### Citations

1573 |
Fundamentals of Statistical Signal Processing: Estimation Theory
- Kay
- 1993
(Show Context)
Citation Context ...iance unbiased estimators (MVUE). The unbiasness is usually considered as a good property for an estimator because the expected value of unbiased estimators is the true value of the unknown parameter =-=[6]-=-. However, in some scenarios the LS method is not directly related to the mean square error (MSE) associated with the target parameter vector and it has been found that a lower MSE can be achieved by ... |

481 |
Estimation with quadratic loss
- James, Stein
- 1961
(Show Context)
Citation Context ...f the conventional estimators with a shrinkage factor in the parameter estimation scenario. The earliest shrinkage estimators that reduce the MSE over MVUE include the well known JamesStein estimator =-=[10]-=- and the work of Thompson [11]. Some extensions of the James-Stein estimator have been proposed in [12]-[15]. In [16], blind minimax estimation (BME) techniques have been proposed, in which the biased... |

93 |
Training-based MIMO channel estimation: A study of estimator tradeoffs and optimal training signals
- Biguesh, Gershman
- 2006
(Show Context)
Citation Context ...estimation scenario, the MMSE estimators with the following expression can also be considered as a biased estimator, ĥMMSE = AĥLS, (28) where ĥMMSE ∈ CL×1 and A ∈ CL×L is a full-rank matrix. As in =-=[22]-=- and [23], such MMSE channel estimators are developed for MIMO and OFDM systems, respectively. Although these MMSE estimators can achieve a much lower MSE than the LS estimator especially in low SNR r... |

84 |
Adaptive Filter Theory”, 4th Edition,
- Haykin
- 2002
(Show Context)
Citation Context ...wo is the optimum tap-weight vector of the receiver (optimum in the 5MSE sense). Assuming that ǫo is white and Gaussian with zero mean and covariance of σ2eIN , then the LS solution in (22) is a MVUE =-=[27]-=-. Now, let us have a look at the following MSE: E{‖wo−ŵLS‖2} = E{(wo−ŵLS)H(wo−ŵLS)} = var(wo, ŵLS). (24) Defining vw = var(wo, ŵLS), we have [6] vw = tr{σ2e(Y HY )−1}, (25) where σ2e is the varia... |

68 |
Adaptive reduced-rank processing based on joint and iterative interpolation, decimation, and filtering,”
- Lamare, Sampaio-Neto
- 2009
(Show Context)
Citation Context ...nau.de) This work has been supported by Zhejiang Key Laboratory for Signal Processing (Contract number of the key laboratory: 2012E10016). also employ a bias to accelerate the convergence speed [32]- =-=[35]-=-. A class of biased estimator that has been studied in recent years is known as the biased estimators with a shrinkage factor [7]-[14]. These biased estimation algorithms have shown their ability to o... |

57 | Adaptive reduced-rank interference suppression based on the multistage Wiener filter,
- Honig, Goldstein
- 2002
(Show Context)
Citation Context ...u-ilmenau.de) This work has been supported by Zhejiang Key Laboratory for Signal Processing (Contract number of the key laboratory: 2012E10016). also employ a bias to accelerate the convergence speed =-=[32]-=-- [35]. A class of biased estimator that has been studied in recent years is known as the biased estimators with a shrinkage factor [7]-[14]. These biased estimation algorithms have shown their abilit... |

56 | Robust mean-squared error estimation in the presence of model uncertainties,”
- Eldar, Ben-Tal, et al.
- 2005
(Show Context)
Citation Context ...the mean square error (MSE) associated with the target parameter vector and it has been found that a lower MSE can be achieved by adding an appropriately chosen bias to the conventional LS estimators =-=[7]-=-,[31]. Note that some reduced-rank techniques Copyright (c) 2013 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from... |

41 |
Channel Codes: Classical and Modern.
- Ryan, Lin
- 2009
(Show Context)
Citation Context ...(BER) performance of the proposed GSE with different numbers of groups are shown in a scenario with 5 users. The coded BER performance is 12 obtained by adopting a convolutional code and an LDPC code =-=[30]-=- designed according to the PEG approach [30]. For the convolutional code, the constraint length is 5, the rate is 2/3 and the code polynomial is [7,5,5]. For the LDPC code, the rate is 1/2 and the cod... |

41 | An iterative algorithm for the computation of the MVDR filter, - Pados, Karystinos - 2001 |

40 | Reduced-rank space-time adaptive interference suppression with joint iterative least squares algorithms for spread-spectrum systems,” - Lamare, Sampaio-Neto - 2010 |

