#### DMCA

## 1Efficient Coordinated Recovery of Sparse Channels in Massive MIMO

### Citations

3592 | Compressed sensing
- Donoho
- 2006
(Show Context)
Citation Context ...he channel and the fact that adjacent antennas have almost the same support (i.e., properties 1 and 2) to substantially reduce the number of pilots needed as promised by the compressed sensing theory =-=[32]-=-, [33]. Several pilot placement schemes have been suggested for OFDM channel estimation. It is best to allocate the pilots uniformly in conventional OFDM channel estimation (which does not make use of... |

1496 | Near-optimal signal recovery from random projections: Universal encoding strategies
- Candes, Tao
- 2006
(Show Context)
Citation Context ...nnel and the fact that adjacent antennas have almost the same support (i.e., properties 1 and 2) to substantially reduce the number of pilots needed as promised by the compressed sensing theory [32], =-=[33]-=-. Several pilot placement schemes have been suggested for OFDM channel estimation. It is best to allocate the pilots uniformly in conventional OFDM channel estimation (which does not make use of spars... |

393 |
Wireless Communications Principles and Practice (2nd edn
- Rappaport
- 2002
(Show Context)
Citation Context ...s channels can be modeled as discrete multipath channels with large delay spread and very few significant paths as scatterers are sparsely distributed in space (see Fig. 1). This makes the CIR sparse =-=[23]-=-, [26], [27]. Thus, for each transmit-receive link, we need only estimate a few significant multipath channel gains, which has the potential to reduce the pilot overhead substantially. We explicitly m... |

274 |
Noncooperative cellular wireless with unlimited numbers of base station antennas
- Marzetta
- 2010
(Show Context)
Citation Context ...key technology that can meet the growing demands of current wireless systems. For interested readers, some other advantages of adding more antennas to the base station (BS) have been discussed in [4]–=-=[6]-=-. In order to benefit from the advantages of massive MIMO systems, we need to determine the channel impulse response (CIR) for each transmit-receive link. In a typical massive MIMO system, a BS is equ... |

264 | Sparse solutions to linear inverse problems with multiple measurement vectors
- Cotter, Rao, et al.
- 2005
(Show Context)
Citation Context ... on λinit. the observation size (K) and the sparsity (n) of the channels. In fact we could establish a loose lower bound on D in the noise free case as a function of these quantities using lemma 1 in =-=[42]-=-. According to this lemma, if observations from q antennas are used to recover n-sparse channel vectors using K pilots then for a unique solution the following relationship holds n ≤ d(K + q)/2e − 1, ... |

219 | Scaling up MIMO: Opportunities and challenges with very large arrays
- Rusek, Persson, et al.
- 2013
(Show Context)
Citation Context ...in the order of multiples of a hundred antennas) has been found to be beneficial to overcome problems encountered in traditional MIMO settings. Such systems, known as massive MIMO or large-scale MIMO =-=[2]-=-,[3], also have the potential to scale down the transmission power because of the use of small active antennas with very low power. Authors are with the Department of Electrical Engineering, King Abdu... |

206 | Outdoor MIMO wireless channels: models and performance prediction
- Gesbert, Bolcskei, et al.
- 2002
(Show Context)
Citation Context ...y small number of pilots. APPENDIX A CHANNEL MODELS Numerous good/accurate models exist for MIMO wireless channels. However, almost all consider the uniform linear array configuration of the antennas =-=[51]-=-, [52]. It should be noted that from a practical point of view, assuming a uniform linear array (ULA) becomes unfeasible for the purpose of modeling a large scale antenna array. Therefore, the use of ... |

109 | Massive MIMO in the UL/DL of cellular networks: How many antennas do we need
- Hoydis, Brink, et al.
- 2013
(Show Context)
Citation Context ...he order of multiples of a hundred antennas) has been found to be beneficial to overcome problems encountered in traditional MIMO settings. Such systems, known as massive MIMO or large-scale MIMO [2],=-=[3]-=-, also have the potential to scale down the transmission power because of the use of small active antennas with very low power. Authors are with the Department of Electrical Engineering, King Abdullah... |

88 | Massive MIMO for next generation wireless systems - Larsson, Edfors, et al. - 2014 |

76 | Pilot contamination and precoding in multi-cell tdd systems
- Jose, Ashikhmin, et al.
- 2011
(Show Context)
Citation Context ...creases, there is a higher chance that the pilot sequences in the neighboring cells interfere with each other. This pilot contamination problem is a major limiting factor for the massive MIMO systems =-=[7]-=-, [8]. However, pilot contamination could be reduced if the reserved number of pilot tones is reduced. Therefore, in a multi-user scenario there is a need to reduce the number of pilots without affect... |

