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REVIEW 3 major objections 5 minor 38 references

Hybrid Beamforming Design for Covert mmWave MIMO with Finite-Resolution DACs

T0 review · 3 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read The paper shows that low-resolution DACs can be incorporated into covert mmWave MIMO beamforming, and that a low-complexity heuristic reaches channel mutual information as the antenna array grows.

desk verdict The warden-detection derivation is clean and the problem is new, but the AO constraint transformation drops a quantization-noise term and the VSH asymptotic proof applies to a beamformer the algorithm never simulates. read the letter →

arxiv 2411.17986 v1 pith:R75S2AOB submitted 2024-11-27 cs.IT eess.SPmath.IT

Wei Ci , Chenhao Qi , Xiaohu You This is my paper · ORCID
classification cs.ITeess.SPmath.IT MSC 94A1594A40
keywords CovertcommunicationsHybridbeamformingFinite-resolutionDACmmWaveMIMOAdditivequantizationnoiseSumrateMultiuser
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

The paper asks whether a millimeter-wave base station with cheap, low-resolution digital-to-analog converters can serve multiple users covertly while a warden tries to detect the transmission. Using the additive quantization noise model, it derives a closed-form expression for the warden's detection error probability and turns covertness into an explicit trace constraint. It then solves the resulting nonconvex beamforming problem with two schemes: an alternating optimization scheme and a much cheaper vector-space heuristic. The central theoretical result is that the heuristic's sum covert rate becomes equal to the channel mutual information as the number of antennas grows to infinity. Simulations indicate that both schemes outperform fully-digital and maximum-ratio baselines, especially when the DACs use very few bits.

What carries the argument

The load-bearing objects are the additive quantization noise model of Eqs. (2)-(3), which replaces the nonlinear DAC with a linear gain $(1-\beta)$ plus Gaussian quantization noise with covariance $\beta(1-\beta)\mathrm{diag}(F_BF_B^H)$; the SIQNR in Eq. (12) and the sum covert rate in Eq. (13); and, for the heuristic, the null-space construction of Eqs. (60)-(61), where the analog beamformer lies in the null space of Willie's channel covariance $\Omega_w$ and the digital beamformer uses block diagonalization to remove multiuser interference. These objects convert covertness into a trace constraint, the rate objective into a quadratic form, and the asymptotic argument into a statement about orthogonal mmWave channel vectors.

What would settle it

Run a Monte Carlo simulation of an actual $b$-bit uniform quantizer at Alice instead of the AQN approximation: generate Willie's observations under $H_0$ and $H_1$, apply the optimal likelihood-ratio test, and compare the empirical detection error probability $P_e$ with (11)-(25). A gap beyond the simulation margin would show that the derived covertness constraint is not the true constraint.

Watch

Extended reading notes

Core claim

On the paper's own terms, the discovery is that finite-resolution DAC quantization noise does not have to be a covertness leak that forces a rate loss; it can be engineered around in the hybrid beamformer. The quantized transmit signal is modeled as $(1-\beta)F_Bs+\eta_q$ with $\eta_q \sim \mathcal{CN}(0, \beta(1-\beta)\mathrm{diag}(F_BF_B^H))$, which lets the authors compute Willie's optimal detection error probability and replace the covertness constraint with the trace bound in (25). The AO scheme iterates between analog and digital beamformers, using fractional programming, a QCQP formulation with constant-modulus constraints, and an inner majorization-minimization method. The VSH scheme projects the analog beamformer into the null space of Willie's channel covariance and block-diagonalizes the digital beamformer; Proposition 2 proves that for $N\to\infty$ the SCR in (13) equals the mutual information in (57). In simulations the AO scheme matches the fully-digital baseline at high DAC resolution and beats it under tight covertness with 1-bit DACs, while the VSH scheme serves as a fast initialization.

Load-bearing premise

The whole design assumes the additive quantization noise model, in which a $b$-bit DAC behaves like a linear scaling plus independent Gaussian noise; if the true quantization error is correlated with the signal or non-Gaussian, the derived detection probability and the power and covertness constraints are not the true ones.

