Integrated sensing and communication empowered by resilient massive access in SAGIN: An energy efficient perspective^✩,✩✩

Abstract

As key technologies in 6G, Space-Air-Ground Integrated Networks (SAGIN) promises to provide seamless global coverage through a comprehensive, ubiquitous communication system, while Integrated Sensing and Communications (ISAC) effectively addresses spectrum congestion by sharing spectrum resources and transceivers for simultaneous communication and sensing operations. However, existing ISAC research has primarily focused on terrestrial networks, with limited exploration of its applications in SAGIN environments. This paper proposes a novel SAGIN-ISAC scheme leveraging High-Altitude Platform Stations (HAPS). In this scheme, HAPS serves as a relay node that not only amplifies and forwards communication signals but also receives and processes target echo signals for parameter estimation. The satellite employs Resilient Massive Access (RMA) to provide communication services to different User Terminals (UTs). To address scenarios with an unknown number of targets, we develop a Two-threshold Detection and Parameter Multiple Signal Classification (MUSIC) algorithm (TDPM), which employs dual-threshold correlation detection to determine the number of targets and utilizes the MUSIC algorithm to estimate targets’ Angle of Arrival (AoA), range, and relative velocity. Furthermore, we establish a joint optimization framework that considers both communication and sensing performance, optimizing energy efficiency, detection probability, and the Cramér-Rao bound. The power allocation coefficients are derived through Nash equilibrium, while the precoding matrix is optimized using Sequential Convex Approximation (SCA) to address the non-convex nature of the optimization problem. Experimental results demonstrate that our proposed scheme significantly enhances the overall performance of the SAGIN-ISAC system.

Keywords

Space-air-ground integrated networks / Integrated sensing and communication / Resilient massive access / Precoding / Sequential convex approximation / Nash equilibrium

References

[1] H. Cui, J. Zhang, Y. Geng, Z. Xiao, T. Sun, N. Zhang, J. Liu, Q. Wu, X. Cao, Space- air-ground integrated network (SAGIN) for 6g: requirements, architecture and chal- lenges, China Commun. 19 (2) (2022) 90-108.

[2] X. Hu, Y. Yao, B. Li, Q. Yao, Z. Chang, W. Wang, F.M. Ghannouchi, Two-stage digi- tal predistortion with neural-network-assisted virtual beamforming for interchannel effects in mimo systems, IEEE Microw. Wirel. Technol. Lett. (2025) 1-4.

[3] K. Zhong, J. Hu, C. Pan, M. Deng, J. Fang, Joint waveform and beamforming design for ris-aided ISAC systems, IEEE Signal Process. Lett. 30 (2023) 165-169.

[4] X. Meng, N. Zhang, M. Jian, M. Kadoch, D. Yang, Channel modeling and estimation for reconfigurable-intelligent-surface-based 6g SAGIN iot, IEEE Internet Things J. 10 (11) (2023) 9273-9282.

[5] X. Zhu, C. Jiang, Integrated satellite-terrestrial networks toward 6g: architectures, applications, and challenges, IEEE Internet Things J. 9 (1) (2021) 437-461.

[6] V. Bankey, S. Sharma, S. R, A.S. Madhukumar, Physical layer security of haps- based space-air-ground-integrated network with hybrid fso/rf communication, IEEE Trans. Aerosp. Electron. Syst. 59 (4) (2023) 4680-4688.

[7] X. Wang, L.T. Yang, D. Meng, M. Dong, K. Ota, H. Wang, Multi-uav cooperative local- ization for marine targets based on weighted subspace fitting in SAGIN environment, IEEE Internet Things J. 9 (8) (2022) 5708-5718.

[8] Y. Liu, S. Zhang, X. Mu, Z. Ding, R. Schober, N. Al-Dhahir, E. Hossain, X. Shen, Evolution of noma toward next generation multiple access (ngma) for 6g, IEEE J. Sel. Areas Commun. 40 (4) (2022) 1037-1071.

[9] K. Guo, M. Wu, X. Li, Z. Lin, T.A. Tsiftsis, Joint trajectory and beamforming opti- mization for federated drl-aided space-aerial-terrestrial relay networks with ris and rsma, IEEE Trans. Wirel. Commun. 23 (12) (2024) 18456-18471.

[10] X. He, Z. Huang, H. Wang, R. Song, Sum rate analysis for massive mimo-noma uplink system with group-level successive interference cancellation, IEEE Wirel. Commun. Lett. 12 (7) (2023) 1194-1198.

[11] X. Li, X. Wang, H. Zhang, Y. Xu, L. Yang, M. Huang, W. Hao, G. Huang, Qos-aware performance analysis of full-duplex rsma vehicle road cooperation systems, IEEE Internet Things J. 11 (22) (2024) 36053-36065.