69 | Turbo equalization.
- Koetter, Singer, et al.
- 2004
(Show Context)
Citation Context ...fically, the reliability measure R in (32) is similar to log-likelihood ratios (LLRs) commonly used in joint channel estimation and data detection methods similar to turboequalizers (for example, see =-=[47]-=- and the references therein). Using (32) each antenna determines the reliability of all data carriers and then select the U carriers with highest reliability values. Let Rr denote the index set of the... |

65 | Low-complexity equalization of OFDM in doubly selective channels
- Schniter
- 2004
(Show Context)
Citation Context ... Sec. III-B. Here we would like to point out that the general approach of using reliable data carriers for enhanced channel estimation is not new and techniques employing reliable carriers exist [44]–=-=[46]-=-. Specifically, the reliability measure R in (32) is similar to log-likelihood ratios (LLRs) commonly used in joint channel estimation and data detection methods similar to turboequalizers (for exampl... |

63 |
How much training is required for multiuser MIMO?”
- Marzetta
- 2006
(Show Context)
Citation Context ...ing key technology that can meet the growing demands of current wireless systems. For interested readers, some other advantages of adding more antennas to the base station (BS) have been discussed in =-=[4]-=-–[6]. In order to benefit from the advantages of massive MIMO systems, we need to determine the channel impulse response (CIR) for each transmit-receive link. In a typical massive MIMO system, a BS is... |

59 | Optimal insertion of pilot symbols for transmissions over time-varying flat fading channels - Dong, Tong, et al. - 2004 |

54 | Compressed channel sensing,”
- Bajwa, Haupt, et al.
- 2008
(Show Context)
Citation Context ... the massive MIMO scenario. It is well known that many wireless channels have impulse response that is sparse in the sense that they have very few significant paths. For example, see [11], [13], [17]–=-=[24]-=- and the references therein. We would also like to add that in massive MIMO since a large number of antennas has to be placed usually it is difficult due to several space, structural, aesthetic constr... |

46 | A coordinated approach to channel estimation in large-scale multiple-antenna systems,” - Yin, Gesbert, et al. - 2013 |

46 | A compressed sensing technique for ofdm channel estimation in mobile environments: Exploiting channel sparsity for reducing pilots.
- Taubock, Hlawatsch
- 2008
(Show Context)
Citation Context ...formly in conventional OFDM channel estimation (which does not make use of sparsity) [34]–[37]. However, when the channel is sparse a random assignment of pilots has been observed to be optimal [38], =-=[39]-=-. With this model, we are now ready to tackle the problem of channel estimation. We do that in three steps spread over three sections 1) Bayesian channel estimation at each antenna, 2) Distributed cha... |

39 | Compressive estimation of doubly selective channels in multicarrier systems: Leakage effects and sparsity-enhancing processing.
- Taubock, Hlawatsch, et al.
- 2010
(Show Context)
Citation Context ...ed in Sec. III-B. Here we would like to point out that the general approach of using reliable data carriers for enhanced channel estimation is not new and techniques employing reliable carriers exist =-=[44]-=-–[46]. Specifically, the reliability measure R in (32) is similar to log-likelihood ratios (LLRs) commonly used in joint channel estimation and data detection methods similar to turboequalizers (for e... |

35 | An investigation into timedomain approach for OFDM channel estimation,”
- Minn, Bhargava
- 2000
(Show Context)
Citation Context ...an be modeled as discrete multipath channels with large delay spread and very few significant paths as scatterers are sparsely distributed in space (see Fig. 1). This makes the CIR sparse [23], [26], =-=[27]-=-. Thus, for each transmit-receive link, we need only estimate a few significant multipath channel gains, which has the potential to reduce the pilot overhead substantially. We explicitly mention the s... |

32 | Sparse channel estimation with zero tap detection - Carbonelli, Vedantam, et al. - 2007 |

29 |
Advanced television systems for terrestrial broadcasting: Some problems and some proposed solutions
- Schreiber
- 1995
(Show Context)
Citation Context ...e for the massive MIMO scenario. It is well known that many wireless channels have impulse response that is sparse in the sense that they have very few significant paths. For example, see [11], [13], =-=[17]-=-–[24] and the references therein. We would also like to add that in massive MIMO since a large number of antennas has to be placed usually it is difficult due to several space, structural, aesthetic c... |

