Pith. sign in

REVIEW 4 major objections 4 minor 2 cited by

A MIMO ISAC System for Ultra-Reliable and Low-Latency Communications

T0 review · 4 major / 4 minor · reviewed 2026-08-10 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read A sensing-triggered MIMO ISAC scheme with dirty-paper coding promises higher eMBB rates while meeting URLLC and detection constraints.

desk verdict Good premise, but the central rate bound assumes an independence the system model itself breaks. read the letter →

arxiv 2501.13025 v2 pith:7LRSLWST submitted 2025-01-22 cs.IT math.IT

Homa Nikbakht , Yonina C. Eldar , H. Vincent Poor This is my paper · ORCID
classification cs.ITmath.IT MSC 94A1594A40
keywords integratedsensingandcommunicationURLLCdirty-papercodingfiniteblocklengthMIMOrate-reliability-detectiontradeofftargetdetectioneMBB
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper tries to show that a single MIMO base station can handle three jobs at once—carrying high-rate eMBB traffic, delivering randomly arriving ultra-reliable low-latency (URLLC) messages, and sensing a target—without dedicating separate resources to each. The proposed system detects the target with a sensing receiver, and that detection itself triggers the next URLLC transmission, so no external arrival model is needed. The key claim is that dirty-paper coding can cancel the interference of both the sensing waveform and the in-flight eMBB stream from the URLLC signal, yielding a finite-blocklength rate–reliability–detection tradeoff (Theorem 1) in which the eMBB rate bound is maximized subject to URLLC error and target-detection constraints. Numerical results indicate this DPC-based scheme supports a higher eMBB rate than power-sharing or time-sharing while meeting the same URLLC and sensing requirements.

What carries the argument

The load-bearing mechanism is a two-stage dirty-paper coding (DPC) construction. In a block with no URLLC message, DPC with parameter \(\alpha_{s,1}\) precancels the sensing signal from the eMBB codebook. In a block carrying URLLC, the transmitter first precancels the sensing signal from the eMBB signal with \(\alpha_{s,2}\), then precancels the combined eMBB-plus-sensing interference from the URLLC codeword with \(\alpha_u\) (equations 13–18). This makes the URLLC message see an almost interference-free channel despite riding on top of eMBB and sensing. The companion machinery is finite-blocklength Gaussian approximation: the information densities are shown to converge to Gaussians with means and variances built from the eigenvalues of the channel Gram matrices, so error probabilities are handled with Q-functions and Berry–Esseen corrections rather than asymptotic capacity arguments.

What would settle it

Run a Monte Carlo simulation of the sensing-triggered protocol: generate target echoes under Lemma 1's channel model, apply the likelihood-ratio test with the same false-alarm threshold, and record the set of blocks in which a URLLC message is actually transmitted and decoded. If the empirical joint distribution of this set diverges from the product formula \(P[\mathcal{B}_{\mathrm{detect}} = \mathcal{B}_{dt}] = P_{\mathrm{det}}^{|\mathcal{B}_{dt}|}(1-P_{\mathrm{det}})^{\eta-|\mathcal{B}_{dt}|}\) used in Lemma 3, the eMBB rate bound in Theorem 1 is not the true rate of the protocol at finite blocklength.

Watch

Extended reading notes

Core claim

On its own terms, the paper establishes the rate-reliability-detection tradeoff for a bi-static MIMO ISAC system with sensing-triggered URLLC. The central result, Theorem 1 (equation 49), maximizes the upper bound on the eMBB rate, \(R_e \leq C_e - \sqrt{V_e/n}\,$Q^{{-1}}$(\epsilon_e - \Delta_e) - K_e \frac{\log\,n}{n} - \frac{\log\,M_s}{n}\), over the DPC power-splitting parameters \(\beta_u, \beta_{s,1}, \beta_{s,2}\) and \(\alpha_u, \alpha_{s,1}, \alpha_{s,2}\), subject to per-block URLLC error probability at most \(\epsilon_U\) and per-block detection probability at least \(P_D\). This bound is assembled from Lemma 1 (the detection probability expressed through generalized chi-square statistics of the echo), Lemma 2 (the URLLC error probability decomposed into missed-detection, misdecoding, and false-alarm events), and Lemma 3 (the eMBB rate bound conditioned on which blocks were detected as carrying URLLC). The claim that the scheme outperforms power-sharing and time-sharing is that this optimized bound lies strictly above the corresponding bounds of those schemes at the same constraints.

