This paper investigates the potential improvements that may be obtained in terms of the secret key transmission rate in a Quantum Key Distribution (QKD) scheme whereby photon-counting detectors are used at the receiver. To take full advantage of such detectors, soft information is generated in the form of Log-Likelihood Ratios (LLRs) using a Bayesian estimator of phase of the signal pulse which is used to carry the information. The technique is general in a sense that any optical communication scheme whereby the received mean photon count is relatively small, but not necessarily below one and uses the polarization state of light to transmit the binary data may benefit from the soft information processing proposed, although in this paper, we have focused on the QKD application. We demonstrate using simulations the significant reduction in the residual Bit Error Rate (BER) and Frame Error Rate (FER) that is achievable using the proposed soft information processing scheme for a given Quantum BER (QBER) on the quantum link, after the information reconciliation process using LDPC Forward Error Correction (FEC) coding.
This paper investigates the potential improvements that may be obtained in terms of the secret key transmission rate in a Quantum Key Distribution (QKD) scheme whereby photon-counting detectors are used at the receiver. To take full advantage of such detectors, soft information is generated in the form of Log-Likelihood Ratios (LLRs) using a Bayesian estimator of phase of the signal pulse which is used to carry the information. The technique is general in a sense that any optical communication scheme whereby the received mean photon count is relatively small, but not necessarily below one and uses the polarization state of light to transmit the binary data may benefit from the soft information processing proposed, although in this paper, we have focused on the QKD application. We demonstrate using simulations the significant reduction in the residual Bit Error Rate (BER) and Frame Error Rate (FER) that is achievable using the proposed soft information processing scheme for a given Quantum BER (QBER) on the quantum link, after the information reconciliation process using LDPC Forward Error Correction (FEC) coding.
Recently we investigated the potential improvements in key transmission rate in a Quantum Key Distribution (QKD) scheme whereby photon-counting detectors are used at the receiver. To take full advantage of such detectors, soft information is generated in the form of Log-Likelihood Ratios (LLRs) using a Bayesian estimator of phase of the signal pulse which is used to carry the information. We achieved significant reduction in the residual Bit Error Rate (BER) and Frame Error Rate (FER) using LDPC codes in the information reconciliation process. In this paper we explore the limits of the achievable performance gains when using photon counting detectors as compared to the case when such detectors are not available. To this end, we find the classical capacity of the Bayesian inference channel clearly showing the potential gains that photon counting detectors can provide in the context of a realistic cost-effective scheme from an implementation point of view. While there are binary communication schemes that can achieve a higher capacity for a given mean photon count at the receiver compared to the scheme presented here (e.g., the Dolinar receiver), most such schemes are complex and at times unrealistic from an implementation point of view.
The focus of this research activity is to work on pragmatic information reconciliation applied to QKD schemes based on single photon or weak pulse laser (WPL) sources, so as to use feed-forward techniques which minimize the interaction between transmitter and receiver. The core ideas of the thesis are employing Forward Error Correction (FEC) coding as opposed to two-way communication for information reconciliation in QKD schemes, exploiting all the available information for data processing at the receiver including information available from the quantum channel, since optimized use of this information can lead to significant performance improvement, and providing a security versus secret-key rate trade-off to the end-user within the context of QKD systems. Moreover, as shown by accurate experimental studies, the communication channel used for quantum key exchange is not able to reach high levels of reliability (the Quantum Bit Error Rate -QBER may have a high value), both because of the inherent characteristics of the system, and of the presence of a possible attacker. In order to obtain acceptable residual error rates, it is necessary to use a parallel classical and public channel, characterized by high transmission rates and low error rates, on which to transmit only the redundancy bits of systematic channel codes with performance possibly close to the capacity limit. Furthermore, since the more redundancy is added by the channel code, the more the corresponding information can be used to decipher the private message itself, it becomes necessary to design high-rate codes obtained by puncturing a low-rate mother code, possibly achieving a redundancy such that elements of the secret message cannot be uniquely determined from the redundancy itself, so for that purpose we designed high rate LDPC codes. Using high rate codes increases the security with trade-off to performance. Other low photon number applications have also been considered, such as weak-laser pulses (WLP) communication. For that purpose, a low-complexity photon-counting receiver has been considered which may be employed in long-distance amplification-free classical optical communication schemes, and which is typically modeled as an equivalent Binary Symmetric Channel (BSC). We have developed a time varying Binary Input-Multiple Output (BIMO) channel model for this low-complexity photon-counting receiver, and analyzed its performance in presence of soft-metric based capacity approaching iteratively decoded error correcting codes, such as soft-metric based Low Density Parity Check (LDPC) codes and polar codes. We show that the classical channel capacity of the suggested BIMO model is higher than the capacity of the BSC model, and that the use of the BIMO model allows to feed the channel decoder with soft information, in the form of Log-Likelihood Ratios (LLRs), achieving a significant reduction in Bit Error Rate (BER) and Frame Error Rate (FER) with respect to classical hard-metric-based schemes which should be used in conjunction with a BSC channel model.