28 | Reduced complexity decision feedback equalization for multipath channels with large delay spreads - Fevrier, Gelfand, et al. - 1999 |

20 | Max-SINR ISI/ICI-shaped multi-carrier communication over the doubly dispersive channel - Das, Schniter - 2007 |

18 | Analysis of the pilot contamination effect in very large multicell multiuser MIMO systems for physical channel models
- Ngo, Larsson, et al.
(Show Context)
Citation Context ...es, there is a higher chance that the pilot sequences in the neighboring cells interfere with each other. This pilot contamination problem is a major limiting factor for the massive MIMO systems [7], =-=[8]-=-. However, pilot contamination could be reduced if the reserved number of pilot tones is reduced. Therefore, in a multi-user scenario there is a need to reduce the number of pilots without affecting t... |

13 | EVD-based channel estimations for multicell multiuser MIMO systems with very large antenna arrays - Ngo, Larsson - 2012 |

10 |
Geometry-based channel modelling of MIMO channels in comparison with channel sounder measurements
- Galdo, Haardt, et al.
- 2003
(Show Context)
Citation Context ...e active tap locations remain fixed across the array. However, for the space-variant case the active tap locations vary slowly across the array. Specifically, we use the IlmProp channel modeling tool =-=[48]-=-, [49] for channel generation. It is important to note that there is a general lack of channel models for massive MIMO scenarios and currently IlmProp seems to be one of the best options available to ... |

9 | Sparse multipath channels: Modeling and estimation - Bajwa, Sayeed, et al. - 2009 |

8 |
Linear prediction based semi-blind estimation of mimo r channels
- Medles, Carvallho
- 2001
(Show Context)
Citation Context ...eds to be thoroughly addressed. Massive MIMO channel estimation is similar to the MIMO channel estimation. Existing literature includes several methods proposed for channel estimation in MIMO systems =-=[9]-=-– [13]. However, it is difficult to directly adopt these approaches for a number of reasons. For example, 1) There is a need to reduce the number of pilots. 2) All received (thousands of) signals in a... |

7 |
Group sparsity methods for compressive channel estimation in doubly dispersive multicarrier systems
- Eiwen, Tauböck, et al.
- 2010
(Show Context)
Citation Context ...o be thoroughly addressed. Massive MIMO channel estimation is similar to the MIMO channel estimation. Existing literature includes several methods proposed for channel estimation in MIMO systems [9]– =-=[13]-=-. However, it is difficult to directly adopt these approaches for a number of reasons. For example, 1) There is a need to reduce the number of pilots. 2) All received (thousands of) signals in a massi... |

7 | Recovery of block sparse signals using the framework of block sparse bayesian learning
- Zhang, Rao
(Show Context)
Citation Context ...blem as several block sparse problems where each receiver collects all observations from its neighbors to estimate the channels. We use the block sparse Bayesian learning algorithm (BSBL) proposed in =-=[50]-=- for block sparse vector estimation as it has been shown to be superior to other methods. C. Evaluation Criteria To evaluate channel estimation performance we use: 1) Normalized mean-squared error (NM... |

5 | Estimation of sparse MIMO channels with common support
- Barbotin, Hormati, et al.
- 2012
(Show Context)
Citation Context ...ity across the large arrays. Specifically, the time difference of arrival ∆τ of a wavefront to two antennas separated by a distance d satisfies ∆τ ≤ dC , where C is the speed of light. The authors in =-=[18]-=- suggest that two channel taps are resolvable if the time difference of arrival is larger than 110BW where BW is the signal bandwidth. Thus, let dmax be the distance between the farthest antennas of a... |

5 |
Optimized pilot placement for sparse channel estimation in
- Qi, Wu
- 2011
(Show Context)
Citation Context ...ts uniformly in conventional OFDM channel estimation (which does not make use of sparsity) [34]–[37]. However, when the channel is sparse a random assignment of pilots has been observed to be optimal =-=[38]-=-, [39]. With this model, we are now ready to tackle the problem of channel estimation. We do that in three steps spread over three sections 1) Bayesian channel estimation at each antenna, 2) Distribut... |

4 | Lowcomplexity polynomial channel estimation in large-scale mimo with arbitrary statistics,”
- Shariati, Bjornson, et al.
- 2014
(Show Context)
Citation Context ...aking it quite different in its model than a regular compact MIMO receiver. Recent works have indicated increased interest in the problem of massive MIMO channel estimation (see for example [7], [8], =-=[14]-=-–[16]). Most of these algorithms make use of the channel statistics. However, these statistics are usually ar X iv :1 40 9. 46 71 v2s[ sta t.A P]s1sO cts20 14 2not known and therefore some kind of ass... |

