Information Theory and Reliable Communication

A new coded modulation scheme is proposed. At the transmitter, the concatenation of a distribution matcher and a systematic binary encoder performs probabilistic signal shaping and channel coding. At the receiver, the output of a bitwise demapper is fed to a binary decoder. No iterative demapping is performed. Rate adaption is achieved by adjusting the input distribution and the transmission power. The scheme is applied to bipolar amplitude-shift keying (ASK) constellations with equidistant signal points and it is directly applicable to two-dimensional quadrature amplitude modulation (QAM). The scheme is implemented by using the DVB-S2 low-density parity-check (LDPC) codes. At a frame error rate of $10^{-3}$ , the new scheme operates within less than 1.1 dB of the AWGN capacity $\frac{1}{2}\log_2(1+{\mathsf{SNR}})$ at any spectral efficiency between 1 and 5 bits/s/Hz by using only 5 modes, i.e., 4-ASK with code rate 2/3, 8-ASK with 3/4, 16-ASK and 32-ASK with 5/6, and 64-ASK with 9/10.

Bandwidth Efficient and Rate-Matched Low-Density Parity-Check Coded Modulation

A new coded modulation scheme is proposed. At the transmitter, the concatenation of a distribution matcher and a systematic binary encoder performs probabilistic signal shaping and channel coding. At the receiver, the output of a bitwise demapper is fed to a binary decoder. No iterative demapping is performed. Rate adaption is achieved by adjusting the input distribution and the transmission power. The scheme is applied to bipolar amplitude shift keying (ASK) constellations with equidistant signal points and it is directly applicable to two-dimensional quadrature amplitude modulation (QAM). The scheme is implemented by using the DVB-S2 low-density parity-check (LDPC) codes. At a frame error rate of 1e-3, the new scheme operates within less than 1 dB of the AWGN capacity 0.5log2(1+SNR) at any spectral efficiency between 1 and 5 bits/s/Hz by using only 5 modes, i.e., 4-ASK with code rate 2/3, 8-ASK with 3/4, 16-ASK and 32-ASK with 5/6 and 64-ASK with 9/10.

We review probabilistic constellation shaping (PCS), which has been a key enabler for several recent record-setting optical fiber communications experiments. PCS provides both fine-grained rate adaptability and energy efficiency (sensitivity) gains. We discuss the reasons for the fundamentally better performance of PCS over other constellation shaping techniques that also achieve rate adaptability, such as time-division hybrid modulation, and examine in detail the impact of sub-optimum shaping and forward error correction (FEC) on PCS systems. As performance metrics for systems with PCS, we compare information-theoretic measures such as mutual information (MI), generalized MI (GMI), and normalized GMI, which enable optimization and quantification of the information rate (IR) that can be achieved by PCS and FEC. We derive the optimal parameters of PCS and FEC that maximize the IR for both ideal and non-ideal PCS and FEC. To avoid plausible pitfalls in practice, we carefully revisit key assumptions that are typically made for ideal PCS and FEC systems.

