###### Abstract  
Photonic millimeter-wave communication systems are promising for high-capacity, high-speed wireless networks, and their production is driven by the growing demand from data-intensive applications. However, challenges such as inter-symbol interferences (ISIs), inter-band interferences (IBIs), symbol timing offsets (STOs), and nonlinearity impairments exist, especially in non-orthogonal multiband configurations. This paper proposes and demonstrates the neural network-based waveform-to-symbol converter (NNWSC) for a coordinated multi-input and single-output (MISO) photonic millimeter-wave system with multiband multiplexing. The NNWSC replaces conventional matched filtering, down-sampling, and equalization, simplifying the receiver and enhancing interference resilience. Additionally, it reduces computational complexity, improving operational feasibility. As a proof of concept, experiments are conducted in a 16 QAM non-orthogonal multiband carrierless amplitude and phase (NM-CAP) modulation system with coordinated MISO configurations in a scenario where two base stations have 5 km and 10 km fiber links, respectively. Data were collected across various roll-off factors, sub-band spacings, and received optical power (ROP) levels. Based on the proposed method, a coordinated MISO photonic millimeter-wave (mmWave) communication system at 91.9 GHz is demonstrated at a transmission speed of 30 Gbps. The results show that the NNWSC-based receiver achieves significant bit error rate (BER) reductions compared to conventional receivers across all configurations. The tolerances to the STO of NNWSC are also studied. These findings highlight NNWSC integration as a promising solution for high-frequency, interference-prone environments, with potential improvements for low-SNR and dynamic STO scenarios. photonic mmWave communication system; neural network (NN); waveform-to-symbol converter +
Footnote †: journal: _arXiv  
0000-0001-88 requirements for higher data rates and denser network support [2]. The sixth-generation (6G) mobile network aims to address these limitations by extending into higher frequency bands, such as mmWave and terahertz (THz) spectra, which offer broad bandwidth and ultrafast data transmission [3; 4]. However, transitioning to these high-frequency bands presents challenges, particularly in signal propagation, interference, and system complexity, necessitating advanced signal processing and transmission architectures [5]. To address these challenges, photonic mmWave communication systems have emerged as a promising solution by integrating optical fiber and wireless access technologies, combining the vast bandwidth of photonics with the coordination and beamforming capabilities of mmWave systems [6; 7]. In previous research, photonic mmWave communication systems have demonstrated the potential for high-capacity data transmission by combining photonic and mmWave technologies, particularly in dense network environments with fiber X-haul and mobile access [8; 9; 10; 11; 12]. Notable progress has been made in using advanced modulation techniques, such as non-orthogonal multiband carrierless amplitude and phase (NM-CAP) modulation, to increase spectral efficiency and reduce interference in multi-sub-band configurations. Studies have shown that NM-CAP enables closer sub-band spacing, which can significantly boost bandwidth utilization [13; 14; 15; 16; 17; 18]. However, this advantage comes with challenges, including inter-symbol interferences (ISIs), inter-band interferences (IBIs), and inter-channel interferences (ICIs), especially in non-orthogonal systems. Conventional digital signal processing (DSP) techniques, such as matched filtering, least mean squares (LMS) equalization, and interference cancellation using independent component analysis (ICA), have been applied to mitigate these interferences [15; 19]. Although effective to a degree, these methods often experience error accumulation in the cascaded filtering and equalization stages.