Communications in highly dynamic channels relying on training-based channel estimation experience a trade-off between increasing channel measurement accuracy by sending more frequent training sequences and increasing data rate by sending fewer training sequences. Simultaneously, most communication systems use forward error correction to enable error detection and correction at the receiver. This paper presents decoder-provided pilots for time-varying channels by using decoded codewords as training sequences to update the channel estimate at the receiver. In contrast to approaches such as data-aided channel estimation, decision-feedback equalization, joint channel estimation and error correction, and turbo equalization, the decoder-provided pilots approach is non-iterative, which is ideal for low-latency requirements in highly dynamic scenarios. Furthermore, it is modulation-, code-, and decoder-agnostic, meaning it can be implemented on top of virtually any communication system that uses forward error correction. From an information-theoretic perspective, we derive the fundamental limits of decoder-provided pilots' ability to simultaneously sense the channel and transmit data. Simu
Pilots operating modern cockpits often face high cognitive demands due to complex interfaces and multitasking requirements, which can lead to overload and decreased performance. This study introduces AdaptiveCoPilot, a neuroadaptive guidance system that adapts visual, auditory, and textual cues in real time based on the pilot's cognitive workload, measured via functional Near-Infrared Spectroscopy (fNIRS). A formative study with expert pilots (N=3) identified adaptive rules for modality switching and information load adjustments during preflight tasks. These insights informed the design of AdaptiveCoPilot, which integrates cognitive state assessments, behavioral data, and adaptive strategies within a context-aware Large Language Model (LLM). The system was evaluated in a virtual reality (VR) simulated cockpit with licensed pilots (N=8), comparing its performance against baseline and random feedback conditions. The results indicate that the pilots using AdaptiveCoPilot exhibited higher rates of optimal cognitive load states on the facets of working memory and perception, along with reduced task completion times. Based on the formative study, experimental findings, qualitative interv
Orthogonal Time Frequency Space (OTFS) modulation has recently garnered attention for its robustness in high-mobility wireless communication environments. In OTFS, the data symbols are mapped to the Doppler-Delay (DD) domain. In this paper, we address low-overhead, scalable pilot-aided estimation of channel state information (CSI) for MIMO OTFS systems. Existing channel estimation techniques either require non-overlapping DD domain pilots with guard regions across multiple antennas, thus sacrificing significant communication rate as the number of transmit antennas increases, or allow pilots to overlap between antennas and rely on high-complexity methods to mitigate pilot pollution. We propose a novel pilot placement approach that embeds pilots within the time-frequency (TF) frame of each OTFS burst, along with a new use of TF and DD guard bins to preserve waveform orthogonality on the TF pilot bins and data integrity in the DD domain, respectively. The proposed pilot placement enables low-complexity coarse estimation of the channel parameters. Moreover, the pilot orthogonality allows the construction of a virtual array (VA), enabling the formulation of a sparse signal recovery (SSR
In this paper, we consider the problem of spread pilot design and effective channel estimation in multiple-input multiple-output Zak-OTFS (MIMO-Zak-OTFS) with superimposed spread pilots, where data and spread pilot signals are superimposed in the same frame. To achieve good estimation performance in a MIMO setting, the spread pilots at different transmit antennas need to be effectively separated at the receiver. Towards this, we propose a spread pilot design that separates the pilot sequences in the cross-ambiguity domain and enables the estimation of the effective channel taps by a simple read-off operation. To further alleviate the effect of pilot-data interference on performance, we carry out turbo iterations between channel estimation and detection. Simulation results for $2\times 2$ and $3\times 3$ MIMO-Zak-OTFS with Gaussian-sinc pulse shaping filter for vehicular-A channel model show that the proposed pilot design and estimation scheme with three turbo iterations can achieve very good estimation/detection performance.