/pdf/probabilistic-constellation-shaping-for-optical-fiber-zv2jhsi78g.pdf

Probabilistic Constellation Shaping for Optical Fiber Communications

At present, reliable ambiguity resolution in real-time GPS precise point positioning (PPP) can only be achieved after an initial observation period of a few tens of minutes. In this study, we propose a method where the incoming triple-frequency GPS signals are exploited to enable rapid convergences to ambiguity-fixed solutions in real-time PPP. Specifically, extra-wide-lane ambiguity resolution can be first achieved almost instantaneously with the Melbourne-Wubbena combination observable on L2 and L5. Then the resultant unambiguous extra-wide-lane carrier-phase is combined with the wide-lane carrier-phase on L1 and L2 to form an ionosphere-free observable with a wavelength of about 3.4 m. Although the noise of this observable is around 100 times the raw carrier-phase noise, its wide-lane ambiguity can still be resolved very efficiently, and the resultant ambiguity-fixed observable can assist much better than pseudorange in speeding up succeeding narrow-lane ambiguity resolution. To validate this method, we use an advanced hardware simulator to generate triple-frequency signals and a high-grade receiver to collect 1-Hz data. When the carrier-phase precisions on L1, L2 and L5 are as poor as 1.5, 6.3 and 1.5 mm, respectively, wide-lane ambiguity resolution can still reach a correctness rate of over 99 % within 20 s. As a result, the correctness rate of narrow-lane ambiguity resolution achieves 99 % within 65 s, in contrast to only 64 % within 150 s in dual-frequency PPP. In addition, we also simulate a multipath-contaminated data set and introduce new ambiguities for all satellites every 120 s. We find that when multipath effects are strong, ambiguity-fixed solutions are achieved at 78 % of all epochs in triple-frequency PPP whilst almost no ambiguities are resolved in dual-frequency PPP. Therefore, we demonstrate that triple-frequency PPP has the potential to achieve ambiguity-fixed solutions within a few minutes, or even shorter if raw carrier-phase precisions are around 1 mm. In either case, we conclude that the efficiency of ambiguity resolution in triple-frequency PPP is much higher than that in dual-frequency PPP.

Triple-frequency GPS precise point positioning with rapid ambiguity resolution

Method for Determining Biases of Satellite Signals a new method for bias estimation on multiple frequencies with a Kalman filter is proposed. It consists of four steps: First, a least-squares estimation of ranges, ionospheric delays, ambiguities, receiver phase biases and satellite phase biases is performed. The code biases are absorbed in the ranges and ionospheric delays, and a subset of ambiguities is mapped to the phase biases to remove linear dependencies between the unknown parameters. In a second step, the accuracy of the bias estimates is efficiently improved by a Kalman filter. The real-valued a posteriori ambiguity estimates are decorrelated by an integer ambiguity transformation to reduce the time of ambiguity resolution. Once the float ambiguities have sufficiently converged, they are fixed sequentially in a third step. Finally, a second Kalman filter is used to separate the receiver and satellite code biases and the tropospheric delays from the ranges.

Estimation of phase and code biases on multiple frequencies with a Kalman filter

. Snow water equivalent (SWE) can be measured using low-cost Global Navigation Satellite System (GNSS) sensors with one antenna placed below the snowpack and another one serving as a reference above the snow. The underlying GNSS signal-based algorithm for SWE determination for dry- and wet-snow conditions processes the carrier phases and signal strengths and derives additionally liquid water content (LWC) and snow depth (HS). So far, the algorithm was tested intensively for high-alpine conditions with distinct seasonal accumulation and ablation phases. In general, snow occurrence, snow amount, snow density and LWC can vary considerably with climatic conditions and elevation. Regarding alpine regions, lower elevations mean generally earlier and faster melting, more rain-on-snow events and shallower snowpack. Therefore, we assessed the applicability of the GNSS-based SWE measurement at four stations along a steep elevation gradient (820, 1185, 1510 and 2540 m a.s.l.) in the eastern Swiss Alps during two winter seasons (2018–2020). Reference data of SWE, LWC and HS were collected manually and with additional automated sensors at all locations. The GNSS-derived SWE estimates agreed very well with manual reference measurements along the elevation gradient and the accuracy (RMSE = 34 mm, RMSRE = 11 %) was similar under wet- and dry-snow conditions, although significant differences in snow density and meteorological conditions existed between the locations. The GNSS-derived SWE was more accurate than measured with other automated SWE sensors. However, with the current version of the GNSS algorithm, the determination of daily changes of SWE was found to be less suitable compared to manual measurements or pluviometer recordings and needs further refinement. The values of the GNSS-derived LWC were robust and within the precision of the manual and radar measurements. The additionally derived HS correlated well with the validation data. We conclude that SWE can reliably be determined using low-cost GNSS-sensors under a broad range of climatic conditions and LWC and HS are valuable add-ons.