[12] X. Li, Q. Wang, M. Zeng, Y. Liu, S. Dang, T.A. Tsiftsis, O.A. Dobre, Physical-layer authentication for ambient backscatter-aided noma symbiotic systems, IEEE Trans. Commun. 71 (4) (2023) 2288-2303.

[13] I.N.A. Ramatryana, S.Y. Shin, Priority access in noma-based slotted aloha for over- load 6g massive iot, IEEE Commun. Lett. 26 (12) (2022) 3064-3068.

[14] H.-H. Choi, K.-M. Kang, H. Lee, Noma-based aloha protocol for air-to-ground com- munications with maximum transmit power limits, IEEE Internet Things J. 11 (16) (2024) 27387-27397.

[15] D. Deng, W. Zhou, X. Li, D.B. da Costa, D.W.K. Ng, A. Nallanathan, Joint beamform- ing and uav trajectory optimization for covert communications in ISAC networks, IEEE Trans. Wirel. Commun. 24 (2) (2025) 1016-1030.

[16] N. González-Prelcic, M. Furkan Keskin, O. Kaltiokallio, M. Valkama, D. Dardari, X. Shen, Y. Shen, M. Bayraktar, H. Wymeersch, The integrated sensing and commu- nication revolution for 6g: vision, techniques, and applications, Proc. IEEE 112 (7) (2024) 676-723.

[17] J. Du, H. Ma, Z. Yu, X. Li, S. Mumtaz, C. Yuen, Dl-based ISAC via tensor analysis in massive mimo-ofdm systems with spatial-frequency wideband effects, IEEE Internet Things J. 12 (5) (2025) 5093-5108.

[18] Z. Wei, H. Qu, Y. Wang, X. Yuan, H. Wu, Y. Du, K. Han, N. Zhang, Z. Feng, Integrated sensing and communication signals toward 5g-a and 6g: a survey, IEEE Internet Things J. 10 (13) (2023) 11068-11092.

[19] F. Liu, C. Masouros, A.P. Petropulu, H. Griffiths, L. Hanzo, Joint radar and com-munication design: applications, state-of-the-art, and the road ahead, IEEE Trans. Commun. 68 (6) (2020) 3834-3862.

[20] S. Chen, Y.-C. Liang, S. Sun, S. Kang, W. Cheng, M. Peng, Vision, requirements, and technology trend of 6g: how to tackle the challenges of system coverage, capacity, user data-rate and movement speed, IEEE Wirel. Commun. 27 (2) (2020) 218-228.

[21] L. Yin, Z. Liu, M.R.B. Shankar, M. Alaee-Kerahroodi, B. Clerckx, Integrated sensing and communications enabled low Earth orbit satellite systems, IEEE Netw. 38 (6) (2024) 252-258.

[22] B. Dong, J. Jia, Z. Li, G. Li, J. Shi, H. Wang, N. Chi, J. Zhang, Photonic-based flexible integrated sensing and communication with multiple targets detection capability for w-band fiber-wireless network, IEEE Trans. Microw. Theory Tech. 72 (8) (2024) 4878-4891.

[23] R. Zhang, L. Cheng, S. Wang, Y. Lou, Y. Gao, W. Wu, D.W.K. Ng, Integrated sensing and communication with massive mimo: a unified tensor approach for channel and target parameter estimation, IEEE Trans. Wirel. Commun. 23 (8) (2024) 8571-8587.

[24] Z. Huang, K. Wang, A. Liu, Y. Cai, R. Du, T.X. Han, Joint pilot optimization, target detection and channel estimation for integrated sensing and communication systems, IEEE Trans. Wirel. Commun. 21 (12) (2022) 10351-10365.

[25] K. Xu, X. Xia, C. Li, C. Wei, W. Xie, Y. Shi, Channel feature projection clustering based joint channel and doa estimation for ISAC massive mimo ofdm system, IEEE Trans. Veh. Technol. 73 (3) (2024) 3678-3689.

[26] Y. Liu, I. Al-Nahhal, O.A. Dobre, F. Wang, Deep-learning channel estimation for irs-assisted integrated sensing and communication system, IEEE Trans. Veh. Technol. 72 (5) (2022) 6181-6193.

[27] L. Zhang, X. Lei, T. Ma, H. Niu, C. Yuen, Joint user localization, channel estimation, and pilot optimization for RIS-ISAC, IEEE Trans. Wirel. Commun. 23 (12) (2024) 19302-19316.

[28] Z. Chen, M.-M. Zhao, M. Li, F. Xu, Q. Wu, M.-J. Zhao, Joint location sensing and channel estimation for irs-aided mmwave ISAC systems, IEEE Trans. Wirel. Commun. 23 (9) (2024) 11985-12002.

[29] Y. Lin, S. Jin, M. Matthaiou, X. Yi, Circular ris-enabled channel estimation and lo-calization for multi-user ISAC systems, IEEE Trans. Wirel. Commun. 23 (8) (2024) 8730-8743.