40 |
Position error bound for UWB localization in dense cluttered environments,” in
- Jourdan, Dardari, et al.
- 2006
(Show Context)
Citation Context ...ator can be employed for applications where a high estimation accuracy is required. These include localization in wireless sensor networks [28] and in dense cluttered environments with UWB technology =-=[29]-=-. The proposed estimators can also be employed into emergent multicast and broadcast systems [5], such as the orthogonal frequency-division multiplexing (OFDM) based multi-user multiple-input multiple... |

37 |
Blind adaptive constrained reduced-rank parameter estimation based on constant modulus design for CDMA interference suppression,”
- Lamare, Haardt, et al.
- 2008
(Show Context)
Citation Context ...N In this work, biased estimation algorithms are considered in two common deterministic estimation scenarios in communications engineering, which are parameter estimation and interference suppression =-=[1]-=--[5]. It is known that under the assumption of AWGN, the least-square (LS) algorithm can provide an efficient solution to these estimation problems and will lead to minimum variance unbiased estimator... |

37 |
Performance evaluation of TH-PPM UWB systems in the presence of multiuser interference,”
- Durisi, Benedetto
- 2003
(Show Context)
Citation Context ...ing UWB (TH-UWB) systems, the multiple access interference (MAI) cannot be accurately approximated by a Gaussian distribution for some values of the the signal-to-interference-plus-noise ratio (SINR) =-=[17]-=-. Another possible reason is that the existing shrinkagebased estimators usually require some statistical information such as the noise variance and the norm of the actual parameter 2vector. In our pr... |

23 |
Minimax estimators of the mean of a multivariate normal distribution
- Bock
- 1975
(Show Context)
Citation Context ...t shrinkage estimators that reduce the MSE over MVUE include the well known JamesStein estimator [10] and the work of Thompson [11]. Some extensions of the James-Stein estimator have been proposed in =-=[12]-=--[15]. In [16], blind minimax estimation (BME) techniques have been proposed, in which the biased estimators were developed to minimize the worst case MSE among all possible values of the target param... |

22 |
Some shrinkage techniques for estimating the mean
- Thompson
- 1968
(Show Context)
Citation Context ...with a shrinkage factor in the parameter estimation scenario. The earliest shrinkage estimators that reduce the MSE over MVUE include the well known JamesStein estimator [10] and the work of Thompson =-=[11]-=-. Some extensions of the James-Stein estimator have been proposed in [12]-[15]. In [16], blind minimax estimation (BME) techniques have been proposed, in which the biased estimators were developed to ... |

17 | Rethinking Biased Estimation: Improving Maximum Likelihood and the Cramér–Rao Bound, ser - Eldar |

17 | Y.C.: ‘Rethinking biased estimation
- Kay, Eldar
(Show Context)
Citation Context ...14]. These biased estimation algorithms have shown their ability to outperform the existing unbiased estimators especially in low signal-to-noise ratios (SNR) scenarios and/or with short data records =-=[9]-=-. For these biased estimators [7]-[14], the complexity is much lower than for MMSE algorithms because the additional number of coefficients to be computed is only one. The motivation for the group-bas... |

16 | Blind minimax estimation
- Ben-Haim, Eldar
- 2007
(Show Context)
Citation Context ...timators that reduce the MSE over MVUE include the well known JamesStein estimator [10] and the work of Thompson [11]. Some extensions of the James-Stein estimator have been proposed in [12]-[15]. In =-=[16]-=-, blind minimax estimation (BME) techniques have been proposed, in which the biased estimators were developed to minimize the worst case MSE among all possible values of the target parameter vector wi... |

10 |
et al., “A comprehensive standardized model for ultrawideband propagation channels
- Molisch
- 2006
(Show Context)
Citation Context ...mulations and we assume that the maximum number of active users is 7. The channel has been simulated according to the standard IEEE 802.15.4a channel model for the NLOS indoor environment as shown in =-=[25]-=-. We assume that the channel is constant during the whole transmission and the time domain channel impulse response has 100 taps. The CP guard interval has a length of 35 chips, which has the equivale... |

10 |
Channel estimation for adaptive frequency-domain equalization,”
- Morelli, Sanguinetti, et al.
- 2005
(Show Context)
Citation Context ...ted, while in the structured channel estimation (SCE), the fact that L < M is taken into account and the vector hequ ∈ CL×1 is the parameter vector to be estimated. The concept of SCE was proposed in =-=[20]-=-, where the SCE shows a better performance than the UCE. In [21], adaptive MMSE detection schemes for SC-FDE in multiuser DS-UWB systems based on SCE are developed, where the estimated hequ is adaptiv... |

