by-symbol receive AS is derived. I.