Editorial extensions

If this is right

  • With 1-bit DACs under a tight covertness requirement, hybrid beamforming can outperform a fully-digital beamformer because the analog stage reduces quantization-noise leakage toward Willie.
  • As the number of antennas grows, the VSH scheme's sum covert rate approaches the channel mutual information, so cheap hardware plus a large array does not sacrifice the asymptotic rate.
  • The VSH scheme provides an initialization for the AO scheme that converges faster and to a higher converged sum covert rate than beam-training initialization.
  • DAC resolution has an energy-efficiency optimum: increasing the number of bits beyond about five yields little sum-rate gain while power consumption keeps rising.

Reading between the lines

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

  • If the AQN model is accurate enough, the same null-space reasoning should extend to wideband mmWave systems, where frequency-dependent beams can also be placed in Willie's channel null space.
  • The asymptotic equivalence suggests that in massive arrays, covertness can come from array geometry rather than from artificial noise; a testable prediction is that the required jamming power drops to zero as $N$ grows.
  • Because the warden's optimal detector assumes Gaussian quantization noise, a stronger test is to let Willie run a data-driven detector on the true quantized waveform; under that threat model the trace constraint in (25) may need to be re-derived.
  • The power-allocation subroutine in (72)-(81) is separable from the beam directions and could be reused for other hybrid or fully-digital architectures with finite-resolution DACs.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. The paper considers covert multiuser mmWave MIMO downlink with a fully-connected hybrid beamforming architecture and finite-resolution DACs at the transmitter. Under the additive quantization noise (AQN) model, the authors derive an approximate detection error probability for a warden Willie, formulate a sum covert rate (SCR) maximization problem with power and covertness constraints, and propose two hybrid beamforming designs: an alternating optimization (AO) scheme based on fractional programming, quadratic transformation, and inner majorization-minimization, and a lower-complexity vector-space heuristic (VSH) scheme. The paper claims that, as the number of antennas grows to infinity, the SCR achieved by the VSH scheme approaches the channel mutual information, and that simulations show both proposed schemes outperform fully-digital and maximum-ratio baselines. The main theoretical results are Proposition 1 (warden KL divergence), Proposition 2 (asymptotic SCR-to-mutual-information equivalence for the VSH design), and the associated Algorithms 1-3.

Significance. If the claims are correct, the paper makes a useful contribution by introducing finite-resolution DAC hardware constraints into covert mmWave MIMO hybrid beamforming, a combination not treated in prior work. The AQN-based warden detection analysis and the AO algorithm are in line with current methodology in the field, and the VSH scheme offers a low-complexity alternative with a precise asymptotic performance target. The paper also provides reproducible simulation evidence for convergence speed, SCR, and energy efficiency. However, the central asymptotic claim and the constraint derivations contain load-bearing gaps: the power and covertness constraint matrices in the analog beamforming subproblem omit the quantization-noise covariance term, and the asymptotic proof for the VSH scheme applies to an unconstrained analog beamformer that is not the one implemented after phase projection. These issues affect the correctness of the proposed algorithms as stated and the support for the main theoretical claim.

