Initial Channel State Research Articles

Steady-state teleportation fidelity and Bell nonlocality in dissipative environments

We investigate quantum teleportation and Bell nonlocality for two channel qubits coupled via the Heisenberg interaction and subject to two independent dissipative environments. Compared with the case of two uncoupled qubits, it is shown that the interaction Hamiltonian is beneficial for enhancing the teleportation fidelity and Bell nonlocality, and remarkably, it can also be used to create nonclassical teleportation fidelity and Bell nonlocality even from the initial product states. Moreover, the interaction Hamiltonian guarantees the generation of steady-state nonclassical teleportation fidelity, which is independent of the initial state and therefore one can take any state as the initial channel state.

Joint Channel Estimation and Decoding for Polar Coded SCMA System Over Fading Channels

Sparse code multiple access (SCMA) and polar codes are key techniques for 5G systems. Towards to the realization of massive machine type communications (mMTC) in Internet of Things (IoT), we propose a joint channel estimation and decoding (JCD) scheme to enhance the performance of polar coded SCMA system. There are three parts in our JCD scheme. First, a sparse Bayesian learning (SBL) algorithm is proposed to measure the initial channel state information (CSI) for the JCD scheme. Then, the JCD receiver performs an iterative channel estimation and detection and decoding (ICED) scheme between the SCMA detector and the polar decoder, where the log-likelihood ratio (LLR) from SCMA detector and polar decoder can iteratively update, and the channel gain is also adjusted by the frozen bit error rate (FBER) from the polar decoder in each ICED iteration. In addition, we propose a soft successive cancellation list (soft-SCL) decoding algorithm by calculating the path metric from an LLR based logarithm method, then the soft-SCL decoder outputs the LLR information and the SCMA detector can update the symbol probability in this ICED scheme. Simulation results demonstrate the superior performance of our JCD scheme over fading channels.

Batched Network Coding With Adaptive Recoding for Multi-Hop Erasure Channels With Memory

In this paper, we study the achievable throughput of batched temporal network coding in multi-hop erasure channels, where network coding is applied only within small coding blocks and each communication hop is modeled as a Gilbert–Elliott (GE) packet erasure channel. The GE channel is a 2-state Markov model that is commonly used for channels with memory. While channel memory does not affect the end-to-end capacity of multi-hop erasure channels, we show that it degrades the end-to-end throughput , when batched network coding with finite batch size is applied, due to the higher variance in erasures within one coding block. On the other hand, if the initial channel state information is available, the channel variance can be significantly reduced. We show that this fact can be utilized for improving the efficiency of the recoding operations at the intermediate nodes, and hence improve the end-to-end throughput of batched network coding schemes. Specifically, we propose adaptive recoding operations, where the network coded packets are adaptively generated based on the number of received packets and the initial channel state for each coding block. The simulation results show that the proposed adaptive recoding scheme significantly enhances the end-to-end throughput of batched network coding over multi-hop GE channels.

Semi-blind pilot-aided channel estimation in uplink cloud radio access networks

In this paper, a quasi-Newton method for semi-blind estimation is derived for channel estimation in uplink cloud radio access networks (C-RANs). Different from traditional pilot-aided estimation, semi-blind estimation utilizes the unknown data symbols in addition to the known pilot symbols to estimate the channel. An initial channel state information (CSI) obtained by least-squared (LS) estimation is needed in semi-blind estimation. BFGS (Brayben, Fletcher, Goldfarb and Shanno) algorithm, which employs data as well as pilot symbols, estimates the CSI though solving the problem provided by maximum-likelihood (ML) principle. In addition, mean-square-error (MSE) used to evaluate the estimation performance can be further minimized with an optimal pilot design. Simulation results show that the semi-blind estimation achieves a significant improvement in terms of MSE performance over the conventional LS estimation by utilizing data symbols instead of increasing the number of pilot symbols, which demonstrates the estimation accuracy and spectral efficiency are both improved by semi-blind estimation for C-RANs.

High Performance Adaptive Algorithms for Single-Group Multicast Beamforming

The single-group multicast beamforming problem is NP-hard, and the available approximations do not always achieve favorable performance-complexity tradeoffs. This paper introduces a new class of adaptive multicast beamforming algorithms that features guaranteed convergence and state-of-the-art performance at low complexity. Each update takes a step in the direction of an inverse signal-to-noise ratio (SNR) weighted linear combination of the SNR-gradient vectors of all the users. Convergence of this update to a Karush-Kuhn-Tucker (KKT) point of proportionally fair beamforming is established. Simulations show that the proposed approach can enable better performance than the prior state-of-art in terms of multicast rate, at considerably lower complexity. This reveals an interesting link between max-min-fair and proportionally fair multicast beamforming formulations. For cases where there is no initial channel state information at the transmitter, an online algorithm is developed that simultaneously learns the user channel correlation matrices and adapts the beamforming vector to maximize the minimum (long-term average) SNR among the users, using only periodic binary SNR feedback from each receiver. The online algorithm uses the analytic center cutting plane method to quickly learn the user correlation matrices with limited signaling overhead.

