Joint Communications, Sensing and PNT

• JCSAP is the full-service convergence of communications, sensing, and PNT, using shared spectrum, hardware, and co-designed waveforms to deliver unified capabilities.
• Architectural designs in JCSAP span cooperative, integrated, and joint modalities that optimize RF front-ends, digital processing, and beamforming for efficient, multi-functional operations.
• Performance metrics for JCSAP address trade-offs among BER, MSE, and localization errors, leveraging advanced signal processing and estimation theory to enhance system reliability.

Searching arXiv for recent and foundational papers on JCSAP and closely related JCAS/ISAC formulations to ground the article. Joint Communications, Sensing, and PNT (JCSAP) denotes the full-service convergence of communications, sensing, and positioning, navigation, and timing on a single platform or payload, with shared front-ends, spectrum, and, in the most integrated form, jointly designed waveforms and processing (Sheemar et al., 30 Sep 2025). Within the multi-functional satellite systems taxonomy, JCSAP is the highest level of integration, whereas terrestrial and maritime realizations often emphasize the same underlying principle: the same beams, pilots, and baseband processing can support data delivery, target/environment sensing, and PNT observables such as time-of-arrival, Doppler, angle, and time transfer (Sheemar et al., 9 Jan 2025). The field therefore spans payload co-design, receiver and precoder optimization, waveform design, statistical performance analysis, and system-level resource management across cellular, mmWave, maritime, and non-terrestrial networks (Xiong et al., 13 Jul 2026).

1. Taxonomy and scope

The literature distinguishes JCSAP from partial integrations rather than treating all integrated sensing-and-communication systems as equivalent (Sheemar et al., 30 Sep 2025).

Class	Integrated functions	Characterization
JCAS	Communications and sensing	Shared spectrum/hardware and coordinated waveforms
JCAP	Communications and PNT	Communications payload supports or embeds PNT
JSAP	Sensing and PNT	Sensing payloads are fused with PNT services
JCSAP	Communications, sensing, and PNT	Full-service convergence on a single platform/payload

The convergence level itself spans three design modalities. In a cooperative design, co-located functions share hardware but retain distinct waveforms or bands. In an integrated design, functions share band or hardware with time, space, or code multiplexing to avoid harmful interference. In a joint design, a single multifunctional signal and receiver chain are co-designed to satisfy all three functions simultaneously (Sheemar et al., 30 Sep 2025). This distinction is important because many papers instantiate only one or two parts of the full JCSAP stack.

A common misconception is that any JCAS realization is automatically a JCSAP realization. The record is more specific. For example, the multi-modal dynamic spectrum access system with image and wireless data modalities is explicitly a joint communications-and-sensing system for transmitter identification, while “PNT is not covered” and “PNT is explicitly out of scope” (Sagduyu et al., 2023). By contrast, the joint receiver framework for integrated sensing and communications explicitly maps delay, Doppler, and angle estimates to range, radial velocity, bearing, timing, and multilateration, thereby supplying a direct pathway from sensing outputs to PNT observables (Dong et al., 2022).

2. Architectural integration and hardware realizations

At payload level, JCSAP architectures are typically described in terms of a shared RF front-end and antenna aperture, a partition into RF Unit and Digital Processing Unit, an On-Board Digital Processor for software-defined routing and scheduling, and software-defined payloads with multi-band transceivers and programmable channelizers (Sheemar et al., 30 Sep 2025). These building blocks support cooperative, integrated, and joint operation while exposing the core system constraints: power, bandwidth, beam agility, synchronization, and regulatory masks.

Several terrestrial architectures illustrate how these principles are realized under different hardware assumptions. A half-duplex 6G design uses a common half-duplex base station that transmits downlink OFDM and a dedicated FMCW receiver co-located at the BS for sensing, thereby avoiding in-band full-duplex OFDM sensing and its severe self-interference burden (Ma et al., 2022). In that framework, random time-division restores the sensing-only unambiguous Doppler span while using only a fraction $1/M$ of sensing occasions, and flexible sensing-implanted OFDM places sensing on $1/M$ of the subcarriers while leaving $(M-1)/M$ for data (Ma et al., 2022). By contrast, a full-duplex MIMO architecture with a near-field RIS jointly optimizes digital beamformers and RIS phase configuration to handle self-interference while improving sensing and communications performance (Sheemar et al., 2023).