Load-bearing premise

The derivation assumes that whether the UE thinks a URLLC message arrived in a block is an independent coin flip with one fixed probability, even though in the protocol a detection in one block changes how likely the next block carries a URLLC message.

Editorial extensions

If this is right

  • If Theorem 1 is correct, the same power budget can serve eMBB, URLLC, and sensing simultaneously, with no orthogonal resource split, so the eMBB rate is not cut by the sensing duty.
  • Tightening the URLLC reliability requirement \(\epsilon_U\) lowers the maximal eMBB rate; the paper's numerical curves show the scheme absorbs this loss more gently than power- or time-sharing.
  • Raising the required detection probability \(P_D\) also lowers the eMBB rate; at a fixed \(P_D\) the DPC scheme holds a rate margin over both baselines.
  • Because URLLC transmissions are triggered by physical detection rather than by an assumed Bernoulli arrival process, the scheme extends to environments where URLLC events are deterministic or unpredictable.
  • The detector threshold can be set to meet a desired false-alarm probability while the DPC parameters are re-optimized per block, decoupling sensing robustness from communication reliability.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If block-level detection outcomes are serially correlated because a detection in block \(b\) changes the probability of a URLLC transmission in block \(b+1\), the product-form probability in Lemma 3 may overstate how often the UE's detection set matches the true arrival set; a Markov-chain extension could be tested against the paper's binomial formula.
  • The same trigger loop could be inverted: instead of sensing triggering URLLC, a URLLC arrival could be used as a sensing cue, turning the scheme into a communication-driven radar setup.
  • One can test DPC gain with imperfect channel state information by treating estimation error as additional interference to be precanceled; the present framework already supplies the SNR-like terms where such error would enter.
  • Because the sensing receiver and the base station are linked by an ideal backhaul in the paper, a practical latency budget would need to fold backhaul delay into the trigger decision, turning the current per-block tradeoff into a latency-aware scheduling law.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 4 minor

Summary. The paper studies a bi-static MIMO ISAC system in which a sensing receiver detects the presence of a target and, upon detection, triggers the transmission of a URLLC message over the next block. The base station employs dirty-paper coding to precancel sensing and eMBB interference, and the authors derive a finite-blocklength rate-reliability-detection trade-off. The central result, Theorem 1, formulates a constrained maximization of an upper bound on the eMBB rate, with constraints on URLLC decoding error and target detection probability. Numerical results compare the proposed DPC-based scheme against power-sharing and time-sharing baselines and claim significant outperformance.

Significance. If the derivations were sound, the paper would offer a useful finite-blocklength framework for a sensing-triggered URLLC traffic model, which is a nontrivial extension of earlier works that assume Bernoulli or deterministic URLLC arrivals. The random-coding structure and the explicit closed-form expressions for the detection probability, URLLC error probability, and eMBB rate bound are a strength. However, the central rate bound relies on an independence assumption that is contradicted by the paper's own system model, and additional load-bearing steps are asserted rather than proved. As a result, Theorem 1 and the numerical comparisons do not currently provide a reliable achievability statement.

