Parallel-interference-cancellation-assisted decision-directed channel estimation for OFDM systems using multiple transmit antennas

Münster, M.; Hanzo, Lajos

doi:10.1109/twc.2005.855793

Cited by 29 publications

(14 citation statements)

References 26 publications

(58 reference statements)

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“…A large number of appropriate algorithms has been proposed in the literature. Amongst these, two popular families of algorithms have received a great deal of attention; algorithms performing joint estimation for all users [8,22,23], and algorithms based on interference cancellation [15,24]. In this article, two algorithm from the first, and one from the second family is considered.…”

Section: Channel Estimation Algorithmsmentioning

confidence: 99%

Iterative receivers with channel estimation for multi-user MIMO-OFDM: complexity and performance

Hammarberg

Rusek

Edfors

2012

J Wireless Com Network

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A family of iterative receivers is evaluated in terms of complexity and performance for the case of an uplink multiuser (MU) multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. The transmission over block fading channels is considered. The analyzed class of receivers is performing channel estimation inside the iterative detection loop, which has been shown to improve estimation performance. As part of our results we illustrate the ability of this type of receiver to reduce the required amount of pilot symbols. A remaining question to ask is which combinations of estimation and detection algorithms that provide the best trade-off between performance and complexity. We address this issue by considering MU detectors and channel estimators, with varying algorithm complexity. For MU detection, two algorithms based on parallel interference cancellation (PIC) are considered and compared with the optimal symbol-wise maximum a-posteriori probability (MAP) detector. For channel estimation, an algorithm performing joint minimum-mean-square-error (MMSE) estimation is considered along with a low complexity replica making use of a Krylov subspace method. An estimator based on the space alternating generalized expectation-maximization (SAGE) algorithm is also considered. Our results show that low-complexity algorithms provide the best tradeoff, even though more receiver iterations are needed to reach a desired performance.

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Section: Channel Estimation Algorithmsmentioning

confidence: 99%

Iterative receivers with channel estimation for multi-user MIMO-OFDM: complexity and performance

Hammarberg

Rusek

Edfors

2012

J Wireless Com Network

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“…Another PIC-based iterative detector designed for multiuser OFDM systems [64] was proposed in [78], which invoked combined multiuser channel estimation and iterative data detection. SDMA [64] was invoked for supporting multiple users in the uplink of the system, where the philosophy is that provided that the CIRs of the various users are sufficiently different, since they are sufficiently far apart, they can communicate within the same time-slot and frequency-slot without unduly interfering with each other.…”

Section: F Concatenated Fec and Iterative Mud For Ofdmmentioning

confidence: 99%

“…As a further advance in the field, in [79] a GA-aided minimum mean-square error (MMSE) MUD was proposed for a TTCM assisted SDMA multiuser OFDM system, which combined the beneficial features of SDMA-OFDM [64], [78], GA-MUDs [70]- [73], and TTCM [9]. A substantial advantage of this solution was its ability to support up to a factor two higher number of users than the number of BS receiver antennas, while imposing a substantially lower complexity than the full-search-based ML detector [64], [70].…”

Section: F Concatenated Fec and Iterative Mud For Ofdmmentioning

confidence: 99%

Turbo Decoding and Detection for Wireless Applications

Hanzo

Woodard²,

Robertson

2007

Proc. IEEE

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Future iterative receivers will be designed using EXIT charts for near-capacity operation over dispersive wireless channels at the lowest possible complexity and delay. More specifically, we commence by discussing the turbo principles, which have been shown to be capable of performing close to Shannon's capacity limit. We continue by reviewing the classic maximum a posteriori probability decoder. These discussions are followed by studying the effect of a range of system parameters in a systematic fashion, in order to gauge their performance ramifications. In the second part of this treatise, we focus our attention on the family of iterative receivers designed for wireless communication systems, which were partly inspired by the invention of turbo codes. More specifically, the family of iteratively detected joint coding and modulation schemes, turbo equalization, concatenated spacetime and channel coding arrangements, as well as multi-user detection and three-stage multimedia systems are highlighted.

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“…In [1], [2], approaches suppressing the interference from other transmit antenna have been proposed. In essence, channel estimates predicted from adjacent symbols and tentative decisions on data symbols are used for this task.…”

Section: Introductionmentioning

confidence: 99%

Virtual pilot signal for massive MIMO-OFDM systems

Park

Choi

Seol

et al. 2014

2014 Information Theory and Applications Workshop (ITA)

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Abstract-A technology exploiting large number of antennas into the wireless transceiver, often called massive MIMO technology, has been received great attention in recent years. The benefits of this approach, however, can be realized only when the quality of estimated channel is ensured at both transmitter and receiver. In this paper, we propose a new channel estimation technique dealing with the pilot shortage in the massive MIMO systems. In a nutshell, we employ reliable data tones obtained from the iterative deteciton and decoding (IDD) as well as pilot signals in the estimation of channels. We show that the proposed method achieves substantial performance gain over conventional approaches employing pilot signals exclusively.

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Parallel-interference-cancellation-assisted decision-directed channel estimation for OFDM systems using multiple transmit antennas

Cited by 29 publications

References 26 publications

Iterative receivers with channel estimation for multi-user MIMO-OFDM: complexity and performance

Iterative receivers with channel estimation for multi-user MIMO-OFDM: complexity and performance

Turbo Decoding and Detection for Wireless Applications

Virtual pilot signal for massive MIMO-OFDM systems

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