In this paper, we consider robust transmit strategies, against the imperfectness of the channel state information at the transmitter (CSIT), for multi-input multi-output (MIMO) communication systems. ...Following a worst-case deterministic model, the actual channel is assumed to be inside an ellipsoid centered at a nominal channel. The objective is to maximize the worst-case received signal-to-noise ratio (SNR), or to minimize the worst-case Chernoff bound of the error probability, thus leading to a maximin problem. Moreover, we also consider the QoS problem, as a complement of the maximin design, which minimizes the transmit power consumption and meanwhile keeps the received SNR above a given threshold for any channel realization in the ellipsoid. It is shown that, for a general class of power constraints, both the maximin and QoS problems can be equivalently transformed into convex problems, or even further into semidefinite programs (SDPs), thus efficiently solvable by the numerical methods. The most interesting result is that the optimal transmit directions, i.e., the eigenvectors of the transmit covariance, are just the right singular vectors of the nominal channel under some mild conditions. This result leads to a channel-diagonalizing structure, as in the cases of perfect CSIT and statistical CSIT with mean or covariance feedback, and reduces the complicated matrix-valued problem to a scalar power allocation problem. Then we provide the closed-form solution to the resulting power allocation problem.
Taking full advantage of both heterogeneous networks and cloud access radio access networks, heterogeneous cloud radio access networks (H-CRANs) are presented to enhance both spectral and energy ...efficiencies, where remote radio heads (RRHs) are mainly used to provide high data rates for users with high quality of service (QoS) requirements, whereas the high-power node (HPN) is deployed to guarantee seamless coverage and serve users with low-QoS requirements. To mitigate the intertier interference and improve energy efficiency (EE) performances in H-CRANs, characterizing user association with RRH/HPN is considered in this paper, and the traditional soft fractional frequency reuse (S-FFR) is enhanced. Based on the RRH/HPN association constraint and the enhanced S-FFR, an energy-efficient optimization problem with the resource assignment and power allocation for the orthogonal-frequency-division-multiple-access-based H-CRANs is formulated as a nonconvex objective function. To deal with the nonconvexity, an equivalent convex feasibility problem is reformulated, and closed-form expressions for the energy-efficient resource allocation solution to jointly allocate the resource block and transmit power are derived by the Lagrange dual decomposition method. Simulation results confirm that the H-CRAN architecture and the corresponding resource allocation solution can enhance the EE significantly.
In millimeter-wave (mmWave) systems, antenna architecture limitations make it difficult to apply conventional fully digital precoding techniques but call for low-cost analog radio frequency (RF) and ...digital baseband hybrid precoding methods. This paper investigates joint RF-baseband hybrid precoding for the downlink of multiuser multiantenna mmWave systems with a limited number of RF chains. Two performance measures, maximizing the spectral efficiency and the energy efficiency of the system, are considered. We propose a codebook-based RF precoding design and obtain the channel state information via a beam sweep procedure. Via the codebook-based design, the original system is transformed into a virtual multiuser downlink system with the RF chain constraint. Consequently, we are able to simplify the complicated hybrid precoding optimization problems to joint codeword selection and precoder design (JWSPD) problems. Then, we propose efficient methods to address the JWSPD problems and jointly optimize the RF and baseband precoders under the two performance measures. Finally, extensive numerical results are provided to validate the effectiveness of the proposed hybrid precoders.
Non-orthogonal multiple access (NOMA) enables power-domain multiplexing via successive interference cancellation (SIC) and has been viewed as a promising technology for 5G communication. The full ...benefit of NOMA depends on resource allocation, including power allocation and channel assignment, for all users, which, however, leads to mixed integer programs. In the literature, the optimal power allocation has only been found in some special cases, while the joint optimization of power allocation and channel assignment generally requires exhaustive search. In this paper, we investigate resource allocation in downlink NOMA systems. As the main contribution, we analytically characterize the optimal power allocation with given channel assignment over multiple channels under different performance criteria. Specifically, we consider the maximin fairness, weighted sum rate maximization, sum rate maximization with quality of service (QoS) constraints, and energy efficiency maximization with weights or QoS constraints in NOMA systems. We also take explicitly into account the order constraints on the powers of the users on each channel, which are often ignored in the existing works, and show that they have a significant impact on SIC in NOMA systems. Then, we provide the optimal power allocation for the considered criteria in closed or semi-closed form. We also propose a low-complexity efficient method to jointly optimize channel assignment and power allocation in NOMA systems by incorporating the matching algorithm with the optimal power allocation. Simulation results show that the joint resource optimization using our optimal power allocation yields better performance than the existing schemes.