major comments (4)
  1. [Appendix C, Eq. (95)] The binomial formula P[Bdetect = Bdt] = Pdet^{|Bdt|}(1-Pdet)^{eta-|Bdt|} requires the events {b in Bdetect} to be independent and identically distributed across blocks with common probability Pdet. This is not consistent with the system model. In Section II, A_1 = 0 and P(A_b = 1) = P_{b-1,D} for b >= 2, while Lemma 1 shows that P_{b,D} depends on whether b is in Barrival through the factors kappa1 and kappa2 in Eqs. (27)-(29). Hence A_{b+1} depends on A_b through the sensing detection probability, creating serial dependence, and the marginal probability Pdet defined in Eqs. (92)-(94) is not block-invariant because P_{b-1,D} varies with b and with the sensing channel eigenvalues. No conditioning or Markov-chain calculation is provided to replace the product form. Since Ce, Ve, and Delta_e in Eqs. (41)-(48) are weighted by this product, the objective in Theorem 1 and the numerical outperformance claims are not justified.
  2. [Appendix C, Eq. (100)] The expression for P[Ee,1|Bdetect = Bdt] is not a valid product of probabilities over the intended events. For a block b not in Bdt and not in Barrival, the required event is that no false alarm occurs, whose probability is 1 - P[EU,3]. The numerator in Eq. (100) instead uses P[EU,1](1-P_{b-1,D}) for the non-detected blocks, where P[EU,1] is the missed-detection probability defined in Eq. (37) for blocks in which a URLLC was actually transmitted. Thus the second factor in the numerator applies the missed-detection probability to blocks without a URLLC arrival, which is not the event of interest. This directly affects Delta_e in Eq. (48) and therefore the Q^{-1} inversion leading to the rate bound in Eq. (109).
  3. [Section III-A, Eqs. (13)-(18)] The admissible-power condition Tr(XX^H) <= nP is asserted at the start of Section III but never proved for the proposed encoding. For a block b not in Barrival, the transmitted signal is X_{b,j} = S^{(1)}_{b,j}(m',s) + (1-alpha_{s,1}) X^{(s,1)}_{b,j}; its squared norm contains the cross term 2(1-alpha_{s,1}) Re<S^{(1)}, X^{(s,1)}>. The DPC condition in Eq. (13) constrains only the norm of S^{(1)} - alpha_{s,1} X^{(s,1)} and does not control this cross term. A similar issue appears for URLLC blocks through Eqs. (16)-(18). Without a proof that the generated codewords satisfy the power constraint, the finite-blocklength achievability bounds and the numerical optimization over beta and alpha in Theorem 1 are not grounded.
  4. [Section III-B.1, paragraph after Eq. (13)] The paper states, 'For simplicity, we assume that at least one such a codeword exists' for the DPC encoding step. This is a non-trivial covering assumption: for every realization of the message and channel, there must exist an index s such that the precoded codeword falls in the required shell. The failure probability of this event under the random codebook construction is never bounded, and similarly for the index v in the URLLC encoding in Section III-B.2. Because the encoders in Definition 1 must be defined for every message, this assumption is part of the achievability argument and cannot be waived without quantification.
minor comments (4)
  1. [Section III-C.2, Eq. (25)] In the second term of the information density expression, the density f_{Y_{b,c}|S^{(2)}_b}(y_{b,c}|s^{(1)}_b) should condition on s^{(2)}_b, the codeword used in blocks b in Bdt, rather than on s^{(1)}_b.
  2. [Appendix C, Eq. (94) and Lemma 3, Eq. (47)] The definition of Pdet is inconsistent between the main text and the appendix: Eq. (47) uses PU,2 as defined in Eq. (32), while Eq. (94) writes (1 - P_{b-1,D})(1 - (1 - tilde{epsilon}_{U,2})^{M_U M_v}) without the division by M_U M_v inside the exponent. Since Pdet enters Ce, Ve, and Delta_e, this discrepancy must be resolved.
  3. [Abstract] The phrase 'Our numerical analysis show' should be 'Our numerical analysis shows'.
  4. [Section V] The numerical optimization procedure is described only verbally: it is not stated how the search over (alpha_u, beta_u) is performed, whether the constraints in Eqs. (49b)-(49c) are evaluated for every possible realization of Barrival or only for a stationary/averaged version, or what values are used for the auxiliary codebook sizes M_v and M_s. These details are needed to reproduce the figures.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: Theorem 1 is derived from the channel model and external finite-blocklength CLT bounds, not from a fitted parameter or a self-citation chain.

full rationale

The paper's central result, Theorem 1's rate-reliability-detection trade-off, is derived from explicit channel-law calculations and standard finite-blocklength random-coding bounds rather than from any quantity fitted to data or defined in terms of the target result. Lemma 1 computes the detection probability from the LRT and generalized chi-square distributions (Appendix A). Lemma 2 upper-bounds the URLLC error using the Berry-Esseen CLT result of MolavianJazi and Laneman [21] and the threshold bound of Polyanskiy, Poor, and Verdú [22], both external standard results. Lemma 3 uses the same external CLT machinery together with a binomial decomposition of the detected-block set; the quantity Pdet in Eq. (47) is computed from the model's detection and error probabilities, not fitted to the eMBB rate. The claimed outperformance over power-sharing and time-sharing is a numerical evaluation of the derived bound, not a re-discovery of an imposed advantage. Self-citations appear in the motivation and in the DPC construction ([15], [18]), but these are not load-bearing: the DPC encoding is defined in the paper itself and the finite-blocklength ISAC framework is only a framing reference. The most serious caveat is that Eq. (95) assumes independent, identically distributed detection events across blocks even though the model's P_{b,D} is block-dependent and serially coupled through the arrival process; that is a modeling-validity or correctness concern, not circularity, since the conclusion is not assumed as an input.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