Programmable propagation surfaces have become a major branch of the field. STAR-RIS introduces simultaneous transmission and reflection with energy splitting, mode switching, and time switching, together with per-element transmission and reflection coefficients obeying $\alpha_n^t+\alpha_n^r=1$ in energy-splitting operation (Khan et al., 10 Feb 2026). Holographic JCAS replaces conventional array abstractions with a reconfigurable holographic surface whose analog beamforming matrix is $W=\mathrm{diag}(w)\Phi$, where $0\le w_i\le 1$, and uses arbitrary inter-element spacing to increase spatial control and derive exact Cramér–Rao Bounds for azimuth and elevation (Sheemar et al., 21 Feb 2025). A plausible implication is that JCSAP hardware is no longer defined only by antenna count, but by how precisely the platform can shape beams, multipath, and timing geometry across communications and sensing tasks.

A further hardware direction is low-complexity hybrid beamforming. One mmWave design combines wideband analog beamforming for fine ToA extraction and narrowband digital beamforming for high-rank AoA estimation, avoiding the aggregate sampling rate of fully digital wideband arrays (Bedin et al., 2023). In the reported example with $N=16$ and $B_A=400$ MHz, the proposed architecture uses approximately $800$ MS/s versus $6.4$ GS/s for a fully digital implementation, with approximately $1/M$0 ADC power reduction (Bedin et al., 2023). This is directly relevant to JCSAP because PNT-grade delay and angle extraction must often coexist with stringent power and form-factor constraints.

3. Signal models, estimation theory, and PNT observables

A central JCSAP theme is that communication and sensing signals are not merely coexisting; they are statistically coupled in the receiver and in the estimators. A representative receive model is

$1/M$1

where a communication stream and a target echo are simultaneously present at the receiver (Dong et al., 2022). In that formulation, the communication detector is built from a whitening matrix $1/M$2 and a maximal-ratio combining vector $1/M$3, while sensing can be performed either by interference cancellation followed by linear MMSE or by a tailored non-IC MMSE estimator that marginalizes over the discrete communication constellation (Dong et al., 2022). The reported conclusion is precise: the Non-IC design is independent of the detector, avoids error propagation inherent in IC, and achieves optimal sensing MMSE while the ML detector remains optimal for communications (Dong et al., 2022).

The PNT mapping is explicit in several formulations. With estimated delay $1/M$4, monostatic range is

$1/M$5

and with Doppler $1/M$6, radial velocity is

$1/M$7

Angle can be extracted by array processing, for example with MUSIC,

$1/M$8

and position can then be formed by multilateration or by direct angle–range mapping, depending on geometry (Dong et al., 2022). Time-transfer and synchronization enter through ToA and two-way timing models, and the timing accuracy is commonly summarized by bounds such as

$1/M$9

which reappears in both terrestrial and satellite JCSAP discussions (Sheemar et al., 30 Sep 2025).

Another line of work formulates sensing performance directly in information-theoretic terms. In stochastic-geometry analysis of mmWave JCAS networks, sensing coverage probability is defined as the probability that the rate of information extracted about the parameters of interest exceeds a threshold, and a sensing SINR surrogate is constructed from the Fisher Information Matrix and mutual-information bounds (Olson et al., 2022). This broadens the performance lens beyond classical detection or estimation error and is especially relevant to JCSAP because PNT accuracy is itself an estimation problem governed by the FIM, CRLBs, and geometry.

4. Representative system realizations

The application space of JCSAP is heterogeneous, and the literature contains several concrete realizations that illustrate different integration mechanisms.

A task-oriented dynamic spectrum access system couples camera images with wireless sensing returns for transmitter identification (Sagduyu et al., 2023). An edge device captures a $(M-1)/M$0 image, compresses it from dimension $(M-1)/M$1 to $(M-1)/M$2, transmits a channel-optimized feature vector, receives a sensing return generated by reflections of that same waveform, re-encodes the sensing signal into $(M-1)/M$3 symbols, and lets a fusion-center decoder make the binary decision (Sagduyu et al., 2023). Under the default setting, the reported accuracy is $(M-1)/M$4 in AWGN and $(M-1)/M$5 in Rayleigh, with joint sensing and image-task features consistently outperforming sensing-only baselines across SNRs (Sagduyu et al., 2023). The system is archetypal JCS, but it also illustrates a boundary condition of the broader field: the paper explicitly excludes PNT.

