phy and mac algorithm development

This study addresses the lack of systematic and accessible technical analyses of codebook-based beamforming in 5G New Radio (NR), particularly concerning Precoding Matrix Indicators (PMIs). It provides a comprehensive examination of the evolution of beamforming codebooks from 3GPP Release 15 to Release 18, elucidating their design principles, the physical interpretation of key parameters, and their information representation mechanisms. Through mathematical modeling, performance benchmarking, comparative analysis of feedback schemes, and scenario-dependent evaluations, the work offers an in-depth comparison between conventional and port-selection codebooks. Notably, this paper establishes a pedagogically oriented, unified framework for understanding these technologies—filling a critical gap in intuitive explanations and visual analyses absent from standardization documents—and delivers a clear technical reference for both academia and industry while outlining promising directions for future research.

To address physical-layer modeling distortions and the inability to accurately capture deep-fading mitigation effects in mid-band digital wireless communication system simulations, this paper proposes a comprehensive end-to-end physical-layer modeling framework for the mid-band. Departing from conventional baseband simplifications, it establishes, for the first time, a unified discrete-time complex baseband model that jointly captures pulse shaping, up/down-conversion, mixing, carrier synchronization, and symbol timing recovery. Implemented in MATLAB for a single-input single-output (SISO) system, the framework demonstrates that temporal alignment and frequency-offset coupling among modules critically govern deep-fading mitigation behavior. The proposed approach significantly enhances simulation fidelity and interpretability for mid-band systems, offering both pedagogical clarity and engineering practicality. It provides a high-fidelity platform for PHY-layer algorithm design and performance evaluation.

This paper addresses beam misalignment in analog beamforming for 3GPP millimeter-wave NR systems, modeling long-term misalignment under the coupled effects of user mobility, SSB periodicity, TDD frame structure, and deployment parameters. Method: It innovatively incorporates practical NR constraints—such as SSB overhead, timing restrictions, and feasible beam count—into a Poisson process modeling framework. Contribution/Results: The work derives, for the first time, closed-form expressions for misalignment duration, misalignment ratio, and beamforming gain loss. The analytical model uncovers fundamental trade-offs among beam count, user velocity, and SSB configuration, providing theoretical design guidelines for robust beam management. Numerical evaluation using 3GPP-standard parameters validates model accuracy and quantifies parameter sensitivity and optimization boundaries.

This paper systematically investigates multi-source interference in OFDM physical-layer systems, encompassing inter-symbol interference (ISI), inter-block interference (IBI), inter-carrier interference (ICI), and inter-cell interference (also denoted ICI), alongside adversarial interference mechanisms—including jamming and spoofing attacks. Methodologically, it establishes the first unified multi-interference modeling framework and a cross-layer interference taxonomy; further, it proposes an interference-resilient OFDM modulation candidate suite tailored for 6G. Through integrated interference modeling, signal processing, network-level coordination, and robustness evaluation, the work quantitatively compares bit-error-rate (BER) performance degradation under SNR reduction across 12 modulation schemes. The results establish a theoretical benchmark and validate technical feasibility for 6G physical-layer design, positioning the proposed framework as a foundational contribution to next-generation resilient waveform development.

To address the joint scheduling challenge of communication, radar search, and tracking tasks under QoS constraints in multi-cell integrated sensing and communication (ISAC) networks, this paper proposes an interference-aware medium access control (MAC) framework. Methodologically, it jointly optimizes radar scanning patterns and inter-cell task scheduling, formulating a QoS-driven multi-task resource reuse model and designing a low-complexity algorithm for dynamic sensing-communication resource coordination. The key contribution lies in the first explicit incorporation of radar scanning degrees of freedom—such as azimuth/elevation angular resolution and revisit interval—into MAC-layer scheduling decisions, thereby enabling deep coupling between physical-layer sensing characteristics and link-layer task orchestration. Simulation results demonstrate that the proposed scheme achieves a 23.7% gain in spectral efficiency and an 18.4% improvement in radar target detection probability, while strictly satisfying latency and reliability QoS requirements—significantly outperforming conventional orthogonal scheduling and static scanning baselines.

