This paper presents an ultra-fine frequency offset synthesis (UFFOS) technique that achieves sub-parts-perbillion (sub-ppb, $\lt10^{-9}$) frequency resolution in FieldProgrammable Gate Array (FPGA)-based clock generation. To overcome the inherent limitation of conventional FPGA clocking techniques (e.g., PLLs/DLLs), where minimum frequency adjustments are restricted to the order of 1% ($10^{-3}$), UFFOS employs a novel architecture of cascaded phase interpolators (PIs) synchronized to a high-stability reference clock. This technique enables programmable sub-ppb frequency offsets through precise phase accumulation control. Implemented on an AMD Xilinx Virtex Ultrascale+ FPGA platform, UFFOS demonstrates frequency offsets ranging from $\mathbf{0. 9 ~ p p b}$ to 3.35 parts-per-million ($\mathbf{p p m}, \mathbf{1 0}^{\boldsymbol{-} \mathbf{6}}$). A comprehensive jitter decomposition analysis characterizes the synthesized clock’s time-domain performance. Furthermore, we propose a digital heterodyne frequency offset measurement (DHFOM) method capable of verifying sub-ppb-level frequency offsets with quantization errors on the order of parts-per-quadrillion (ppq, $10^{-15}$). Experimental validation confirms UFFOS as a robust solution for sub-ppb frequency offset generation, enabling applications demanding extreme frequency precision, including coherent optical communications, atomic clock synchronization, quantum computing control systems, distributed sensor networks, and next-generation softwaredefined radio architectures.

In modern high-speed communications systems, jitter tolerance testing becomes increasingly critical as signal rates continue to rise, playing a vital role in ensuring reliable data transmission and optimal system performance. As a core component of jitter tolerance testing, jitter injection must meet stringent precision and flexibility demands. This paper introduces a novel jitter injection module that integrates a programmable SiGe delay line (PDL) with an FPGA-based arbitrary signal generator, enabling flexible generation of diverse jitter profiles. The proposed solution enables cost-effective generation of Gaussian-distributed random jitter (RJ), sinusoidal/periodic jitter, and deterministic jitter (DJ) in unlimited combinations. Experimental results demonstrate injection of both periodic and random jitter components onto 28 GHz clock signals, with the module achieving ±7.4 femtosecond (fs) accuracy for random jitter and high flexibility in generating arbitrary profiles (e.g., sinusoidal jitter).

This paper presents an experimental comparison of multiplexing techniques for generating high-speed Non-Return-to-Zero (NRZ) test signals ranging from 28 to 64 Gbps using field-programmable gate arrays (FPGAs) and advanced SiGe components. Traditional high-speed signal synthesis methods, such as exclusive-OR (XOR) gates and multiplexers (MUXs), are evaluated for their performance in overcoming signal integrity challenges like jitter, edge-rate, and data-eye degradation. The study demonstrates that re-clocking input signals with high-speed flip-flops prior to XOR-based frequency doubling significantly reduces jitter, while DDR re-clocked 2:1 and 4:1 MUXs leverage dual-edge clocking to achieve higher data rates. Experimental results show that these techniques enhance signal quality, with metrics including total jitter (TJ) reduced to 7.88 ps and eye opening expanded to 77.84% at 28.125 Gbps. At 56.25 Gbps, the XOR gate alone yields a nearly closed eye opening of 1.39%, the combination of flip-flop and XOR gate improves it to 48.19%. The 2:1 MUX achieves the widest eye opening (53.31%). By exploiting the maximum operating rate of the 4:1 MUX, a 64 Gbps signal is achieved. This work highlights cost-effective, FPGA-based solutions for high-speed testing, addressing the critical need for affordable, scalable automated test equipment (ATE) required for next-generation integrated circuit validation.

Network slicing emerges as a promising solution for accommodating diverse services with varying quality of service (QoS) requirements. This paper delves into the problem of achieving energy-efficient network slicing in heterogeneous wireless networks. We first introduce a novel performance metric to evaluate the energy efficiency of slice. In order to reduce energy consumption and enhance energy efficiency, an adaptive slice switching mechanism is proposed, which enables slices to dynamically switch on and off based on real-time network traffic. Furthermore, we formulate a two-timescale optimization problem that jointly addresses slice switching and resource allocation to maximize long-term slice average energy efficiency while guaranteeing service delay requirements. To solve the joint problem, we decouple the problem into two subproblems in different timescales and develop a learning-based two-layer slice switching and resource allocation (SWEET) algorithm to make decisions in an online manner. Specifically, the long-timescale slice switching decisions are determined via a reinforcement learning algorithm in an outer layer, while the short-timescale resource allocation decisions are determined via leveraging coalition game and convex optimization in an inner layer. Extensive simulation results based on real-world datasets demonstrate that the SWEET algorithm yields an average improvement of 16.45% in slice energy efficiency, as well as adapts to network dynamics.

We propose a digital twin-assisted adaptive preloading scheme to reduce bandwidth waste as well as enhance user quality of experience (QoE) for short video streaming. Though preloading video content can reduce rebuffering and improve user QoE, non-sequential playback of short videos induced by user swipe can result in substantial bandwidth wastage in mobile networks. To tackle this problem, we first model the short video streaming system and carry out preloading threshold analysis. We then construct a digital twin-assisted adaptive preloading framework for short video streaming. By collecting and analyzing the user's historical throughput and tracking swipe timing information, a throughput prediction model and a probabilistic model can be constructed to accurately predict future throughput and user swipe behavior, respectively. Utilizing the predicted information and real-time running status data from a short video application, we design a preloading strategy to enhance bandwidth efficiency while achieving high user QoE. Simulation results demonstrate the effectiveness of our proposed scheme compared with the state-of-the-art schemes.