major comments (3)
  1. [Section III-B.1, Eqs. (36)-(38)] The matrices Q1 and Q2 used in the analog beamforming subproblem omit the quantization-noise contribution. Substituting (3) into the power constraint (15) gives F_R[(1-β)^2 F_BF_B^H + β(1-β)diag(F_BF_B^H)]F_R^H ≤ P_max, and the vectorized quadratic form should therefore contain the term β(1-β)diag(F_BF_B^H)^T ⊗ I_N in Q1 and β(1-β)diag(F_BF_B^H)^T ⊗ Ω_w in Q2. Equations (37)-(38) keep only the first term, so the constraints enforced by (36b)-(36c) are weaker than those of the original problem (14). The same omission propagates into the majorization functions g1 and g2 in (42)-(43), so a solution returned by Algorithm 1 need not satisfy the true power or covertness constraints. Notably, the digital beamforming subproblem in (51), (54), and (55) does include the diag term, which indicates the omission in (37)-(38) is not an intentional modeling choice.
  2. [Section IV-A, Proposition 2 and Algorithm 3] Proposition 2 is proved for the unconstrained analog beamformer eFR = V_w^(0)[Ṽ]:,1:K in (60), which has orthonormal columns and lies in the null space of Ω_w. The VSH scheme actually simulated in Figs. 2-8 uses instead the phase-projected beamformer bFR = exp(j∠eFR) from (83), followed by rescaling of bFB in (84). No argument is supplied that phase projection preserves the null-space property Ω_w bFR = 0, the orthonormality of the columns, or the asymptotic channel-orthogonality properties used in the proof. The citation [34] removes constant-modulus constraints by doubling the number of RF chains, but N_RF is not doubled in Algorithm 3. Moreover, the power allocation optimization in (72)-(81) is derived under the assumption F_R = eFR; after (83) the effective user and warden channels change, so the optimized ζ is no longer tailored to the projected beamformer. Consequently the asymptotic "SCR approaches mutual information" claim is established only for an intermediate design that is never simulated, and the corresponding claim for the implemented VSH scheme is unsupported.
  3. [Section IV-A, Eq. (83)] The statement that bFR = exp(j∠eFR) is "the optimal solution approaching (60)" is not an asymptotic equivalence in any norm relevant to the proof. For a generic unit-norm vector v with iid entries, the normalized inner product between v and exp(j∠v) tends to approximately 0.886, not to 1, and the component of exp(j∠v) orthogonal to v has non-vanishing norm. More importantly for covertness, a vector that is exactly orthogonal to the steering vectors spanning Ω_w will, after phase projection, generally have an O(1) projection onto each such steering vector, so the left-hand side of the covertness constraint (25) is not inherited from eFR. The scaling in (84) can force feasibility, but only at the cost of a rate reduction that is not accounted for in Proposition 2. The paper should either prove the needed preservation properties for the projected beamformer, or explicitly state that Proposition 2 applies to the unconstrained design and treat the projected VSH as a heuristic supported only by simulation.
minor comments (5)
  1. [Section II-B, Eq. (11)] The sentence "Pe = 1 means that Willie always makes error detection" is inaccurate: P_FA + P_MD = 1 is equivalent to P(D1|H0) = P(D1|H1), i.e., Willie's decision is statistically independent of the true hypothesis, not that he always errs. This does not change the optimization because the same convention is used consistently, but the wording should be corrected.
  2. [Section IV-A, Eq. (68)] The last diagonal entry in the expression for Υ should read ĕ_K R_q ĕ_K^H rather than ĕ_K F_R R_q ĕ_K^H; as printed, the dimensions do not match.
  3. [Section IV-B, Eq. (73) and following] The notation ϑ ∈ R^{K×K} appears to be a typo: ϑ_k is a K-dimensional vector for each k, so the statement should be ϑ_k ∈ R^K or ϑ ∈ R^K.
  4. [Section IV-B, Eq. (76)] In the term ϑ_k^T(ζ^T(Π_k+Θ_k)ζ + σ_k^2 I_K)ϑ_k, the quantity ζ^T(Π_k+Θ_k)ζ is a scalar, so the expression is a scalar times ||ϑ_k||^2; writing the scalar denominator explicitly would improve readability and avoid apparent dimension mismatch.
  5. [Algorithm 3, steps 10-11] After the phase projection and the scaling in (84), the digital beamformer bFB no longer satisfies the zero-interference property (69) exactly, and the power allocation from (81) is computed for a different effective channel. This should be acknowledged in the text surrounding Algorithm 3.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: all derived quantities are computed from the stated AQN model and external channel statistics, and the asymptotic equivalence is proved for the constructed beamformers rather than assumed.