Entanglement Teleportation via One Two-Qubit Spin Evolution Quantum Channel

Entanglement teleportation via treating one two-qubit evolution Ising model as the quantum channel with Dzyaloshinskii-Moriya (DM) interaction under inhomogeneous magnetic field is investigated in detail. We mainly concentrate on the effects about the purity (r) of the initial state about the channel system, the DM interaction (D) and the inhomogeneous magnetic field (b) on the entanglement of the output state and the average fidelity. We show that varying the parameters D and b can influence on the frequency of the oscillation to the teleported entanglement and the average fidelity, and the amplitude of the oscillation can be enhanced evidently by changing r or tuning the entanglement of the input state. The teleported entanglement can fall to zero and maintain to be zero for a short period of time before entanglement recovers when we change the three parameters, one interesting point is that the time interval of the teleported entanglement sudden death will be shorter when we choose the higher purity r of the initial channel state. It also shown us that choosing the smaller values of D and b can broaden the length of the average fidelity where the region is superior to 2/3 and raising the purity of initial state of the quantum channel can expand the height of the average fidelity where the region is superior to 2/3.

On the Capacity of Indecomposable Finite-State Channels With Feedback

We study the capacity of indecomposable finite-state channels (IFSCs) with feedback. It is first shown that the capacity-achieving input distribution for IFSCs with feedback is independent of the initial channel state, even though the capacity depends on the worst-case channel state. In addition, it is shown that for a large class of IFSCs for which the channel state is a deterministic function of a finite number of the most recent channel inputs and outputs, the feedback capacity depends only on the best-case channel state. This result is obtained by a novel transmission strategy whereby feedback is used to synchronize the beginning of the codeword transmission to be at the best-case channel state.

The Effect of a Hydration Pocket on the Function Of nAChR Studied by Computational Approach

The first and solely available crystal structure of the extracellular domain of the nicotinic acetylcholine receptor (nAChR) was published in 2007 (Dellisanti et al. 2007). The intriguing finding of the paper was the existence of a hydration pocket inside the beta sandwich core of the nAChR. A well-ordered water molecule bonded by two hydrophilic residues, Thr52 and Ser126, was found. Based on the patch-clamp experiments of the wild-type and mutant receptors and the fact that the nonchannel homolog acetylcholine binding protein (AChBP) has bulky hydrophobic residues at these positions, authors assumed that hydration pocket might be a key element required for the receptor function as a ligand-gated ion channel. Although this assumption seems quite reasonable, computer simulation is required to provide the energetics of conformational changes.The application of brute force MD simulations to the study of the above problem and other aspects of the action of nAChRs is problematic. This reflects the fact that the time scale for the gating transition is beyond the range of current computational capability. For example, nanoseconds-long MD simulations performed earlier (Law et al. 2005, Cheng et al. 2007) sample only the local conformational space of the initial channel's state. Thus we explored the origin of the hydrophilic/hydrophobic substitution effect by formulation this problem in terms of the relevant free energy changes and applying a proper thermodynamic cycle plus free energy perturbation calculations. Exploring the effect of the Thr52Val in both the open and closes states of nAChR appeared to provide an interesting microscopic insight on the operation of this system and highlighted the importance of using the proper computational strategies in studying biophysical problems.

Iterative receiver for OFDM systems based on semi-blind channel estimation

In this paper we propose two iterative algorithms of joint channel estimation and symbol detection for Orthogonal Frequency Division Multiplexing (OFDM) systems. In which, superimposed pilot scheme is adopted and an initial Channel State Information (CSI) is obtained by employing a first-order statistic. In each subsequent iteration, we propose two algorithms to update the CSI. The Mean Square Error (MSE) of channel estimation and Bit Error Rate (BER) performance are given and simulation results demonstrate that the iterative algorithm using method B has good performance approaching the ideal condition.

A source of bias in the analysis of single channel data: Assessing the apparent interaction between channel proteins

A recent study of single sodium channel currents in neuroblastoma cells suggested interaction between ion channels in close proximity to one another (T. Kiss and K. Nagy, Eur. Biophys. J., 12, 13, 1985). The opening of one channel appeared to affect the likelihood that neighboring channels might open. Some of the conclusions were based on the analysis of observed channel openings that were segregated depending on whether one channel or more than one channel was open at the same time. We hypothesized that the longer one channel remained open, the more likely another channel operating independently, would open, thereby creating the impression of an apparent coupling of channel behavior. We performed simulations and measurements of single sodium channel currents to determine whether the technique of event segregation could account for apparent channel interactions. The simulations showed that the segregation of overlapping (more than one channel open at the same time) and nonoverlapping events led to a bias in the estimated open time and the derived closing rate. To avoid the bias, we found that random pairing of opening and closing events provided an unbiased estimate of the mean closing rate. Using this random assignment approach, we showed that the mean closing rate of single sodium channels in neonatal rat myocytes decreased with depolarization over a limited range of membrane potential. This suggested that the underlying closure mechanism(s) was voltage dependent. From the analysis of open times, we found no evidence for channel interaction in the time scale of tens of milliseconds. Depolarizing steps without events occurred in runs suggesting the existence of long-lived shut state(s). Double pulse experiments with the prepulse and test pulse above threshold showed significant inactivation of channels that did not open. The rate of inactivation of shut channels was substantially slower than the closure rate of open channels. The rate of inactivation of cardiac sodium channels appeared to be strongly dependent on the initial channel state.

The structure of the many-body wavefunction for scattering

We show that the scattered part of the many-body wavefunction initiated by two incoming clusters is given by a fully connected operator acting on the initial channel state. The structure of this operator suggests a division of the full wavefunction into two-cluster components. A set of coupled equations in both the differential and integral form is then derived for these components. These equations have structure and properties similar to the three-body equations of Faddeev. We demonstrate that each component has outgoing waves in a unique two-cluster partition. The transition amplitude for any final arrangement can therefore be extracted directly from the outgoing waves in the relevant components.