Low earth orbit (LEO) satellite communications are expected to be incorporated in future wireless networks, in particular 5G and beyond networks, to provide global wireless access with enhanced data ...rates. Massive multiple-input multiple-output (MIMO) techniques, though widely used in terrestrial communication systems, have not been applied to LEO satellite communication systems. In this paper, we propose a massive MIMO transmission scheme with full frequency reuse (FFR) for LEO satellite communication systems and exploit statistical channel state information (sCSI) to address the difficulty of obtaining instantaneous CSI (iCSI) at the transmitter. We first establish the massive MIMO channel model for LEO satellite communications and simplify the transmission designs via performing Doppler and delay compensations at user terminals (UTs). Then, we develop the low-complexity sCSI based downlink (DL) precoder and uplink (UL) receiver in closed-form, aiming to maximize the average signal-to-leakage-plus-noise ratio (ASLNR) and the average signal-to-interference-plus-noise ratio (ASINR), respectively. It is shown that the DL ASLNRs and UL ASINRs of all UTs reach their upper bounds under some channel condition. Motivated by this, we propose a space angle based user grouping (SAUG) algorithm to schedule the served UTs into different groups, where each group of UTs use the same time and frequency resource. The proposed algorithm is asymptotically optimal in the sense that the lower and upper bounds of the achievable rate coincide when the number of satellite antennas or UT groups is sufficiently large. Numerical results demonstrate that the proposed massive MIMO transmission scheme with FFR significantly enhances the data rate of LEO satellite communication systems. Notably, the proposed sCSI based precoder and receiver achieve the similar performance with the iCSI based ones that are often infeasible in practice.
Objective: The key principle of motor imagery (MI) decoding for electroencephalogram (EEG)-based Brain-Computer Interface (BCI) is to extract task-discriminative features from spectral, spatial, and ...temporal domains jointly and efficiently, whereas limited, noisy, and non-stationary EEG samples challenge the advanced design of decoding algorithms. Methods: Inspired by the concept of cross-frequency coupling and its correlation with different behavioral tasks, this paper proposes a lightweight Interactive Frequency Convolutional Neural Network (IFNet) to explore cross-frequency interactions for enhancing representation of MI characteristics. IFNet first extracts spectro-spatial features in low and high-frequency bands, respectively. Then the interplay between the two bands is learned using an element-wise addition operation followed by temporal average pooling. Combined with repeated trial augmentation as a regularizer, IFNet yields spectro-spatio-temporally robust features for the final MI classification. We conduct extensive experiments on two benchmark datasets: the BCI competition IV 2a (BCIC-IV-2a) dataset and the OpenBMI dataset. Results: Compared with state-of-the-art MI decoding algorithms, IFNet achieves significantly superior classification performance on both datasets while improving the winner's result in BCIC-IV-2a by 11%. Moreover, by conducting sensitivity analysis on decision windows, we show IFNet attains the best trade-off between decoding speed and accuracy. Detailed analysis and visualization verify IFNet can capture the coupling across frequency bands along with the known MI signatures. Conclusion: We demonstrate the effectiveness and superiority of the proposed IFNet for MI decoding. Significance: This study suggests IFNet holds promise for rapid response and accurate control in MI-BCI applications.