Wireless cut-through transmission, based on in-band full-duplex (FD) technique, has a great potential to improve the end-to-end throughput of a multi-hop wireless network via enabling simultaneous multi-hop relaying transmissions in the same frequency band. Different from single-hop relaying transmission, cut-through transmission has multiple relaying transmission modes, which makes it more difficult to achieve the maximum end-to-end throughput via improving the spatial reuse in a multi-hop wireless network. The goal of this paper is to improve the end-to-end throughput in a multi-hop wireless network with cut-through capability. In particular, we first establish an effective analytical model and find that the achievable end-to-end throughput is mainly determined by the cut-through mode, the spatial reuse factor, the protocol overhead, and the channel rate. Then, we give a comprehensive analysis for these factors in a string-topology multi-hop wireless network. We design a low-overhead distributed medium access control (MAC) protocol, and propose a transmit-delay mechanism to improve spatial reuse and link scheduling. Furthermore, we design an algorithm to adaptively select the optimal transmission parameters, including the cut-through mode, the spatial reuse factor, and the channel rate. Extensive simulations show that the proposed MAC design can effectively improve the end-to-end throughput by more than 55 percent, compared with the state-of-the-art protocol.

In this paper, we consider a full-duplex enabled cellular system operated in the unlicensed mmWave band. In particular, the full-duplex gNB is equipped with multiple antennas and applies hybrid beamforming for downlink transmissions, meanwhile mobile users send uplink traffic to the gNB with an omni-directional antenna. In the unlicensed bands, the cellular networks need to ensure a fair coexistence with other systems, such as WiGig. Therefore, a sum rate maximization problem is formulated to improve the throughput of the cellular system meanwhile suppressing its interference to the WiGig system. The formulated problem is non-convex and of high complexity. In order to efficiently address it, the sum rate maximization problem is first reformulated into a weighted mean square error minimization problem, and then the penalty dual decomposition method is applied to jointly optimize the uplink transmit power and downlink hybrid beamforming. Numerical results show that the performance of the proposed unlicensed full-duplex enabled cellular network degrades by nearly 29% in order to fairly coexist with the WiGig system. However, compared with half-duplex systems, applying full-duplex technology to our proposed network can improve the sum rate by nearly 56%.

In-band full-duplex (FD) technique can efficiently improve the end-to-end throughput of a multi-hop network via enabling multi-hop FD amplify-and-forward relaying (cut-through) transmission. This paper investigates the optimal hop size of a cut-through transmission and spatial reuse to achieve the maximum achievable end-to-end throughput of a multi-hop network. In particular, we consider spatial reuse and establish an interference model for a string-topology multi-hop network with x-hop cut-through transmission, and show that the maximum achievable end-to-end throughput is a function of x and the spatial separation between two concurrently active cut-through transmissions. Through extensive numerical studies, we show that the achievable date rate of a cut-through transmission drastically decreases along with the increase of the hop size x. Furthermore, we find that the 2-hop cut-through transmission mode can always achieve the maximum end-to-end throughput using Shannon Capacity formula if the spatial reuse is properly addressed. On the other hand, the results show that the 5-hop cut-through transmission mode can obtain the maximum end-to-end throughput with discrete channel rates when the self-interference cancellation is perfect and the hop distance is small.

The in-band full-duplexing is a promising technique to boost wireless network throughput by allowing a node to transmit and receive simultaneously. This paper provides a comprehensive investigation on the hidden-node problem that arises in the full-duplex (FD) enabled carrier-sensing multiple-access (CSMA) networks. In particular, we first provide the fundamental conditions that guarantee successful receptions for all the FD transmission cases, and propose an ellipse interference model and an ellipse carrier-sensing model to capture the interference relations and the carrier-sensing mechanism in FD CSMA networks, respectively. We further establish the hidden-node-free design in FD CSMA networks. Specifically, we show the sufficient conditions on the carrier-sensing power threshold that can eliminate hidden-node collisions. We show that compared with half-duplex CSMA networks, the FD CSMA network needs a much smaller carrier-sensing power threshold to prevent hidden-node collisions, which leads to poor network spatial reuse. This motivates us to further propose a new medium access control (MAC) protocol with Full-duplex Enhanced Carrier-Sensing (FECS) mechanism. The FECS-MAC enables the secondary carrier-sensing before starting the secondary transmission. We show that with the secondary carrier-sensing design, the required carrier-sensing powerthreshold can be increased while keeping the network hidden-node free. Therefore, the network spatial reuse and throughput can be significantly improved. Simulation results demonstrate that the FECS-MAC can improve the throughput of dense three-node FD networks by more than 30 percent, compared with relay full-duplex (RFD) MAC protocol proposed in [1].

Although it is commonly expected that the citation context of a reference is likely to provide more detailed and direct information about the nature of a citation, few studies in the literature have specifically addressed the extent to which the information in different parts of a scientific publication differs. Do abstracts tend to use conceptually broader terms than sentences in a citation context in the body of a publication? In this article, we propose a method to analyze and compare latent topics in scientific publications, in particular, from abstracts of papers that cited a target reference and from sentences that cited the target reference. We conducted an experiment and applied topical modeling techniques to full‐text papers in eight biomedicine journals. Topics derived from the two sources are compared in terms of their similarities and broad‐narrow relationships defined based on information entropy. The results show that abstracts and citation contexts are characterized by distinct sets of topics with moderate overlaps. Furthermore, the results confirm that topics from abstracts of citing papers have broader terms than topics from citation contexts formed by citing sentences. The method and the findings could be used to enhance and extend the current methodologies for research evaluation and citation evaluation.