full rationale

The paper's central quantities—Willie's detection error probability, SIQNR, SCR, power and covertness constraints—are derived from the additive quantization noise model in Eqs. (2)–(3), which is imported from the external quantization literature [24], [25]. The beta values are external inputs, not fitted to the paper's own outputs, and no parameter in the AO or VSH schemes is calibrated to the mutual information or SCR that the paper claims to achieve. Proposition 2's asymptotic equivalence between SCR and mutual information is derived by constructing eFR and eFB from the null space of Omega_w and the user channel structure, then showing (68)-(70) under the stated asymptotic orthogonality assumptions; the conclusion is not used as an input to the construction. The only self-citation [1] covers the first two contributions (system model and AO scheme) and is not load-bearing for the VSH asymptotic claim, which is the paper's main new theoretical result. The reviewer concern that Algorithm 3 replaces the proved eFR by the phase projection bFR = exp(j angle eFR) in (83), so the simulated VSH scheme may not inherit the asymptotic guarantee, is a proof-completeness or correctness gap rather than a circularity: the paper does not assume the mutual-information equivalence to design bFR, and no fitted parameter is renamed as a prediction.

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

The central derivations rest on the AQN approximation, the worst-case Willie detection model, availability of statistical CSI, asymptotic orthogonality, and the unquantified constant-modulus projection in VSH. No free parameters are fitted and no new physical entities are introduced.

assumptions (5)
  • domain assumption Quantized DAC output follows the additive quantization noise model of Eq. (2): x_b ≈ (1-β)F_B s + η_q with η_q ~ CN(0,R_q), R_q = β(1-β)diag(F_BF_B^H).
    All derivations of SIQNR, power and covertness constraints, P_e, and the VSH proposition depend on this approximation. It is cited to [24],[25] but not validated against an actual b-bit quantizer or measurements.
  • domain assumption Willie observes T independent slots, knows h_w, F_R, F_B and R_q, uses the optimal likelihood ratio test, and Alice transmits with equal priors, so the minimum detection error probability is P_e = 1 - V(P_1^T,P_0^T).
    Section II-B and Eq. (18), following [4],[9],[19]. This is a worst-case adversary model; if Willie has less information, the resulting covertness constraint is conservative.
  • domain assumption Alice knows only statistical CSI of the Willie channel, h_w ~ CN(0,Ω_w), and the covertness constraint is averaged over h_w.
    Section II-A, Eq. (8), and Eq. (14d). This turns the unknown instantaneous warden channel into the trace constraint in Eq. (25).
  • standard math For continuously distributed AoDs, array responses are asymptotically orthogonal as N→∞, giving Pr(lim a(N,θ_i)^H a(N,θ_j)=0)=1 for distinct angles, which makes user channels and the warden channel orthogonal in the limit.
    Used in the proof of Proposition 2, Eqs. (62)-(65). The finite-N simulations rely on this orthogonality being approximately valid at N=64.
  • ad hoc to paper The constant-modulus constraint can be dropped during VSH construction and then restored by phase projection F_R=exp(j∠F_R) in Eq. (83), with any loss compensated by scaling F_B in Eq. (84).
    This is a heuristic. The phase projection does not preserve the null-space property used in Proposition 2, and no error bound is provided; feasibility is only guaranteed for the two quadratic constraints after scaling.

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Pith. "Pith review of Hybrid Beamforming Design for Covert mmWave MIMO with Finite-Resolution DACs." pith.science (2026). https://pith.science/paper/R75S2AOB

@misc{pith2026241117986,
  author       = {Pith},
  title        = {Pith review of: Hybrid Beamforming Design for Covert mmWave MIMO with Finite-Resolution DACs},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/R75S2AOB}},
  note         = {Machine review of arXiv:2411.17986}
}
read the original abstract

