In this paper, we firstly derive two approximations of the achievable uplink rate with the perfect/imperfect channel state information (CSI) in cell-free massive multi-input multi-output (MIMO) systems, and all these approximations are not only in the simple, but also converge into the classical bounds achieved in conventional massive MIMO systems where the base-station (BS) antennas are co-located. It is worth noting that the obtained two approximations with perfect CSI could be regarded as the special cases of the obtained two approximations with imperfect CSI when the pilot sequence power becomes infinite, respectively. Moreover, the theory analysis shows that all obtained approximations with perfect/imperfect CSI have an asymptotic lower bound α2log2L thanks to the extra distance diversity offered by massively distributed antennas, where L is the number of BS antennas and the path-loss factor α>2, except for the free space environment. Obviously, these results indicate that the cell-free massive MIMO system has huge potential of spectral efficiency than the conventional massive MIMO system with the asymptotically tight bound log2L.

To achieve high resolution, orthogonal frequency division multiplex (OFDM) radars deploy two-dimensional multiple signal classification (2D-MUSIC) in the joint range-velocity estimator. However, it is obvious that both of the signal reconstruction and 2D smoothing affect the noise statistical distribution and virtual array aperture in the joint range-velocity estimator with 2D-MUSIC. Therefore, the conventional accuracy analysis methods for the MUSIC are no longer suitable. In this paper, we propose an estimation accuracy analysis for the joint range-velocity estimator with 2D-MUSIC. Firstly, we present that the noise statistical distribution of the signals being reconstructed and 2D smoothed has a 2-fold Hankel structure. Then, the closed-forms of the range and velocity estimation accuracies are derived, respectively, which both show that the estimation accuracies highly depend on the 2D smoothing and could be improved by properly choosing the 2D smoothing window. Further, we formulate the smoothing optimization and propose the quasi-optimal size of the 2D smoothing window. Finally, both theoretical analyses and simulations validate that the proposed smoothing optimization could significantly improve the estimation accuracies with a lower computational burden than the conventional smoothing.

In this paper, the feasibility of a new downlink transmission mode in massive multi-input multi-output (MIMO) systems is investigated with two types of users, i.e., the users with only statistical channel state information (CSI) and the users with imperfect instantaneous CSI. The problem of downlink precoding design with mixed utilization of statistical and imperfect instantaneous CSI is addressed. We first theoretically analyze the impact of the mutual interference between the two types of users on their achievable rate. Then, considering the mutual interference suppression, we propose an extended zero-forcing (eZF) and an extended maximum ratio transmission (eMRT) precoding methods to minimize the total transmit power of base station and to maximize the received signal power of users, respectively. Thanks to the exploitation of statistical CSI, pilot-based channel estimation is avoided enabling more active users, higher system sum rate and shorter transmission delay. Finally, simulations are performed to validate the accuracy of the theoretical analysis and the advantages of the proposed precoding methods.

The sharing waveform-based integrated radar and communication (IRC) has great potential to apply in Internet-of-Things (IoT) devices due to its equipment miniaturizing and high efficiency of spectrum and energy, etc. However, the sharing waveform scheme demands a tradeoff between radar and communication performances. In this article, we focus on the design of multiple phase-shift keying (MPSK)-based linear frequency modulation (LFM) sharing waveform by exploring the tradeoff among energy leakage, peak-to-side lobe ratio (PSLR), and symbol rate. First, we derive the energy leakage and PSLR with respect to the symbol rate. Next, a novel LFM-MPSK waveform design is carried out by formulating a communication frame-based optimization, where the symbol rate is maximized with the constraints of the energy leakage and PSLR. Then, a branch-and-reduce algorithm is proposed to solve the optimization. Compared with the conventional one, the proposed LFM-MPSK waveform has a higher symbol rate with the same energy leakage and PSLR. Besides, the proposed waveform design alleviates the difficulty of the tradeoff among the energy leakage, PSLR, and symbol rate due to more Pareto solutions. Finally, all the analytical results are validated by simulations.

Metamaterial-based absorbers have been extensively investigated in the terahertz (THz) range with ever increasing performances. In this paper, we propose an all-dielectric THz absorber based on doped silicon. The unit cell consists of a silicon cross resonator with an internal cross-shaped air cavity. Numerical results suggest that the proposed absorber can operate from THz to far-infrared regimes, having an average power absorption of ∼95% between 0.6 and 10 THz. Experimental results using THz time-domain spectroscopy show a good agreement with simulations. The underlying mechanisms for broadband absorption are attributed to the combined effects of multiple cavities modes formed by silicon resonators and bulk absorption in the doped silicon substrate, as confirmed by simulated field patterns and calculated diffraction efficiency. This ultra-wideband absorption is polarization insensitive and can operate across a wide range of the incident angle. The proposed absorber can be readily integrated into silicon-based photonic platforms and used for sensing, imaging, energy harvesting and wireless communications applications in the THz/IR range.

Hybrid analog/digital precoding is a promising technology to cut down hardware cost in massive multi-input multi-output systems at millimeter wave frequencies. In this letter, we propose a joint beam selection scheme for analog domain precoding under discrete lens array. By considering channel correlation among users, the proposed scheme is able to avoid inter-user interference and maximize system sum rate. Moreover, a bio-inspired ant colony optimization-based algorithm is proposed to obtain a near-optimal solution with dramatically reduced computational complexity. Finally, simulations show the advantages of the proposed scheme in improving system sum rate.