No new physical entities are introduced; the system uses standard MIMO channels, DPC, and LRT detection. The main free parameters are the DPC/power-splitting design variables and the unspecified constants in the bounds.

free parameters (4)
  • DPC and power-splitting parameters alpha_u, alpha_s,1, alpha_s,2, beta_u, beta_s,1, beta_s,2 = not specified; optimized numerically
    These six parameters define the codebook radii and DPC interference cancellation; Theorem 1 maximizes the rate bound over them. They are design variables, not fitted to external data.
  • Positive constants K_U, B, K_e, B_tilde = unspecified
    These constants appear in the finite-blocklength error bounds (Lemmas 2-3, eqs. 33-34, 40, 48) and must take concrete values to evaluate the plotted rates; the paper only states they exist.
  • Auxiliary codebook sizes M_v, M_s = not specified
    M_v appears in the URLLC union bound and M_s enters the eMBB rate through log(M_s)/n; their values affect the bounds and are not reported.
  • Shell slack parameters zeta_s,1, zeta_s,2, zeta_u = not specified
    The DPC shell sets D(a,zeta) require positive slack parameters; values are never given, though they affect whether an index exists.
assumptions (5)
  • domain assumption MIMO memoryless Gaussian quasi-static fading channel with channel state information known at both BS and UE.
    Stated in Section II-A as the channel model for all derivations.
  • domain assumption The SR and BS can communicate over an interference-free backhaul link, and the UE is outside the sensing range.
    Stated in Section II as a system-level simplification; removes interference between sensing and communication backhaul.
  • standard math The information density of the power-shell DPC-coded scheme converges to a Gaussian distribution as stated in Lemma 4/5, citing [21, Proposition 1].
    The proof is deferred to an external Berry-Esseen CLT result; the applicability to non-i.i.d. power-shell codebooks is not verified in the paper.
  • ad hoc to paper For every message realization there exists at least one DPC index s (and v) such that the precoded codeword lies in the required shell D(...,zeta).
    Section III-B states this 'for simplicity' with no covering lemma; if false, the encoder is undefined.
  • ad hoc to paper URLLC detection events across blocks are independent and identically distributed with a common probability Pdet.
    Appendix C eq. (95) uses a binomial product Pdet^|Bdt|(1-Pdet)^{eta-|Bdt|}, which requires i.i.d. detection per block; the system model creates serial dependence via Pb-1,D.

how reviews work

0 comments
Cite this review

Pith. "Pith review of A MIMO ISAC System for Ultra-Reliable and Low-Latency Communications." pith.science (2026). https://pith.science/paper/7LRSLWST

@misc{pith2026250113025,
  author       = {Pith},
  title        = {Pith review of: A MIMO ISAC System for Ultra-Reliable and Low-Latency Communications},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/7LRSLWST}},
  note         = {Machine review of arXiv:2501.13025}
}
read the original abstract

In this paper, we propose a bi-static multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system to detect the arrival of ultra-reliable and low-latency communication (URLLC) messages and prioritize their delivery. In this system, a dual-function base station (BS) communicates with a user equipment (UE) and a sensing receiver (SR) is deployed to collect echo signals reflected from a target of interest. The BS regularly transmits messages of enhanced mobile broadband (eMBB) services to the UE. During each eMBB transmission, if the SR senses the presence of a target of interest, it immediately triggers the transmission of an additional URLLC message. To reinforce URLLC transmissions, we propose a dirty-paper coding (DPC)-based technique that mitigates the interference of both eMBB and sensing signals. For this system, we formulate the rate-reliability-detection trade-off in the finite blocklength regime by evaluating the communication rate of the eMBB transmissions, the reliability of the URLLC transmissions and the probability of the target detection. Our numerical analysis show that our proposed DPC-based ISAC scheme significantly outperforms power-sharing based ISAC and traditional time-sharing schemes. In particular, it achieves higher eMBB transmission rate while satisfying both URLLC and sensing constraints.

Figures

Figures reproduced from arXiv: 2501.13025 by the authors.

