Iterative compensated MMSE channel estimation in LTE systems

Liu, Yang; Sezginer, Serdar

doi:10.1109/icc.2012.6363977

Cited by 12 publications

(3 citation statements)

References 5 publications

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“…They use the simple joint pilot and "soft" information that build a new pilot with both channel estimate from the initial iteration and channel estimate based on soft information from the channel decoder [4]. At same time they compensated MMSE in "null" sub-carriers, put "null" sub-carriers as "virtual" pilot symbols according to power coarse calculation [5].The undoubtable fact is that iterative channel estimations increased MSE performance. But in [6],compared a-posteriori, extrinsic and hard estimated data symbols information from the channel decoder, the performance only 3dB increased after 5 iterations.…”

Section: Introductionmentioning

confidence: 99%

A Novel Channel Estimation Based on Pilot-Aided in LTE Downlink Systems

Jin

2014

2014 Seventh International Symposium on Computational Intelligence and Design

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In this paper, a novel channel estimation is proposed that exploit control area channel estimation for the Long Term Evolution (LTE) downlink. In order to achieve a high data rate over wireless channels in LTE, it is crucial to obtain high accurate channel state information at the receiver. The LTE standards adopt training data known as pilot symbols to estimate channel effectively. The key question is whether the accuracy of channel estimation based on pilot symbols is sufficient to achieve perfect channel state information. Therefore we propose a novel channel estimation in LTE Downlink OFDM system based on reference channel estimation. Due to high precision of control area channel estimation, the accurate outcome of control area channel can be used as virtual pilot to estimate the channel. Simulation results show that virtual pilot approaches provide considerable improvement with low complexity.

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Section: Introductionmentioning

confidence: 99%

A Novel Channel Estimation Based on Pilot-Aided in LTE Downlink Systems

Jin

2014

2014 Seventh International Symposium on Computational Intelligence and Design

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“…These standards are orthogonal frequency division multiple access (OFDMA) based and they can satisfy the need for shorter communication links to provide truly broadband connectivity services. In these systems, either MVU/least squares (LS) or MMSE channel estimators are used, usually employing some sort of estimate interpolation through the frame if the goal is to track a time-varying channel [1], [4], [11], [18], [19], [20], [23], [25], [27].…”

Section: Introductionmentioning

confidence: 99%

On the Design of Channel Estimators for given Signal Estimators and Detectors

Katselis¹,

Rojas²,

Hjalmarsson³

et al. 2013

Preprint

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The fundamental task of a digital receiver is to decide the transmitted symbols in the best possible way, i.e., with respect to an appropriately defined performance metric. Examples of usual performance metrics are the probability of error and the Mean Square Error (MSE) of a symbol estimator. In a coherent receiver, the symbol decisions are made based on the use of a channel estimate. This paper focuses on examining the optimality of usual estimators such as the minimum variance unbiased (MVU) and the minimum mean square error (MMSE) estimators for these metrics and on proposing better estimators whenever it is necessary. For illustration purposes, this study is performed on a toy channel model, namely a single input single output (SISO) flat fading channel with additive white Gaussian noise (AWGN). In this way, this paper highlights the design dependencies of channel estimators on target performance metrics.

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“…∀m∈G k ,∀k∈{1,...,K} (3.27) Using the fact 5.12.4 from [33](T r(XY) ≤ n i=1 λ i (X)λ i (Y), for X and Y ∈ C n×n and the definition of the norm from (3.25), then (3.27) reduces to…”

Section: Discussionmentioning

confidence: 99%

Sub-optimal and robust downlink beamforming in wireless networks with imperfect channel state information

Al-Asadi¹

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The rapid growth in internet applications such as video streaming enforce the researcher to explore a new wireless technique to ensure high signal to interference noise ratio (SINR) at the end users, leading to high quality of service (QOS). The fourth generation (4G) wireless technologies introduced a with promising technique known as multiple-input-multiple-output (MIMO) paradigm. The MIMO offers spatial diversity of multiple signals between the source and the destination which can ensure high concentration of the desired power at the destination as well as combat the unwanted interference which can be done by the beamforming technique, implemented in two ways the up-link and the down-link. Two methods of beamforming have been addressed in MIMO wireless communications, the first consider the minimization of transmitted power for predefined SINR at the receiver and the second approach consider maximization of SINR at the recipient while maintaining the power at the sender to a small fixed value. Rigid beamforming is assured when the accurate channel state information (CSI) of the wireless system are acquired at the beamforming side. Because of some practical limitations in wireless systems such as feedback error, dynamic characteristics of wireless channel, etc., the ideal CSI cannot be obtained and thus the beamforming must consider the error in CSI. Three type of solutions have been developed to combat the effect of uncertain CSI these solutions are the non-robust, the sub-optimal and the robust solution. In this work the sub-optimal and the robust downlink beamforming in conventional wireless network are addressed. The solution considers a multicast, multi-group, multicell scenario. The uncertainty in CSI is modeled mathematically using Frobinius norm and the beamforming method used is the QOS method where the minimum SINR over all groups is maximized for small predefined transmitted power. Because the problem is difficult to be solved as a single optimization problem, it is divided into two problems. The first problem eliminates the effect of CSI uncertainty using the non-monotone spectral projected gradient (NMSPG) method, and the second problems use the successive convex approximation (SCA) method to extract the beamforming vectors for each group. The procedure goes through an iterate-alternative convex technique between the two methods until stopped by some predefined criteria. Wireless communication researchers have also achieved significant development in the area of spectrum scarcity by introducing the cognitive radio (CR) network. In a CR network the secondary users (SUs) can utilize the licensed frequency that is underutilized by the primary users (PUs). Two type of CR network were developed, the overlay and the underlay CR network. The beamforming in an overlay CR network follows the same procedure as in a conventional network while in an underlay CR network an extra constraint must be added to the beamforming problem which makes the problem more difficult to solved. In this thesis the beamforming problem in a CR network with multiple secondary transmitters that generate multiple beamforming vectors to multiple groups of secondary receivers under uncertain CSI are analyzed and solved. Two solutions were developed: the sub-optimal and the robust solutions. For the sub-optimal solution, the problem is split into two problems, the QOS and the interference power problem to combat the effect of CSI uncertainty then the two problems are combined to find the beamforming vectors using the SCA method. For the robust solution, the problem is also divided into two problems, the QOS and the interference power problem to eliminate the CSI uncertainty. The interference power problem is solved using the Lagrangian duality. The QOS problem is solved using the Lagrangian duality and the NMSPG method. after addressing CSI uncertainty, the beamforming vectors are extracted using the SCA method and, solved using the bisection search method.

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Iterative compensated MMSE channel estimation in LTE systems

Cited by 12 publications

References 5 publications

A Novel Channel Estimation Based on Pilot-Aided in LTE Downlink Systems

A Novel Channel Estimation Based on Pilot-Aided in LTE Downlink Systems

On the Design of Channel Estimators for given Signal Estimators and Detectors

Sub-optimal and robust downlink beamforming in wireless networks with imperfect channel state information

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