Looking towards 6G wireless systems, frequency bands like the sub-terahertz (sub-THz) band (100 GHz - 300 GHz) are gaining traction for their promises of large available swaths of bandwidth to support the ever-growing data demands. However, challenges with harsh channel conditions and hardware nonlinearities in the sub-THz band require robust communication techniques with favorable properties, such as good spectral efficiency and low peak-to-average power ratio (PAPR). Recently, OTFS and its variants have garnered significant attention for their performance in severe conditions (like high delay and Doppler), making it a promising candidate for future communications. In this work, we implement Zak-OTFS for the over-the-air experiments with traditional point pilots and the new spread pilots. Notably, we design our spread-pilot waveforms with communications and sensing coexisting in the same radio resources. We define the system model and the signal design for integration onto our state-of-the-art sub-THz wireless testbed. We show successful data transmission over-the-air at 140 GHz and 240 GHz in a variety of signal-to-noise ratio (SNR) conditions. In addition, we demonstrate integra
In this paper, we investigate the downlink throughput performance of a massive multiple-input multiple-output (MIMO) system that employs superimposed pilots for channel estimation. The component of downlink (DL) interference that results from transmitting data alongside pilots in the uplink (UL) is shown to decrease at a rate proportional to the square root of the number of antennas at the BS. The normalized mean-squared error (NMSE) of the channel estimate is compared with the Bayesian Cramér-Rao lower bound that is derived for the system, and the former is also shown to diminish with increasing number of antennas at the base station (BS). Furthermore, we show that staggered pilots are a particular case of superimposed pilots and offer the downlink throughput of superimposed pilots while retaining the UL spectral and energy efficiency of regular pilots. We also extend the framework for designing a hybrid system, consisting of users that transmit either regular or superimposed pilots, to minimize both the UL and DL interference. The improved NMSE and DL rates of the channel estimator based on superimposed pilots are demonstrated by means of simulations.
The drone industry is diversifying and the number of pilots increases rapidly. In this context, flight schools need adapted tools to train pilots, most importantly with regard to their own awareness of their physiological and cognitive limits. In civil and military aviation, pilots can train themselves on realistic simulators to tune their reaction and reflexes, but also to gather data on their piloting behavior and physiological states. It helps them to improve their performances. Opposed to cockpit scenarios, drone teleoperation is conducted outdoor in the field, thus with only limited potential from desktop simulation training. This work aims to provide a solution to gather pilots behavior out in the field and help them increase their performance. We combined advance object detection from a frontal camera to gaze and heart-rate variability measurements. We observed pilots and analyze their behavior over three flight challenges. We believe this tool can support pilots both in their training and in their regular flight tasks. A demonstration video is available on https://www.youtube.com/watch?v=eePhjd2qNiI
When the delay period of the Zak-OTFS carrier is greater than the delay spread of the channel, and the Doppler period of the carrier is greater than the Doppler spread of the channel, the effective channel filter taps can simply be read off from the response to a single pilot carrier waveform. The input-output (I/O) relation can then be reconstructed for a sampled system that operates under finite duration and bandwidth constraints. We introduce a framework for pilot design in the delay-Doppler (DD) domain which makes it possible to support users with very different delay-Doppler characteristics when it is not possible to choose a single delay and Doppler period to support all users. The method is to interleave single pilots in the DD domain, and to choose the pilot spacing so that the I/O relation can be reconstructed by solving a small linear system of equations.
We consider a cell-free massive MIMO system with multiple antennas on the users and access points. In previous works, the downlink spectral efficiency (SE) has been evaluated using the hardening bound that requires no downlink pilots. This approach works well when having single-antenna users. In this paper, we show that much higher SEs can be achieved if downlink pilots are sent since the effective channel matrix does not harden when having multi-antenna users. We propose a pilot-based downlink estimation scheme and derive a new SE expression that utilizes zero-forcing combining. We show numerically how the number of users and user antennas affects the SE.
The recent proposed affine frequency division multiplexing (AFDM) employing a multi-chirp waveform has shown its reliability and robustness in doubly selective fading channels. In the existing embedded pilot-aided channel estimation methods, the presence of guard symbols in the discrete affine Fourier transform (DAFT) domain causes inevitable degradation of the spectral efficiency (SE). To improve the SE, we propose a novel AFDM channel estimation scheme by introducing the superimposed pilots in the DAFT domain. An effective pilot placement method that minimizes the channel estimation error is also developed with a rigorous proof. To mitigate the pilot-data interference, we further propose an iterative channel estimator and signal detector. Simulation results demonstrate that both channel estimation and data detection performances can be improved by the proposed scheme as the number of superimposed pilots increases.