[30] W. Zhu, Y. Han, L. Wang, L. Xu, Y. Zhang, A. Fei, Pilot optimization for ofdm-based ISAC signal in emergency iot networks, IEEE Internet Things J. 11 (18) (2023) 29600-29614.

[31] S. Lu, F. Liu, F. Dong, Y. Xiong, J. Xu, Y.-F. Liu, S. Jin, Random ISAC signals deserve dedicated precoding, IEEE Trans. Signal Process. 72 (2024) 3453-3469.

[32] S. Li, W. Yuan, C. Liu, Z. Wei, J. Yuan, B. Bai, D.W.K. Ng, A novel ISAC transmission framework based on spatially-spread orthogonal time frequency space modulation, IEEE J. Sel. Areas Commun. 40 (6) (2022) 1854-1872.

[33] Z. Liao, F. Liu, A. Li, C. Masouros, Faster-than-Nyquist symbol-level precoding for wideband integrated sensing and communications, IEEE Trans. Wirel. Commun. 23 (8) (2024) 10445-10458.

[34] W. Jiang, Z. Wei, F. Liu, Z. Feng, P. Zhang, Collaborative precoding design for ad- jacent integrated sensing and communication base stations, IEEE Internet Things J. 11 (9) (2024) 15059-15074.

[35] N. Babu, C. Masouros, C.B. Papadias, Y.C. Eldar, Precoding for multi-cell ISAC: from coordinated beamforming to coordinated multipoint and bi-static sensing, IEEE Trans. Wirel. Commun. 23 (10) (2024) 14637-14651.

[36] Z. Wang, C. Xiao, X. Liu, M. Peng, J. Guo, Interference mitigation in multi-cell ISAC systems: a three-dimensional mimo precoding approach, IEEE Commun. Lett. 28 (11) (2024) 2543-2547.

[37] A. Gupta, M. Jafri, S. Srivastava, A.K. Jagannatham, L. Hanzo, An affine precoded superimposed pilot-based mmwave mimo-ofdm ISAC system, IEEE Open J. Commun. Soc. 5 (2024) 1504-1524.

[38] X. Lou, W. Xia, S. Chen, H. Zhu, Precoding for multi-static ISAC system with inte- grated active and passive sensing, IEEE Commun. Lett. 28 (9) (2024) 2036-2040.

[39] W. Hao, Y. Qu, S. Zhou, F. Wang, Z. Lu, S. Yang, Joint beamforming design for hybrid ris-assisted mmwave ISAC system relying on hybrid precoding structure, IEEE Internet Things J. 11 (18) (2024) 29455-29469.

[40] S. Zhang, W. Hao, G. Sun, C. Huang, Z. Zhu, X. Li, C. Yuen, Joint beamforming optimization for active star-ris-assisted ISAC systems, IEEE Trans. Wirel. Commun. 23 (11) (2024) 15888-15902.

[41] Z. Yang, D. Li, N. Zhao, Z. Wu, Y. Li, D. Niyato, Secure precoding optimization for noma-aided integrated sensing and communication, IEEE Trans. Commun. 70 (12) (2022) 8370-8382.

[42] W. Mao, Y. Lu, G. Pan, B. Ai, Uav-assisted communications in SAGIN-ISAC: mobile user tracking and robust beamforming, IEEE J. Sel. Areas Commun. 43 (1) (2025) 186-200.

[43] L. You, X. Qiang, C.G. Tsinos, F. Liu, W. Wang, X. Gao, B. Ottersten, Beam squint- aware integrated sensing and communications for hybrid massive mimo Leo satellite systems, IEEE J. Sel. Areas Commun. 40 (10) (2022) 2994-3009.

[44] Z. Liu, L. Yin, W. Shin, B. Clerckx, Rate-splitting multiple access for quantized ISAC Leo satellite systems: a max-min fair energy-efficient beam design, IEEE Trans. Wirel. Commun. 23 (10) (2024) 15394-15408.

[45] M. Huang, F. Gong, G. Li, N. Zhang, Q.-V. Pham, Secure precoding for satellite noma- aided integrated sensing and communication, IEEE Internet Things J. 11 (18) (2024) 29533-29545.

[46] B. Zhao, M. Wang, Z. Xing, G. Ren, J. Su, Integrated sensing and communication aided dynamic resource allocation for random access in satellite terrestrial relay networks, IEEE Commun. Lett. 27 (2) (2022) 661-665.

[47] C. Wang, M. Pang, T. Wu, F. Gao, L. Zhao, J. Chen, W. Wang, D. Wang, Z. Zhang, P. Zhang, Resilient massive access for SAGIN: a deep reinforcement learning approach, IEEE J. Sel. Areas Commun. 43 (1) (2025) 297-313.

[48] K. Werner, M. Jansson, P. Stoica, On estimation of covariance matrices with Kro- necker product structure, IEEE Trans. Signal Process. 56 (2) (2008) 478-491.