We investigate hybrid beamforming design for covert millimeter wave multiple-input multiple-output systems with finite-resolution digital-to-analog converters (DACs), which impose practical hardware constraints not yet considered by the existing works and have negative impact on the covertness. Based on the additive quantization noise model, we derive the detection error probability of the warden considering finite-resolution DACs. Aiming at maximizing the sum covert rate (SCR) between the transmitter and legitimate users, we design hybrid beamformers subject to power and covertness constraints. To solve this nonconvex joint optimization problem, we propose an alternating optimization (AO) scheme based on fractional programming, quadratic transformation, and inner majorization-minimization methods to iteratively optimize the analog and digital beamformers. To reduce the computational complexity of the AO scheme, we propose a vector-space based heuristic (VSH) scheme to design the hybrid beamformer. We prove that as the number of antennas grows to be infinity, the SCR in the VSH scheme can approach the channel mutual information. Simulation results show that the AO and VSH schemes outperform the existing schemes and the VSH scheme can be used to obtain an initialization for the AO scheme to speed up its convergence.

Figures

Figures reproduced from arXiv: 2411.17986 by the authors.

Figure 1
Figure 1. Illustration of the system model. based on the AO scheme. The VSH scheme is proposed for hybrid beamforming design in Section IV. Simulation results are presented in Section V. Finally, this paper is concluded in Section VI. The notations are defined as follows. Symbols for vectors (lower case) and matrices (upper case) are in boldface. (·) ∗ , (·) T and (·) H denote the conjugate, transpose and conjugate transpose,… view at source ↗
Figure 2
Figure 2. Comparison of the SCR for different methods with varying iterations. [PITH_FULL_IMAGE:figures/full_fig_p010_2.png] view at source ↗
Figure 3
Figure 3. Comparison of the SCR for different methods with varying detection [PITH_FULL_IMAGE:figures/full_fig_p010_3.png] view at source ↗
Figures from the paper (3 more)
Figure 5
Figure 5. Figure 5: Comparison of the SCR for different methods with varying transmit [PITH_FULL_IMAGE:figures/full_fig_p011_5.png]
Figure 6
Figure 6. Figure 6: Comparison of the SCR for different methods with varying numbers [PITH_FULL_IMAGE:figures/full_fig_p011_6.png]
Figure 7
Figure 7. Figure 7: Comparison of the SCR for different methods with varying numbers [PITH_FULL_IMAGE:figures/full_fig_p012_7.png]

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Works this paper leans on

38 extracted references · 32 canonical work pages

  1. [34]

    Hybrid beamforming for multi-user massive MIMO systems,

    X. Wu, D. Liu, and F. Yin, “Hybrid beamforming for multi-user massive MIMO systems,” IEEE Trans. Commun., vol. 66, no. 9, pp. 3879–3891, Sep. 2018

    work page 2018

  2. [1]

    Finite-resolution DACs based hybrid beamforming design for covert communications,

    W. Ci and C. Qi, “Finite-resolution DACs based hybrid beamforming design for covert communications,” inProc. 2024 lEEE Global Commu- nications Conference (GLOBECOM) , Cape Town, South Africa, Dec. 2024, pp. 1–6

    work page 2024

  3. [2]

    Joint deep reinforcement learning and unfolding: Beam selection and precoding for mmWave multiuser MIMO with lens arrays,

    Q. Hu, Y . Liu, Y . Cai, G. Yu, and Z. Ding, “Joint deep reinforcement learning and unfolding: Beam selection and precoding for mmWave multiuser MIMO with lens arrays,” IEEE J. Sel. Areas Commun. , vol. 39, no. 8, pp. 2289–2304, Aug. 2021

    work page 2021

  4. [3]

    Hierarchical codebook- based multiuser beam training for millimeter wave massive MIMO,

    C. Qi, K. Chen, O. A. Dobre, and G. Y . Li, “Hierarchical codebook- based multiuser beam training for millimeter wave massive MIMO,” IEEE Trans. Wireless Commun. , vol. 19, no. 12, pp. 8142–8152, Dec. 2020

    work page 2020

  5. [4]

    Limits of reliable commu- nication with low probability of detection on AWGN channels,