This study addresses the challenge of accurately evaluating key performance indicators for unmanned aerial vehicles (UAVs) in 5G New Radio (NR) networks, where their altitude-induced coverage and interference characteristics differ significantly from those of terrestrial users. The authors develop a 3GPP-compliant system-level simulation framework incorporating three-dimensional antenna radiation patterns, LOS/NLOS probability models, and multi-site tri-sector deployments. For the first time, they identify the critical altitude at which UAVs transition from coverage-limited to interference-limited regimes and quantify the coupled effects of inter-site distance and UAV height on RSRP, RSRQ, and SINR. Results reveal that SINR degrades sharply with increasing altitude due to dominant line-of-sight interference, while larger inter-site distances—despite reducing received power—effectively improve both SINR and RSRQ.

This study addresses the cross-layer protocol adaptation challenges in 5G New Radio Non-Terrestrial Networks (NR-NTN) for satellite communications, spanning the physical layer, MAC layer, and higher-layer protocols. It systematically examines the full protocol stack design issues specified in 3GPP 5G NR-NTN standards, leveraging the ns-3 simulation platform to quantitatively evaluate the impact of critical impairments—such as large propagation delays and Doppler shifts—on overall network performance. By incorporating realistic channel characteristics, this work presents the first end-to-end simulation analysis of NR-NTN protocol stack adaptability, offering empirical evidence and actionable design insights to inform future protocol optimization and standardization efforts.

This study addresses the problem of distributed throughput optimization in dense multi-access point (Multi-AP) IEEE P802.11be networks by constructing a packet-level system model that incorporates CSMA/CA, RTS/CTS, beam training overhead, directional millimeter-wave interference, SINR-driven MCS selection, and retransmission mechanisms. The configuration optimization is formulated as a combinatorial multi-armed bandit (CMAB) problem with multiple groups. To efficiently navigate the high-dimensional discrete configuration space, the authors propose an innovative exploration strategy guided by Hadamard matrices and a grouped combinatorial Successive Accept-Reject (CSAR) algorithm. Experimental results demonstrate that the proposed approach significantly improves both aggregate and per-AP throughput across various AP densities and reduces throughput convergence time by approximately 49%.

To address the high baseband processing power consumption and hardware overhead in millimeter-wave (mmWave) massive MIMO systems, this work proposes a beam-domain sparse adaptive equalization framework. The core method introduces the Complex Sparse Adaptive Equalizer (CSPADE) algorithm and derives configurable parallel and serial multiply-accumulate (MAC)-based VLSI architectures. For the first time, beam-domain equalization hardware is validated in 22 nm fully depleted silicon-on-insulator (FDSOI) technology. Under optimal throughput, the fully parallel architecture reduces power consumption by 54% compared to conventional antenna-domain equalization, while the serial MAC architecture achieves 66% energy savings. Both energy efficiency and area efficiency achieve state-of-the-art performance. This work establishes a holistic co-optimization across algorithm, architecture, and process technology, delivering a practical, low-power hardware solution for mmWave communication baseband processing.

This study addresses the compounded interference caused by residual self-interference and carrier frequency offset in full-duplex FBMC/QAM multi-user MISO systems. It presents the first systematic end-to-end effective channel model, elucidating the interference structure of FBMC/QAM under full-duplex MIMO configurations, and leverages the Balian–Low theorem to compare performance limits across modulation schemes. The work proposes an online sum-rate optimization framework based on stochastic successive convex approximation, integrating closed-form power updates, MRT/Zero-Forcing precoding, and PHYDYAS prototype filters (Type-I/II) to substantially enhance spectral efficiency and link robustness. Simulations demonstrate that, in the presence of residual frequency offset, FBMC/QAM achieves significantly lower bit error rates and higher network throughput compared to CP-OFDM.