Figure 1
Figure 1. An illustration of the system model: (a) no target is [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Comparing our DPC-based scheme with power-sharing [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Blind and Topological Interference Managements for Bistatic Integrated Sensing and Communication

    cs.IT 2024-12 conditional novelty 6.0 of 10

    For bistatic ISAC with dispersed receivers and a sensor that does not know the communication messages, BIA and TIM schemes achieve (sDoF,cDoF) tradeoff points that dominate time-sharing.

  2. A Comprehensive Survey of 5G URLLC and Challenges in the 6G Era

    cs.NI 2025-08 conditional novelty 2.0 of 10

    A broad literature survey of 5G URLLC across PHY, MAC, cross-layer, ML, and security, with a 6G challenges and research directions section.

Reference graph

Works this paper leans on

22 extracted references · 21 canonical work pages · cited by 2 Pith papers

  1. [1]

    Multicarrier ISAC: Advances in waveform design, signal pro- cessing, and learning under nonidealities,

    V . Koivunen, M. F. Keskin, H. Wymeersch, M. Valkama, and N. González- Prelcic, “Multicarrier ISAC: Advances in waveform design, signal pro- cessing, and learning under nonidealities,” IEEE Signal Processing Mag- azine, vol. 41, no. 5, pp. 17–30, Sept. 2024

    work page 2024

  2. [2]

    YOLO: An efficient terahertz band integrated sensing and communications scheme with beam squint,

    H. Luo, F. Gao, H. Lin, S. Ma, and H. V . Poor, “YOLO: An efficient terahertz band integrated sensing and communications scheme with beam squint,” IEEE Transactions on Wireless Communications , vol. 23, no. 8, pp. 9389–9403, Aug. 2024

    work page 2024

  3. [3]

    Integrated sensing and communications: Toward dual- functional wireless networks for 6G and beyond,

    F. Liu et al., “Integrated sensing and communications: Toward dual- functional wireless networks for 6G and beyond,” IEEE Journal on Se- lected Areas in Communications, vol. 40, no. 6, pp. 1728–1767, June 2022

    work page 2022

  4. [4]

    Waveform shaping in integrated sensing and communications,

    H. Li, Z. Han and H. V . Poor, “Waveform shaping in integrated sensing and communications,” in Proceedings of the IEEE Military Communications Conference, Washington, DC, USA, pp. 670–671, 2024

    work page 2024

  5. [5]

    Next- generation multiple access for integrated sensing and communications,

    Y . Liu, T. Huang, F. Liu, D. Ma, W. Huangfu, and Y . C. Eldar, “Next- generation multiple access for integrated sensing and communications,” Proceedings of the IEEE , vol. 112, no. 9, pp. 1467–1496, Sept. 2024

    work page 2024

  6. [6]

    Ultra-reliable low-latency communications: Foundations, enablers, sys- tem design, and evolution towards 6G,

    N. H. Mahmood, I. Atzeni, E. A. Jorswieck, and O. L. A. López, “Ultra-reliable low-latency communications: Foundations, enablers, sys- tem design, and evolution towards 6G,” Foundations and Trends® in Communications and Information Theory , vol. 20, no. 5-6, pp. 512–747, 2023

    work page 2023

  7. [7]

    Joint processing and transmission energy optimization for ISAC in cell-free massive MIMO with URLLC,

    Z. Behdad, Ö. T. Demir, K. W. Sung, and C. Cavdar, “Joint processing and transmission energy optimization for ISAC in cell-free massive MIMO with URLLC,” arXiv:2401.10315, 2024

    arXiv 2024

  8. [8]

    URLLC-aware trajectory plan and beamforming design for NOMA-aided UA V integrated sensing, communication, and computation networks,

    P. Qin, Y . Fu, Z. Yu, J. Zhang, and X. Zhao, “URLLC-aware trajectory plan and beamforming design for NOMA-aided UA V integrated sensing, communication, and computation networks,” IEEE Transactions on Vehic- ular Technology, vol. 74, no. 1, pp. 1610–1625, Jan. 2025

    work page 2025

Show all 22 references
  1. [9]

    Joint beamforming and scheduling for integrated sensing and communication systems in URLLC: A POMDP approach,

    X. Zhao and Y . -J. Angela Zhang, “Joint beamforming and scheduling for integrated sensing and communication systems in URLLC: A POMDP approach,” IEEE Transactions on Communications , vol. 72, no. 10, pp. 6145–6161, Oct. 2024

    2024

  2. [10]