/pdf/gnss-signal-based-snow-water-equivalent-determination-for-3yu23lqw75.pdf

GNSS signal-based snow water equivalent determination for different snowpack conditions along a steep elevation gradient

Real-Time Kinematic (RTK) positioning with low-cost mass-market Global Navigation Satellite System (GNSS) receivers and antennas is attractive for precise landing of Unmanned Air Vehicles (UAV). Code multipath mitigation and a reliable resolution of the carrier phase integer ambiguities are two challenges. In this paper, we describe an RTK method which estimates a code multipath parameter for each double difference to fully exploit the temporal correlation of multipath and to prevent a mapping of the multipath into the baseline and ambiguities. The ambiguity fixing is performed in two phases: In the first phase, sets of integer candidate vectors are derived from the float solution at multiple epochs. We merge the sets of candidate vectors to increase the likelihood of including the correct candidate vector in the set of candidates. In the second phase, we track each candidate vector by determining a single epoch baseline estimate for each candidate vector. The respective measurement residuals are accumulated over time to increase the likelihood of selecting the correct candidate. The proposed method was applied to real measurements from two low-cost ANavS GPS modules and enabled a millimeter-level positioning accuracy despite code multipath of up to 50 m.

/pdf/real-time-kinematic-positioning-for-unmanned-air-vehicles-33ejoemkri.pdf

Real-time kinematic positioning for unmanned air vehicles

A method for determining at least one real-valued parameter, in particular an absolute or relative position of a receiver is proposed. The method uses a satellite navigation system comprising a plurality of satellites, which emit navigation signals on carrier signals. The method comprises the steps: 
- phase measurements on the carriers of the navigation signals are performed (12), 
- a real-valued float solution for at least one real-valued parameter and for phase ambiguities of the phase measurements and a corresponding covariance matrix are determined, 
- a sequential resolution of the phase ambiguities is performed, wherein a particular ambiguity to be resolved is mapped on a fixed ambiguity in dependency of the previously fixed ambiguities, wherein the mapping of a particular ambiguity to be resolved to the fixed ambiguity is performed by setting the fixed ambiguity equal to a weighted sum of integer candidates for the particular ambiguity, and 
- the float solution of the at least one real-valued parameter is adjusted to the fixed ambiguities

Method, network of reference stations and mobile navigation device for determining at least one real valued parameter of a receiver, in particular an absolute or relative position of the receiver, by means of a satellite navigation system

Precise point positioning with integer ambiguity resolution requires precise knowledge of satellite position, clock and phase bias corrections. In this paper, a method for the estimation of these parameters with a global network of reference stations is presented. The method processes uncombined and undifferenced measurements of an arbitrary number of frequencies such that the obtained satellite position, clock and bias corrections can be used for any type of differenced and/or combined measurements. We perform a clustering of reference stations. The clustering enables a common satellite visibility within each cluster and an efficient fixing of the double difference ambiguities within each cluster. Additionally, the double difference ambiguities between the reference stations of different clusters are fixed. We use an integer decorrelation for ambiguity fixing in dense global networks. The performance of the proposed method is analysed with both simulated Galileo measurements on E1 and E5a and real GPS measurements of the IGS network. We defined 16 clusters and obtained satellite position, clock and phase bias corrections with a precision of better than 2 cm.

https://link.springer.com/content/pdf/10.1007%2Fs00190-018-1146-y.pdf

Patrick Henkel

Papers

Estimation of phase and code biases on multiple frequencies with a Kalman filter

GNSS signal-based snow water equivalent determination for different snowpack conditions along a steep elevation gradient

Real-time kinematic positioning for unmanned air vehicles

Method, network of reference stations and mobile navigation device for determining at least one real valued parameter of a receiver, in particular an absolute or relative position of the receiver, by means of a satellite navigation system

Estimation of satellite position, clock and phase bias corrections