4 |
Compressive sensing-based channel estimation for massive multiuser MIMO systems
- Nguyen, Ghrayeb
- 2013
(Show Context)
Citation Context ... it quite different in its model than a regular compact MIMO receiver. Recent works have indicated increased interest in the problem of massive MIMO channel estimation (see for example [7], [8], [14]–=-=[16]-=-). Most of these algorithms make use of the channel statistics. However, these statistics are usually ar X iv :1 40 9. 46 71 v2s[ sta t.A P]s1sO cts20 14 2not known and therefore some kind of assumpti... |

4 |
Multichannel-compressive estimation of doubly selective channels in MIMO-OFDM systems: Exploiting and enhancing joint sparsity
- Eiwen, Taubock, et al.
- 2010
(Show Context)
Citation Context ...antennas is assumed to be d = λ/2 where λ is the signal wavelength. While most of the available research in MIMO channel estimation deals with the space-invariant case (for example, [11], [18], [29], =-=[30]-=-), very limited research has been conducted for the space-variant scenario. Similarly, the literature related to the estimation of space-variant sparse channels in massive MIMO is limited (e.g., see [... |

4 |
Fulfilling the promise of massive MIMO with 2D active antenna array,” in
- Ng
- 2012
(Show Context)
Citation Context ...nd three-dimensional antenna array configurations. For example, the IlmProp tool available online [49] allows to generate CIR for 2D antenna array configuration. A similar proposal was put forward in =-=[53]-=-, [54], to extend the spatial channel model (SCM) standard [52]. Similar models have also been considered in Winner II [55] and Winner+ [56] initiatives. However, these models come with their limitati... |

3 |
Tareq Y, “Sparse Reconstruction Using Distribution Agnostic Bayesian Matching Pursuit
- Masood, Al-Naffouri
(Show Context)
Citation Context ...lots and enhance the CIR estimate. The distributed Bayesian algorithm we develop in this paper is based on the Support Agnostic Bayesian Matching Pursuit algorithm (SABMP) developed by the authors in =-=[25]-=-. The remainder of this paper is organized as follows. In Section II, we present the system model and formulate the channel estimation problem. In Section III, we present a simple channel recovery met... |

3 |
Structure-Based Bayesian Sparse Reconstruction
- Quadeer, Al-Naffouri
- 2012
(Show Context)
Citation Context ...bitrarily selected antenna is highlighted in red along with its neighboring antennas in blue. In this context, the red antenna is the central antenna r and rU , rR, rD, and rL are its 4-neighbors. as =-=[28]-=- hr = hrAshrB , (3) wheresindicates element-by-element multiplication. The vector hrA consists of elements that are drawn from some distribution2 and hrB is a Bernoulli random vector with independent ... |

3 |
On optimum pilot design for comb-type OFDM transmission over doubly-selective channels
- Islam, Al-Naffouri, et al.
- 2011
(Show Context)
Citation Context ...eral pilot placement schemes have been suggested for OFDM channel estimation. It is best to allocate the pilots uniformly in conventional OFDM channel estimation (which does not make use of sparsity) =-=[34]-=-–[37]. However, when the channel is sparse a random assignment of pilots has been observed to be optimal [38], [39]. With this model, we are now ready to tackle the problem of channel estimation. We d... |

2 | Semiblind channel estimation of MIMO-OFDM systems with pulse shaping - Wan, Zhu, et al. |

2 | Highly efficient sparse multipath channel estimator with optimal chu-sequence premable for mimo frequency-domain dfe receiver - Hwang, Chung, et al. |

2 |
Al-Naffouri, “Pilotless recovery of clipped OFDM signals by compressive sensing over reliable data carriers
- Al-Safadi, Y
- 2012
(Show Context)
Citation Context ...includes the effect of both the channel estimation error and the noise and plays the central role in the calculation of reliability measure. Specifically, we use the reliability criterion proposed in =-=[43]-=- which takes into consideration the fact that for some carrier i, the distortion Z(i) might be strong enough to take the estimated data symbol X̂ (i) out of its correct decision region, while for some... |

1 |
sparse channel estimation for MIMO-OFDM systems
- “Semiblind
- 2010
(Show Context)
Citation Context ...ot reasonable for the massive MIMO scenario. It is well known that many wireless channels have impulse response that is sparse in the sense that they have very few significant paths. For example, see =-=[11]-=-, [13], [17]–[24] and the references therein. We would also like to add that in massive MIMO since a large number of antennas has to be placed usually it is difficult due to several space, structural,... |