OFDM-based mmWave JCS has been pushed toward super-resolution with subspace methods. A MUSIC-based downlink system operating at $(M-1)/M$6 GHz with $(M-1)/M$7 BS UPAs, $(M-1)/M$8, $(M-1)/M$9, and $\alpha_n^t+\alpha_n^r=1$0 MHz replaces grid-limited FFT sensing with sequential AoA, range, and Doppler MUSIC processing, then uses the sensed delay in a Kalman filter to enhance CSI for communications demodulation (Chen et al., 2022). The reported gains are more than $\alpha_n^t+\alpha_n^r=1$1 dB in sensing MSE relative to FFT baselines, together with substantial BER reductions when CSI enhancement is used (Chen et al., 2022). Because AoA, range, and Doppler are directly estimated, the same outputs naturally support 3D localization and tracking.

Waveform design has also been used to recover sensing capability lost in conventional time-sharing. In half-duplex 6G JCS, random time-division and flexible sensing-implanted OFDM recover the sensing-only unambiguous Doppler span while sharing resources with communications, a property termed super sensing range (Ma et al., 2022). With $\alpha_n^t+\alpha_n^r=1$2 GHz, $\alpha_n^t+\alpha_n^r=1$3 MHz, and $\alpha_n^t+\alpha_n^r=1$4, the design preserves $\alpha_n^t+\alpha_n^r=1$5 km/h for sensing-only, RTD, and FSI-OFDM, whereas periodic TDD at $\alpha_n^t+\alpha_n^r=1$6 sensing fraction reduces the unambiguous speed to approximately $\alpha_n^t+\alpha_n^r=1$7 km/h (Ma et al., 2022). The same framework also uses CP-assisted dual-window processing to extend range coverage without lengthening the symbol.

At network level, multi-cell coordination changes the sensing–communications trade-off. In a multi-cell MISO downlink with block-level precoders, coordinated beamforming treats inter-cell reflections as interference, whereas coordinated multi-point treats them as known signal contributions, leading to a lower azimuth-angle CRB at the same minimum-SINR target (Babu et al., 2024). The paper’s simulations show that neglecting inter-cell reflections degrades angle estimation, and that CoMP consistently outperforms CBF in sensing while also improving communication performance (Babu et al., 2024). This is directly relevant to JCSAP because multi-anchor angle estimates are fundamental to geometric localization.

Non-terrestrial realizations make the PNT dimension explicit. An integrated satellite-terrestrial maritime system uses a shore-based TBS and a LEO satellite that jointly provide communications and bistatic target sensing in the VHF band with $\alpha_n^t+\alpha_n^r=1$8 MHz and $\alpha_n^t+\alpha_n^r=1$9 MHz (Xiong et al., 13 Jul 2026). The system derives a CRB for target position through Jacobians from $W=\mathrm{diag}(w)\Phi$0 to $W=\mathrm{diag}(w)\Phi$1, then solves a joint beamforming optimization that maximizes user sum rate subject to localization-accuracy and power constraints (Xiong et al., 13 Jul 2026). The architecture uses GNSS pulse-per-second synchronization between the TBS and satellite, and the sensing algorithm is based on differential evolution for angle estimation (Xiong et al., 13 Jul 2026). In this case, communications, sensing, and PNT are all explicit components of the formulation.

5. Performance metrics and trade-offs

JCSAP is intrinsically multi-objective, and its metrics span link-layer, sensing, and navigation domains. Communications is commonly quantified through BER, SINR, achievable rate, or weighted sum-rate, for example

$W=\mathrm{diag}(w)\Phi$2

while sensing is evaluated through detection probability, false alarm probability, MSE, SCNR, or CRB/SPEB-type bounds (Sheemar et al., 30 Sep 2025). PNT metrics add pseudorange error, localization RMSE, GDOP or PDOP, velocity RMSE, timing error, and Allan deviation for clock stability (Sheemar et al., 30 Sep 2025).