Owing to abundant spectrum resources, millimeter wave (mmwave) communication promises to provide Gbps data rates, which, however, may be restricted by large path-loss. Thus, antenna arrays are ...commonly used along with beam alignment (BA) as an important step to achieve the array gain. Efficient BA relies on the beam training codebook design. In this paper, we propose a new hierarchical codebook to achieve uniform BA performance with low overhead. To better elaborate on the design principle, a single-path channel model is considered first to frame the proposal. The codebook design is formulated as an optimization problem, where the ripple in the main/side lobes is constrained such that each training beam is close to the ideal one with a flat magnitude response and a narrow transition band. Then, we propose an efficient algorithm to find such a beam training codebook. Furthermore, we derive closed-form expressions of the BA misalignment probability or error rate of the proposed beam training codebook. Our results reveal that using the proposed codebook, the error rate of tree-search-based BA exponentially decreases with the SNR for a given channel, and linearly decreases in the log-log coordinate axis for a fading channel. We further propose a power allocation scheme used in different training stages to further improve the BA performance. Finally, the proposed framework is extended to the more complex case of multi-path channels. Numerical results confirm the effectiveness of the proposed training codebook and power allocation scheme as well as the accuracy of the performance analysis.
High dielectric loss materials have an important application in electromagnetic (EM) absorption fields. In this paper, the ternary nanocomposites: 1T/2H-MoS2/Mo2S3 with heterogeneous interfaces are ...synthesized by hydrothermal method. XRD, XPS, FTIR, SEM, and TEM measurements are applied to study the structure, morphology, and composition. The frequency spectra of complex permittivity (εr-f) are measured in 2–18 GHz by vector network analyzer. The results show that the nanocomposites have higher dielectric loss angle tangents than the reported 2H-MoS2 absorbers. Based on the εr-f spectra, the reflection loss-frequency curves (RL−f) are simulated at given thicknesses. An effective absorption bandwidth of 5.2 GHz (12.8–18 GHz) and a RL peak of −29.49 dB are achieved in a thin thickness of 1.62 mm, which are comparable to the reported 2H-MoS2 absorbers with complex composition, showing that the 1T/2H-MoS2/Mo2S3 nanocomposites have great application potential as an EM wave absorber in the Ku band.
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•1T/2H-MoS2/Mo2S3 rich in 1T phase is synthesized.•Dielectric properties in 2–18 GHz are studied.•Large dielectric loss tangent is obtained due to the 1T-MoS2.•The maximum EAB is 5.2 GHz and the RLmin is −29.49 dB in 1.62 mm.
CRISPR-Cas12a is a promising genome editing system for targeting AT-rich genomic regions. Comprehensive genome engineering requires simultaneous targeting of multiple genes at defined locations. ...Here, to expand the targeting scope of Cas12a, we screen nine Cas12a orthologs that have not been demonstrated in plants, and identify six, ErCas12a, Lb5Cas12a, BsCas12a, Mb2Cas12a, TsCas12a and MbCas12a, that possess high editing activity in rice. Among them, Mb2Cas12a stands out with high editing efficiency and tolerance to low temperature. An engineered Mb2Cas12a-RVRR variant enables editing with more relaxed PAM requirements in rice, yielding two times higher genome coverage than the wild type SpCas9. To enable large-scale genome engineering, we compare 12 multiplexed Cas12a systems and identify a potent system that exhibits nearly 100% biallelic editing efficiency with the ability to target as many as 16 sites in rice. This is the highest level of multiplex edits in plants to date using Cas12a. Two compact single transcript unit CRISPR-Cas12a interference systems are also developed for multi-gene repression in rice and Arabidopsis. This study greatly expands the targeting scope of Cas12a for crop genome engineering.
Non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) have been recognized as promising technologies for the beyond fifth generation networks to achieve significant capacity ...improvement and delay reduction. In this paper, the technologies of hybrid NOMA and MEC are integrated. In the hybrid NOMA MEC system, multiple users are classified into different groups and each group is allocated a dedicated time slot. In each group, a user first offloads its task by sharing a time slot with another user, and then solely offloads during a time interval. To reduce the delay and save the energy consumption, we consider jointly optimizing the power and time allocation in each group as well as the user grouping. As the main contribution, the optimal power and time allocation is characterized in closed form. In addition, by incorporating the matching algorithm with the optimal power and time allocation, we propose a low complexity method to efficiently optimize user grouping. Simulation results demonstrate that the proposed resource allocation method in the hybrid NOMA MEC systems not only yields better performance than the conventional OMA scheme but also achieves quite close performance as global optimal solution.
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