    B. A. Bash, D. Goeckel, and D. Towsley, “Limits of reliable commu- nication with low probability of detection on AWGN channels,” IEEE J. Sel. Areas Commun. , vol. 31, no. 9, pp. 1921–1930, Sep. 2013

    1921

  6. [5]

    Covert communication over noisy channels: A resolvabil- ity perspective,

    M. R. Bloch, “Covert communication over noisy channels: A resolvabil- ity perspective,” IEEE Trans. Inf. Theory, vol. 62, no. 5, pp. 2334–2354, May 2016

    2016

  7. [6]

    Embedding covert informa- tion in broadcast communications,

    K. S. Kumar Arumugam and M. R. Bloch, “Embedding covert informa- tion in broadcast communications,” IEEE Trans. Inf. F orensics Security, vol. 14, no. 10, pp. 2787–2801, Oct. 2019

    work page 2019

  8. [7]

    Covert communication over a K-user multiple-access channel,

    K. S. K. Arumugam and M. R. Bloch, “Covert communication over a K-user multiple-access channel,” IEEE Trans. Inf. Theory , vol. 65, no. 11, pp. 7020–7044, Nov. 2019

    work page 2019

Show all 38 references
  1. [8]

    Covert communica- tions when the warden does not know the background noise power,

    D. Goeckel, B. Bash, S. Guha, and D. Towsley, “Covert communica- tions when the warden does not know the background noise power,” IEEE Commun. Lett. , vol. 20, no. 2, pp. 236–239, Feb. 2016

    2016

  2. [9]

    Covert communication in fading channels under channel uncertainty,

    K. Shahzad, X. Zhou, and S. Yan, “Covert communication in fading channels under channel uncertainty,” in Proc. IEEE 85th V eh. Technol. Conf. (VTC Spring) , Sydney, NSW, Australia, June 2017, pp. 1–5

    2017

  3. [10]

    Covert communication in the presence of an uninformed jammer,

    T. V . Sobers, B. A. Bash, S. Guha, D. Towsley, and D. Goeckel, “Covert communication in the presence of an uninformed jammer,” IEEE Trans. Wireless Commun., vol. 16, no. 9, pp. 6193–6206, Sep. 2017

    2017

  4. [11]

    Achieving covert wireless communications using a full-duplex receiver,

    K. Shahzad, X. Zhou, S. Yan, J. Hu, F. Shu, and J. Li, “Achieving covert wireless communications using a full-duplex receiver,” IEEE Trans. Wireless Commun. , vol. 17, no. 12, pp. 8517–8530, Dec. 2018

    2018

  5. [12]

    Wireless covert communications aided by distributed cooperative jamming over slow fading channels,

    T.-X. Zheng, Z. Yang, C. Wang, Z. Li, J. Yuan, and X. Guan, “Wireless covert communications aided by distributed cooperative jamming over slow fading channels,” IEEE Trans. Wireless Commun., vol. 20, no. 11, pp. 7026–7039, Nov. 2021

    2021

  6. [13]

    Robust beamforming design for covert communications,

    S. Ma et al., “Robust beamforming design for covert communications,” IEEE Trans. Inf. F orensics Security , vol. 16, pp. 3026–3038, 2021

    2021

  7. [14]

    Covert millimeter-wave communica- tion: Design strategies and performance analysis,

    M. V . Jamali and H. Mahdavifar, “Covert millimeter-wave communica- tion: Design strategies and performance analysis,” IEEE Trans. Wireless Commun., vol. 21, no. 6, pp. 3691–3704, June 2022

    2022

  8. [15]

    Joint beam training and data transmission design for covert millimeter-wave communication,

    J. Zhang et al. , “Joint beam training and data transmission design for covert millimeter-wave communication,” IEEE Trans. Inf. F orensics Security, vol. 16, pp. 2232–2245, 2021

    2021

  9. [16]