1 | Wavelet-based semiblind channel estimation for ultrawideband OFDM systems - Sadough, Ichir, et al. - 2009 |

1 | Blind estimation and low-rate sampling of sparse MIMO systems with common support
- Xiong, Lu
(Show Context)
Citation Context ...acent antennas is assumed to be d = λ/2 where λ is the signal wavelength. While most of the available research in MIMO channel estimation deals with the space-invariant case (for example, [11], [18], =-=[29]-=-, [30]), very limited research has been conducted for the space-variant scenario. Similarly, the literature related to the estimation of space-variant sparse channels in massive MIMO is limited (e.g.,... |

1 |
Compressive sensing for multi-channel and largescale MIMO networks,” August 2013. [Online]. Available: http: //spectrum.library.concordia.ca/977759
- Nguyen
(Show Context)
Citation Context ...]), very limited research has been conducted for the space-variant scenario. Similarly, the literature related to the estimation of space-variant sparse channels in massive MIMO is limited (e.g., see =-=[31]-=- and the references therein). The approach we pursue in this paper is capable of dealing with both the space-variant and space-invariant cases. D. Pilots Pilots are needed for channel estimation where... |

1 | mmse-optimum pilot design for comb-type OFDM channel estimation in high-mobility scenarios - “Asymptotically - 2011 |

1 |
pilot placement for time-varying channels
- “Optimal
- 2003
(Show Context)
Citation Context ...pilot placement schemes have been suggested for OFDM channel estimation. It is best to allocate the pilots uniformly in conventional OFDM channel estimation (which does not make use of sparsity) [34]–=-=[37]-=-. However, when the channel is sparse a random assignment of pilots has been observed to be optimal [38], [39]. With this model, we are now ready to tackle the problem of channel estimation. We do tha... |

1 |
Al-Naffouri and Mudassir Masood, “Distribution agnostic structured sparsity recovery algorithms
- Tareq
(Show Context)
Citation Context ...riance for Gaussian), especially when the channel statistics are not i.i.d. In that respect, the use of distribution agnostic Bayesian sparse signal recovery (SABMP) developed by the authors in [25], =-=[40]-=- is quite attractive, as it provides Bayesian estimates even when the prior is non-Gaussian or unknown. A. Simple Channel Estimation using SABMP The set of channel estimation algorithms that we propos... |

1 |
An Introduction to Signal Detection and Estimation, ser. A Dowden & Culver book
- Poor
- 1994
(Show Context)
Citation Context ...r the dominant support set Sd and is given by Rh̃ = ∑ S∈Sd p(S|Y) Rh̃|S . (19) Since we replace E[h|Y ,S] with a BLUE estimate, the conditional error covariance matrix will be Rh̃|S = (A H SC −1AS)−1 =-=[41]-=- (where C = σ2wI is the noise covariance matrix). Combining this fact with (19) yields Rh̃ = σ 2 w ∑ S∈Sd p(S|Y) (AHSAS)−1. (20) Note that the calculation of covariance matrix involves a matrix invers... |

1 |
Online; accessed
- dentenilmprop
- 2014
(Show Context)
Citation Context ...ve tap locations remain fixed across the array. However, for the space-variant case the active tap locations vary slowly across the array. Specifically, we use the IlmProp channel modeling tool [48], =-=[49]-=- for channel generation. It is important to note that there is a general lack of channel models for massive MIMO scenarios and currently IlmProp seems to be one of the best options available to the re... |

1 |
http://www.ist-winner.org/deliverables.html, [Online; accessed
- “WINNER
- 2014
(Show Context)
Citation Context ...IR for 2D antenna array configuration. A similar proposal was put forward in [53], [54], to extend the spatial channel model (SCM) standard [52]. Similar models have also been considered in Winner II =-=[55]-=- and Winner+ [56] initiatives. However, these models come with their limitations. For example, in IlmProp the parameters have been estimated using much lower spatial resolution. Indeed, there is a gen... |

1 |
Online; accessed
- orgwinner
- 2014
(Show Context)
Citation Context ... array configuration. A similar proposal was put forward in [53], [54], to extend the spatial channel model (SCM) standard [52]. Similar models have also been considered in Winner II [55] and Winner+ =-=[56]-=- initiatives. However, these models come with their limitations. For example, in IlmProp the parameters have been estimated using much lower spatial resolution. Indeed, there is a general lack of chan... |