9 | James-Stein state filtering algorithms
- Manton, Krishnamurthy, et al.
- 1998
(Show Context)
Citation Context ...inkage estimators that reduce the MSE over MVUE include the well known JamesStein estimator [10] and the work of Thompson [11]. Some extensions of the James-Stein estimator have been proposed in [12]-=-=[15]-=-. In [16], blind minimax estimation (BME) techniques have been proposed, in which the biased estimators were developed to minimize the worst case MSE among all possible values of the target parameter ... |

8 | Distributed Variational Filtering for Simultaneous Sensor Localization and Target Tracking in Wireless Sensor Networks
- Teng, Snoussi, et al.
(Show Context)
Citation Context ... data support. It should be noted that the proposed GSE estimator can be employed for applications where a high estimation accuracy is required. These include localization in wireless sensor networks =-=[28]-=- and in dense cluttered environments with UWB technology [29]. The proposed estimators can also be employed into emergent multicast and broadcast systems [5], such as the orthogonal frequency-division... |

4 | Reduced-Rank Adaptive Least Bit-Error-Rate Detection in Hybrid Direct-Sequence TimeHopping Ultrawide Bandwidth System - Ahmed, Yang, et al. - 2011 |

3 |
de Lamare, “Frequency Domain Adaptive Detectors for SC-FDE
- Li, C
- 2010
(Show Context)
Citation Context ...that L < M is taken into account and the vector hequ ∈ CL×1 is the parameter vector to be estimated. The concept of SCE was proposed in [20], where the SCE shows a better performance than the UCE. In =-=[21]-=-, adaptive MMSE detection schemes for SC-FDE in multiuser DS-UWB systems based on SCE are developed, where the estimated hequ is adaptively calculated based on RLS, least-mean squares (LMS) and the co... |

3 |
Uniformly Best Biased Estimators in Non-Bayesian Parameter Estimation
- Todros, Tabrikian
(Show Context)
Citation Context ...mean square error (MSE) associated with the target parameter vector and it has been found that a lower MSE can be achieved by adding an appropriately chosen bias to the conventional LS estimators [7],=-=[31]-=-. Note that some reduced-rank techniques Copyright (c) 2013 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the ... |

2 |
A novel architecture of single-carrier block transmission DS-CDMA
- Chang, Yang
- 2006
(Show Context)
Citation Context ...smit signal is given by xk(i) = Skbk,e(i), (10) where the spreading matrix Sk ∈ CM×M , M = N × Nc, is a circulant Toeplitz matrix and its first column consists of the spreading codes and zero-padding =-=[26]-=-. The equivalent M - dimensional expanded data vector is bk,e(i) = [b (1) k (i),0Nc−1, b (2) k (i),0Nc−1, · · · , b(N)k (i),0Nc−1]T , where (·)T is the transpose. Using this signal expression we can o... |

1 | A Low-Complexity and Efficient Channel Estimator for Multiband OFDM-UWB - Wang, Xin, et al. - 2010 |

1 |
da Silva et al.,Transmission Techniques for Emergent Multicast and Broadcast Systems
- Marques
- 2010
(Show Context)
Citation Context ... this work, biased estimation algorithms are considered in two common deterministic estimation scenarios in communications engineering, which are parameter estimation and interference suppression [1]-=-=[5]-=-. It is known that under the assumption of AWGN, the least-square (LS) algorithm can provide an efficient solution to these estimation problems and will lead to minimum variance unbiased estimators (M... |

1 |
Linear interference suppression in the frequency domain for DS-UWB systems using biased RLS estimation with adaptive shrinkage factors
- Li, Lamare, et al.
- 2011
(Show Context)
Citation Context ...r adopting the biased algorithms here is to accelerate the convergence rate for the adaptive implementations and provide a better performance with short training data support in long filter scenarios =-=[13]-=-. To the best of our knowledge, biased estimators with shrinkage factors are rarely implemented into real-world signal processing and have not been considered in the frequency domain for communication... |

1 |
Adaptive frequency-domain biased estimation algorithms with automatic adjustment of shrinkage factors
- Li, Lamare, et al.
- 2011
(Show Context)
Citation Context ...16). also employ a bias to accelerate the convergence speed [32]- [35]. A class of biased estimator that has been studied in recent years is known as the biased estimators with a shrinkage factor [7]-=-=[14]-=-. These biased estimation algorithms have shown their ability to outperform the existing unbiased estimators especially in low signal-to-noise ratios (SNR) scenarios and/or with short data records [9]... |

1 | et al., “DS-UWB Physical Layer Submission to - Fisher, Kohno, et al. - 2005 |

1 | de Lamare, “Reduced-Rank Linear Interference Suppression for DS-UWB Systems Based on Switched Approximations of Adaptive Basis Functions - Li, C - 2011 |