The trade-offs are rarely monotone. In multi-cell coordinated JSC, the relative CRB grows rapidly as the minimum-SINR requirement increases because more power must be steered to users and away from sensing directions (Babu et al., 2024). In holographic JCAS, a weighted multi-objective design explicitly maximizes communication rate while minimizing $W=\mathrm{diag}(w)\Phi$3, thereby tracing different Pareto points by changing the weights $W=\mathrm{diag}(w)\Phi$4 and $W=\mathrm{diag}(w)\Phi$5 (Sheemar et al., 21 Feb 2025). In STAR-RIS-enabled systems, throughput, SCNR, CRB, and fairness are coupled through transmission/reflection coefficients, phase quantization, and hardware losses (Khan et al., 10 Feb 2026).

There are also non-obvious interference interactions. In multi-user MIMO JCAS, the use of the communication signal for sensing can prevent a loss in communication performance if channel interference occurs, whereas the kurtosis of the transmit alphabet limits sensing performance (Muth et al., 28 Jan 2026). The analytical result is that sensing should illuminate a sector with the single stream having the lowest kurtosis, and in overlapping sectors the affected UE’s communication signal can be reused for sensing to avoid an explicit interference term in the SINR (Muth et al., 28 Jan 2026). This result links waveform statistics directly to the communications–sensing operating point.

System geometry matters just as much as waveform or precoder design. In a stochastic-geometry framework for mmWave JCAS, network densification improves sensing SINR performance—in contrast to communications (Olson et al., 2022). The explanation given in that work is tied to the steeper two-way path loss of radar: shrinking link distances improves the desired sensing path faster than interference rises, whereas downlink communication becomes increasingly interference-limited in dense deployments (Olson et al., 2022). For JCSAP, this means that communications-optimal and PNT-optimal network densification need not coincide.

6. Limitations, controversies, and open directions

A recurring controversy concerns what “integration” should mean in practice. Some designs avoid in-band full-duplex entirely by adding a dedicated FMCW sensing chain to a half-duplex BS, arguing that aggressive self-interference suppression before ADC is otherwise required because echo power may be $W=\mathrm{diag}(w)\Phi$6 dB below self-interference (Ma et al., 2022). Other designs embrace full-duplex and use SI-aware RIS or joint beamformer/RIS optimization to loosen the requirement for additional SI cancellation (Sheemar et al., 2023). The literature therefore does not converge on a single hardware doctrine; it instead exposes a design spectrum shaped by complexity, dynamic range, and calibration.

Another persistent limitation is realism. Many papers rely on AWGN, Rayleigh, LoS, or single-target models, and several explicitly identify the need for richer models of clutter, multipath, hardware impairments, calibration drift, and synchronization error (Sagduyu et al., 2023). Maritime and satellite studies emphasize rain attenuation, Earth-curvature LoS boundaries, LEO Doppler, feeder-link coordination, and multilayer synchronization because tiny timing errors lead to meter-level ranging errors (Sheemar et al., 9 Jan 2025). STAR-RIS and holographic formulations add further realism gaps, including amplitude–phase coupling, phase quantization, mutual coupling, insertion losses, and the difficulty of acquiring cascaded CSI under mobility (Khan et al., 10 Feb 2026).

PNT itself remains unevenly integrated across the literature. Some works derive direct mappings from delay, Doppler, and angle to range, velocity, timing, and localization (Dong et al., 2022); others use CRB or SPEB formulations that can be propagated to position error bounds (Sheemar et al., 21 Feb 2025); and still others remain strictly JCAS despite being highly relevant to JCSAP (Sagduyu et al., 2023). This suggests that a mature JCSAP system requires not only shared signals and hardware, but also explicit state estimation, synchronization, and integrity models.

The open directions are correspondingly broad. Surveys identify waveform co-design under hardware nonidealities, synchronization under extreme LEO dynamics, interference-aware resource management, AI-native controllers, digital twins, cooperative satellite constellations, reconfigurable surfaces, and JCSAP-specific standardization gaps as major unresolved problems (Sheemar et al., 30 Sep 2025). Satellite studies add multi-target detection, multilayer clock management, ISL-assisted time transfer, and robust TDOA/FDOA fusion (Sheemar et al., 9 Jan 2025). A plausible implication is that the field is moving from pairwise integrations toward system-level convergence, where communications reliability, sensing fidelity, and PNT integrity must be optimized together rather than treated as adjacent objectives.