Multi-task missions for unmanned aerial vehicles (UAVs) involving inspection and landing tasks are challenging for novice pilots due to the difficulties associated with depth perception and the control interface. We propose a shared autonomy system, alongside supplementary information displays, to assist pilots to successfully complete multi-task missions without any pilot training. Our approach comprises of three modules: (1) a perception module that encodes visual information onto a latent representation, (2) a policy module that augments pilot's actions, and (3) an information augmentation module that provides additional information to the pilot. The policy module is trained in simulation with simulated users and transferred to the real world without modification in a user study (n=29), alongside alternative supplementary information schemes including learnt red/green light feedback cues and an augmented reality display. The pilot's intent is unknown to the policy module and is inferred from the pilot's input and UAV's states. The assistant increased task success rate for the landing and inspection tasks from [16.67% & 54.29%] respectively to [95.59% & 96.22%]. With the
In this paper, superimposed pilots are introduced as an alternative to time-multiplexed pilot and data symbols for mitigating pilot contamination in massive multiple-input multiple-output (MIMO) systems. We propose a non-iterative scheme for uplink channel estimation based on superimposed pilots and derive an expression for the uplink signal-to-interference-plus-noise ratio (SINR) at the output of a matched filter employing this channel estimate. Based on this expression, we observe that power control is essential when superimposed pilots are employed. Moreover, the quality of the channel estimate can be improved by reducing the interference that results from transmitting data alongside the pilots, and an intuitive iterative data-aided scheme that reduces this component of interference is also proposed. Approximate expressions for the uplink SINR are provided for the iterative data-aided method as well. In addition, we show that a hybrid system with users utilizing both time-multiplexed and superimposed pilots is superior to an optimally designed system that employs only time-multiplexed pilots, even when the non-iterative channel estimate is used to build the detector and precoder
The Neyman Allocation is used in many papers on experimental design, which typically assume that researchers have access to large pilot studies. This may be unrealistic. To understand the properties of the Neyman Allocation with small pilots, we study its behavior in an asymptotic framework that takes pilot size to be fixed even as the size of the main wave tends to infinity. Our analysis shows that the Neyman Allocation can lead to estimates of the ATE with higher asymptotic variance than with (non-adaptive) balanced randomization. In particular, this happens when the outcome variable is relatively homoskedastic with respect to treatment status or when it exhibits high kurtosis. We provide a series of empirical examples showing that such situations can arise in practice. Our results suggest that researchers with small pilots should not use the Neyman Allocation if they believe that outcomes are homoskedastic or heavy-tailed. Finally, we examine some potential methods for improving the finite sample performance of the FNA via simulations.
Pilot contamination, caused by the reuse of pilots among interfering cells, remains as a significant obstacle that limits the performance of massive multi-input multi-output antenna systems. To handle this problem, less aggressive reuse of pilots involving allocation of additional pilots for interfering users is closely examined in this paper. Hierarchical pilot reuse methods are proposed, which effectively mitigate pilot contamination and increase the net throughput of the system. Among the suggested hierarchical pilot reuse schemes, the optimal way of assigning pilots to different users is obtained in a closed-form solution which maximizes the net sum-rate in a given coherence time. Simulation results confirm that when the ratio of the channel coherence time to the number of users in each cell is sufficiently large, less aggressive reuse of pilots yields significant performance advantage relative to the case where all cells reuse the same pilot set.
This letter shows that optimizing the transmit powers along with optimally designed nonorthogonal pilots can significantly reduce pilot contamination and improve the overall throughput of the uplink multi-cell massive multiple-input multiple-output (MIMO) system as compared to the conventional schemes that use orthogonal pilots. Given the optimized nonorthogonal pilots, power control as a function of the large-scale path-loss can be thought of as a stochastic optimization problem due to the presence of fast fading. This paper advocates a deterministic approach to solve this problem, then further proposes a stochastic optimization method that utilizes successive convex approximation as a benchmark to quantify the performance of the proposed approach. Simulation results reveal significant advantage of using optimized nonorthogonal pilots together with power control to combat pilot contamination.