This thesis deals with soft-information based information reconciliation and data sifting for Quantum Key Distribution (QKD). A novel composite channel model for QKD is identified, which includes both a hard output quantum channel and a soft output classic channel. The Log-Likelihood Ratios, - also called soft-metrics - derived from the two channels are jointly processed at the receiver, exploiting capacity achieving soft-metric based iteratively decoded block codes. The performance of the proposed mixed-soft-metric algorithms are studied via simulations as a function of the system parameters. The core ideas of the thesis are employing Forward Error Correction (FEC) coding as opposed to two-way communication for information reconciliation in QKD schemes, exploiting all the available information for data processing at the receiver including information available from the quantum channel, since optimized use of this information can lead to significant performance improvement, and providing a security versus secret-key rate trade-off to the end-user within the context of QKD systems.
We address photon-number-assisted, polarization-based, binary communication systems equipped with photon counting receivers. In these channels, information is encoded in the value of polarization phase-shift but the carrier has an additional degree of freedom, i.e., its photon distribution, which may be exploited to implement binary-input multiple-output (BIMO) channels also in the presence of a phase diffusion noise affecting the polarization. Here, we analyze the performances of these channels, which approach capacity by means of iteratively decoded error correcting codes. In this paper, we use soft-metric-based low-density parity-check codes for this purpose. In order to take full advantage of all the information available at the output of a photon counting receiver, soft information is generated in the form of log-likelihood ratios, leading to improved frame error rate and bit error rate compared to binary symmetric channels. We evaluate the classical capacity of the considered BIMO channel and show the potential gains that may be provided by photon counting detectors in realistic implementations.
Quantum key distribution (QKD) is a cryptographic communication protocol that utilizes quantum mechanical properties for provable absolute security against an eavesdropper. The communication is carried between two terminals using random photon polarization states represented through quantum states. Both these terminals are interconnected through disjoint quantum and classical channels. Information reconciliation using delay controlled joint decoding is performed at the receiving terminal. Its performance is characterized using data and error rates. Achieving low error rates is particularly challenging for schemes based on error correcting codes with short code lengths. This article addresses the decoding process using ordered statistics decoding for information reconciliation of both short and medium length Bose–Chaudhuri–Hocquenghem codes over a QKD link. The link’s quantum channel is modeled as a binary symmetric quantum depolarization channel, whereas the classical channel is configured with additive white Gaussian noise. Our results demonstrate the achievement of low bit error rates, and reduced decoding complexity when compared to other capacity achieving codes of similar length and configuration.
This paper deals with soft-information based information reconciliation and data sifting for Quantum Key Distribution (QKD).We propose a novel composite channel model for QKD, which includes both a hard output quantum channel and a soft output classic channel. The metrics derived from the two channels are jointly processed at the receiver, exploiting capacity achieving soft-metric based iteratively decoded block codes. The performance of the proposed mixed-softmetric algorithms are studied via simulations as a function of the system parameters. The core ideas of the paper are: a) employing FEC coding as opposed to two-way communication for information reconciliation, b) exploiting all the available information for data processing at the receiver including information available from the quantum channel, since optimized use of this information can lead to significant performance improvement.