    An information-theoretic view of mixed-delay traffic in 5G and 6G,

    H. Nikbakht, M. Wigger, M. Egan, S. Shamai (Shitz), J-M. Gorce, and H. V . Poor, “An information-theoretic view of mixed-delay traffic in 5G and 6G,” Entropy, vol. 24, no. 5, article 637, 2022

    2022

  3. [11]

    Performance analysis of one-way highway vehicular networks with dynamic multiplexing of eMBB and URLLC traffics,

    X. Song and M. Yuan, “Performance analysis of one-way highway vehicular networks with dynamic multiplexing of eMBB and URLLC traffics,” IEEE Access, vol. 7, pp. 118020–118029, 2019

    2019

  4. [12]

    On the coexistence of eMBB and URLLC in multi-cell massive MIMO,

    G. Interdonato, S. Buzzi, C. D’Andrea, L. Venturino, C. D’Elia, and P. Vendittelli, “On the coexistence of eMBB and URLLC in multi-cell massive MIMO,” IEEE Open Journal of the Communications Society , vol. 4, pp. 1040–1059, 2023

    2023

  5. [13]

    Joint coding of eMBB and URLLC in vehicle-to-everything (V2X) communications,

    H. Nikbakht, E. Ruzomberka, M. Wigger, S. Shamai, and H. V . Poor, “Joint coding of eMBB and URLLC in vehicle-to-everything (V2X) communications,” in Proceedings of the IEEE Global Communications Conference, Kuala Lumpur, Malaysia, pp. 1–6, 4–8 Dec. 2023

    2023

  6. [14]

    Feedback coding of URLLC in vehicle-to-everything (V2X) communications and its secrecy analysis,

    J. Wang, G. Xie, D. Xia, and B. Dai, “Feedback coding of URLLC in vehicle-to-everything (V2X) communications and its secrecy analysis,” in Proceedings of the IEEE Wireless Communications and Networking Conference, Dubai, United Arab Emirates, pp. 01-06, 21–24 April, 2024

    2024

  7. [15]

    Dirty paper coding for con- secutive messages with heterogeneous decoding deadlines in the finite blocklength regime,

    H. Nikbakht, M. Egan, and J.-M. Gorce, “Dirty paper coding for con- secutive messages with heterogeneous decoding deadlines in the finite blocklength regime,” in Proceedings of the IEEE International Symposium on Information Theory, pp. 2100–2105, Espoo, Finland, 26 June – 01 ...

    2022

  8. [16]

    Writing on dirty paper (Corresp.),

    M. H. M. Costa, “Writing on dirty paper (Corresp.),” IEEE Transactions on Information Theory , vol. 29, no. 3, pp. 439–441, May 1983

    1983

  9. [17]

    A broadcast channel framework for joint communications and sensing-part II: Superposition coding,

    H. Li, Z. Han, and H. V . Poor, “A broadcast channel framework for joint communications and sensing-part II: Superposition coding,” in Proceed- ings of the IEEE Global Communications Conference , Kuala Lumpur, Malaysia, pp. 7381–7386, 4–8 Dec. 2023

    2023

  10. [18]

    Integrated sensing and communication in the finite blocklength regime,

    H. Nikbakht, M. Wigger, S. Shamai, and H. V . Poor, “Integrated sensing and communication in the finite blocklength regime,” in Proceedings of the IEEE International Symposium on Information Theory, pp. 2790–2795, Athens, Greece, 07–12 July, 2024

    2024

  11. [19]

    H. V . Poor, An introduction to signal detection and estimation , Springer Science & Business Media, 2013

    2013

  12. [20]

    Probability of error for optimal codes in a Gaussian channel,

    C. E. Shannon, “Probability of error for optimal codes in a Gaussian channel,” The Bell System Technical Journal, vol. 38, no. 3, pp. 611–656, 1959

    1959

  13. [21]

    A finite-blocklength perspective on Gaussian multi-access channels,

    E. MolavianJazi and J. N. Laneman, “A finite-blocklength perspective on Gaussian multi-access channels,” arXiv:1309.2343, sep. 2013

    2013 arXiv

  14. [22]

    Channel coding rate in the finite blocklength regime,

    Y . Polyanskiy, H. V . Poor and S. Verdu, “Channel coding rate in the finite blocklength regime,” IEEE Transactions on Information Theory , vol. 56, no. 5, pp. 2307–2359, May, 2010

    2010

Pith tools

Reviewed August 10, 2026 · model on record in the stance chip above.