    Covert millimeter wave communications based on beam sweeping,

    Z. Xing, C. Qi, Y . Cheng, Y . Wu, D. Lv, and P. Li, “Covert millimeter wave communications based on beam sweeping,” IEEE Commun. Lett. , vol. 27, no. 5, pp. 1287–1291, Mar. 2023

    2023

  10. [17]

    Secure hybrid A/D beamforming for hardware-efficient large-scale multiple- antenna SWIPT systems,

    Y . Cai, F. Cui, Q. Shi, Y . Wu, B. Champagne, and L. Hanzo, “Secure hybrid A/D beamforming for hardware-efficient large-scale multiple- antenna SWIPT systems,” IEEE Trans. Commun. , vol. 68, no. 10, pp. 6141–6156, Oct. 2020

    2020

  11. [18]

    Two-step codeword design for millimeter wave massive MIMO systems with quantized phase shifters,

    K. Chen, C. Qi, and G. Y . Li, “Two-step codeword design for millimeter wave massive MIMO systems with quantized phase shifters,” IEEE Trans. Signal Process. , vol. 68, pp. 170–180, Dec. 2020

    2020

  12. [19]

    Covert rate optimization of millimeter wave full-duplex communications,

    C. Wang, Z. Li, and D. W. K. Ng, “Covert rate optimization of millimeter wave full-duplex communications,” IEEE Trans. Wireless Commun., vol. 21, no. 5, pp. 2844–2861, May 2022

    2022

  13. [20]

    Low power analog-to-digital conversion in millimeter wave systems: Impact of resolution and bandwidth on performance,

    O. Orhan, E. Erkip, and S. Rangan, “Low power analog-to-digital conversion in millimeter wave systems: Impact of resolution and bandwidth on performance,” in Proc. Inf. Theory Appl. Workshop (ITA), San Diego, CA, USA, Feb. 2015, pp. 191–198

    2015

  14. [21]

    Millimeter wave receiver efficiency: A comprehensive comparison of beamforming schemes with low resolution ADCs,

    W. B. Abbas, F. Gomez-Cuba, and M. Zorzi, “Millimeter wave receiver efficiency: A comprehensive comparison of beamforming schemes with low resolution ADCs,” IEEE Trans. Wireless Commun., vol. 16, no. 12, pp. 8131–8146, Dec. 2017

    2017

  15. [22]

    Secure hybrid digital and analog precoder for mmWave systems with low-resolution DACs and finite-quantized phase shifters,

    L. Xu et al. , “Secure hybrid digital and analog precoder for mmWave systems with low-resolution DACs and finite-quantized phase shifters,” IEEE Access , vol. 7, pp. 109 763–109 775, 2019

    2019

  16. [23]

    Secure hybrid analog and digital beamforming for mmWave XR communications with mixed-DAC,

    D. Wu et al. , “Secure hybrid analog and digital beamforming for mmWave XR communications with mixed-DAC,” IEEE J. Sel. Topics Signal Process., vol. 17, no. 5, pp. 995–1006, Sep. 2023

    2023

  17. [24]

    Achievable rate and energy efficiency of hybrid and digital beamforming receivers with low resolution ADC,

    K. Roth and J. A. Nossek, “Achievable rate and energy efficiency of hybrid and digital beamforming receivers with low resolution ADC,” IEEE J. Sel. Areas Commun. , vol. 35, no. 9, pp. 2056–2068, Sep. 2017

    2017

  18. [25]

    Robust predictive quantization: Analysis and design via convex optimization,

    A. K. Fletcher, S. Rangan, V . K. Goyal, and K. Ramchandran, “Robust predictive quantization: Analysis and design via convex optimization,” IEEE J. Sel. Topics Signal Process. , vol. 1, no. 4, pp. 618–632, Dec. 2007

    2007

  19. [26]

    Robust beamforming design for integrated sensing and covert communication systems,

    X. Zhao, W. Deng, M. Li, and M.-J. Zhao, “Robust beamforming design for integrated sensing and covert communication systems,” IEEE Wireless Commun. Lett., early access , pp. 1–5, 2024