In this work, novel physical layer security (PLS) schemes are proposed for orthogonal frequency-division multiplexing (OFDM) to secure both data and pilots. The majority of previous studies focus on only securing the data without considering the security of the pilots used for channel estimation. However, the leakage of channel state information (CSI) from a legitimate node to an eavesdropper allows the latter to acquire knowledge about the channel of the legitimate nodes. To this end, we propose adaptive and flexible PLS algorithms which can 1) secure data, 2) secure pilots, and 3) jointly secure both data and pilots. Particularly, minimum-phase all-pass channel decomposition is exploited, where the proposed algorithms use the all-pass component to provide security without harming the performance of the legitimate user. In the analysis for data security, we evaluated the secrecy under correlated and uncorrelated eavesdropping channels via closed-form bit error rate (BER) formulas. For pilot security, we analyzed the normalized mean squared error (NMSE) performance of the estimated channel. The simulation results along with theoretical analysis demonstrate that the proposed algorit
We designed and evaluated an AI pilot in a planetarium visualization software, OpenSpace, for public shows in science centers. The piloting role is usually given to a human working in close collaboration with the guide on stage. We recruited 7 professional guides with extensive experience in giving shows to the public to study the impact of the AI-piloting on the overall experience. The AI-pilot is a conversational AI-agent listening to the guide and interpreting the verbal statements as commands to execute camera motions, change simulation time, or toggle visual assets. Our results show that, while AI pilots lack several critical skills for live shows, they could become useful as co-pilots to reduce workload of human pilots and allow multitasking. We propose research directions toward implementing visualization pilots and co-pilots in live settings.
This paper investigates the statistical ambiguity functions (AFs) of orthogonal frequency division multiplexing (OFDM) waveforms that incorporate deterministic unit-modulus pilot symbols and random data payloads for integrated sensing and communication (ISAC). We derive analytical expressions for the mean squared discrete periodic ambiguity function (DP-AF) and fast-slow-time ambiguity function (FST-AF) of such pilot-embedded OFDM signals. Our analysis demonstrates that, under a fixed signal length and constellation scheme, the mean squared DP-AF depends jointly on the pilot patterns, pilot symbols and number of pilots, while the mean squared FST-AF relies only on the number of pilots. Numerical simulations closely match the theoretical expressions. Furthermore, in numerical results, we show that different pilot patterns correspond to DP-AF with distinct characteristics, offering relevant considerations for pilot design in communication-centric ISAC systems.
Pilot studies (PS) are ubiquitous in HCI research. CHI papers routinely reference 'pilot studies', 'pilot tests', or 'preliminary studies' to justify design decisions, verify procedures, or motivate methodological choices. Yet despite their frequency, the role of pilot studies in HCI remains conceptually vague and empirically underexamined. Unlike fields such as medicine, nursing, and education, where pilot and feasibility studies have well-established definitions, guidelines, reporting standards and even a dedicated research journal, the CHI community lacks a shared understanding of what constitutes a pilot study, why they are conducted, and how they should be reported. Many papers reference pilots 'in passing', without details about design, outcomes, or how the pilot informed the main study. This variability suggests a methodological blind spot in our community.
Most skydiving accidents occur during the parafoil-piloting and landing stages and result from human lapses in judgment while piloting the parafoil. Training of novice pilots is protracted due to the lack of functional and easily accessible training simulators. Moreover, work on parafoil trajectory planning suitable for aiding human training remains limited. To bridge this gap, we study the problem of computing safe trajectories for human-piloted parafoil flight and examine how such trajectories fare against human-generated solutions. For the algorithmic part, we adapt the sampling-based motion planner Stable Sparse RRT (SST) by Li et al., to cope with the problem constraints while minimizing the bank angle (control effort) as a proxy for safety. We then compare the computer-generated solutions with data from human-generated parafoil flight, where the algorithm offers a relative cost improvement of 20\%-80\% over the performance of the human pilot. We observe that human pilots tend to, first, close the horizontal distance to the landing area, and then address the vertical gap by spiraling down to the suitable altitude for starting a landing maneuver. The algorithm considered here m