Iterative channel estimation for GPRS

Nefedov, Nikolai; Pukkila, M.

doi:10.1109/pimrc.2000.881572

Cited by 9 publications

(3 citation statements)

References 6 publications

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“…where N (ω) denotes the additive Gaussian white noise. Most advanced channel estimation algorithms, as [10], are based on the symbol rate or chip rate in CDMA system. However, these methods fail in WASN settings where nodes are densely deployed.…”

Section: Channel Model and Estimationmentioning

confidence: 99%

Matrix Pencil for Positioning in Wireless ad hoc Sensor Network

Song

Adve

Hatzinakos

2004

Lecture Notes in Computer Science

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Wireless ad-hoc sensor networks (WASN) are attracting research interest recently because of their various applications in distributed monitoring, communication, and computing. In this paper, we concentrate on the range error problem of WASN positioning algorithms. A new matrix pencil based time of arrival (TOA) positioning method (MPP) is proposed for WASN. The new scheme employs matrix pencil for multipath time-delay estimation, and triangulation for absolute positioning. Simulations in a square-room scenario show that the positioning performance is generally robust to multipath effect and the positioning error is limited to around one meter.

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Section: Channel Model and Estimationmentioning

confidence: 99%

Matrix Pencil for Positioning in Wireless ad hoc Sensor Network

Song

Adve

Hatzinakos

2004

Lecture Notes in Computer Science

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“…Uniqueness is not guaranteed in the blind case, however, since the matrix is not necessarily full rank. The matrix inverse can be avoided by introducing an LMS based algorithm as in [41]. In practice, the subchannel gains and the noise are complex.…”

Section: A Em Algorithm For Channel Gain Estimation With Known Noisementioning

confidence: 99%

Channel estimation for multicarrier multiple input single output systems using the em algorithm

Aldana

Carvalho²,

Cioffi

2003

IEEE Trans. Signal Process.

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This paper investigates the problem of blindly and semi-blindly acquiring the channel gains for an underdetermined synchronous multiuser multicarrier system. The special case of a MISO (Multiple Input Single Output) channel is considered where the different users transmit at the same time and in the same bandwidth. In order to separate the different users blindly, techniques exploiting the finite alphabet are used. For such techniques, and for a general underdetermined MIMO system, we study conditions under which the channel and the data for each user are blindly and semi-blindly identifiable. We consider the Stochastic Maximum Likelihood (SML) criterion in which the unknown input symbols are modeled as discrete random variables. We apply the Expectation-Maximization (EM) algorithm in the frequency domain to get blind and semi-blind channel estimates for each user in the MISO case. We also present a recursive EM solution that updates the channel and noise estimates at each time instant. Simulations show that users can be separated even at low SNR. Furthermore, semi-blind estimation allows for a more robust estimation solution since a possible singularity problem is avoided.

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“…In this paper we assume that the channel state information is either known or the provided estimate is constant over the whole iteration process. In [15] we consider an iterative channel estimation scheme, where the feedback information is also utilised in the estimation of the channel impulse response.…”

Section: Principle Of Turbo Equalisationmentioning

confidence: 99%

Turbo equalisation for the Enhanced GPRS system

Pukkila

11th IEEE International Symposium on Personal Indoor and Mobile Radio Communications. PIMRC 2000. Proceedings (Cat. No.00TH8525

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--The iterative receiver structures can often improve the performance with a reasonable level of complexity. In this paper, we study iterative equalisation technique, i.e., turbo equalisation (TE), which enables to improve the performance by signal processing means in the receiver -without altering any other part of the system. TE is based on the feedback information from the channel decoder into the equaliser. That information is used as a priori information in the equaliser to start a new iteration, which provides more reliable decisions. The performance evaluation for Enhanced General Packet Radio System (EGPRS) shows that TE is beneficial for 8-PSK modulation in particular giving 2 dB gain with one extra iteration. However, TE requires soft-in-softout (SISO) decoder to be used, since the feedback information from the decoder should contain reliability information.

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Iterative channel estimation for GPRS

Cited by 9 publications

References 6 publications

Matrix Pencil for Positioning in Wireless ad hoc Sensor Network

Matrix Pencil for Positioning in Wireless ad hoc Sensor Network

Channel estimation for multicarrier multiple input single output systems using the em algorithm

Turbo equalisation for the Enhanced GPRS system

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