    2024

  20. [27]

    T. M. Cover and J. A. Thomas, Elements of Information Theory , 2nd ed. Hoboken, NJ, USA: Wiley, 2002

    2002

  21. [28]

    Covert commu- nications with randomly distributed wardens in the finite blocklength regime,

    R. Ma, W. Yang, L. Tao, X. Lu, Z. Xiang, and J. Liu, “Covert commu- nications with randomly distributed wardens in the finite blocklength regime,” IEEE Trans. V eh. Technol., vol. 71, no. 1, pp. 533–544, Jan. 2022

    2022

  22. [29]

    Fractional programming for communication systems—Part II: Uplink scheduling via matching,

    K. Shen and W. Yu, “Fractional programming for communication systems—Part II: Uplink scheduling via matching,” IEEE Trans. Signal Process., vol. 66, no. 10, pp. 2631–2644, May 2018

    2018

  23. [30]

    Hybrid precoding for mixture use of phase shifters and switches in mmWave massive MIMO,

    C. Qi, Q. Liu, X. Yu, and G. Y . Li, “Hybrid precoding for mixture use of phase shifters and switches in mmWave massive MIMO,” IEEE Trans. Commun., vol. 70, no. 6, pp. 4121–4133, June 2022

    2022

  24. [31]

    QCQP with extra constant modulus constraints: Theory and application to SINR constrained mmWave hybrid beam- forming,

    X. He and J. Wang, “QCQP with extra constant modulus constraints: Theory and application to SINR constrained mmWave hybrid beam- forming,” IEEE Trans. Signal Process. , vol. 70, pp. 5237–5250, 2022

    2022

  25. [32]

    Joint pilot optimization, target detection and channel estimation for integrated sensing and communication systems,

    Z. Huang, K. Wang, A. Liu, Y . Cai, R. Du, and T. X. Han, “Joint pilot optimization, target detection and channel estimation for integrated sensing and communication systems,” IEEE Trans. Wireless Commun. , vol. 21, no. 12, pp. 10 351–10 365, Dec. 2022

    2022

  26. [33]

    Strategies in covert commu- nication with imperfect channel state information,

    X. Peng, J. Wang, S. Xiao, and W. Tang, “Strategies in covert commu- nication with imperfect channel state information,” in Proc. 2021 IEEE Global Commun. Conf. (GLOBECOM) , Madrid, Spain, Dec. 2021, pp. 1–6

    2021

  27. [35]

    Beam training and track- ing for extremely large-scale MIMO communications,

    K. Chen, C. Qi, C.-X. Wang, and G. Y . Li, “Beam training and track- ing for extremely large-scale MIMO communications,” IEEE Trans. Wireless Commun., vol. 23, no. 5, pp. 5048–5062, May 2024

    2024

  28. [36]

    Covert threat region analysis of 3-D location-based beamforming in Rician channel,

    Y . Lin, L. Jin, K. Huang, Z. Zhong, and Q. Han, “Covert threat region analysis of 3-D location-based beamforming in Rician channel,” IEEE Wireless Commun. Lett. , vol. 11, no. 6, pp. 1253–1257, June 2022

    2022

  29. [37]

    Achieving covert wireless communication with a multi-antenna relay,

    L. Lv, Z. Li, H. Ding, N. Al-Dhahir, and J. Chen, “Achieving covert wireless communication with a multi-antenna relay,” IEEE Trans. Inf. F orensics Security, vol. 17, pp. 760–773, 2022

    2022

  30. [38]

    Hybrid archi- tectures with few-bit ADC receivers: Achievable rates and energy-rate tradeoffs,

    J. Mo, A. Alkhateeb, S. Abu-Surra, and R. W. Heath, “Hybrid archi- tectures with few-bit ADC receivers: Achievable rates and energy-rate tradeoffs,” IEEE Trans. Wireless Commun. , vol. 16, no. 4, pp. 2274– 2287, Apr. 2017

    2017

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.