Low-complexity MRC Receiver Algorithm Based on OTFS System

WANG Zhenduo; JI Tianzhi; SUN Rongchen

doi:10.11999/JEIT241056

Volume 47 Issue 5

May 2025

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WANG Zhenduo, JI Tianzhi, SUN Rongchen. Low-complexity MRC Receiver Algorithm Based on OTFS System[J]. Journal of Electronics & Information Technology, 2025, 47(5): 1392-1401. doi: 10.11999/JEIT241056

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WANG Zhenduo, JI Tianzhi, SUN Rongchen. Low-complexity MRC Receiver Algorithm Based on OTFS System[J]. Journal of Electronics & Information Technology, 2025, 47(5): 1392-1401. doi: 10.11999/JEIT241056

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Low-complexity MRC Receiver Algorithm Based on OTFS System

doi: 10.11999/JEIT241056 cstr: 32379.14.JEIT241056

College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China

Funds: The National Natural Science Foundation of China (62001138)

Received Date: 2024-12-02
Rev Recd Date: 2025-05-05

Available Online: 2025-05-10

Publish Date: 2025-05-01

Abstract

Abstract

Objective Ultra-high-speed mobile applications—such as Unmanned Aerial Vehicles (UAVs), high-speed railways, satellite communications, and vehicular networks—place increasing demands on communication systems, particularly under high-Doppler conditions. Orthogonal Time Frequency Space (OTFS) modulation offers advantages in such environments due to its robustness against Doppler effects. However, conventional receiver algorithms rely on computationally intensive matrix operations, which limit their efficiency and degrade real-time performance in high-mobility scenarios. This paper proposes a low-complexity Maximum Ratio Combining (MRC) receiver for OTFS systems that avoids matrix inversion by exploiting the structural characteristics of OTFS channel matrices in the Delay-Doppler (DD) domain. The proposed receiver achieves high detection performance while substantially reducing computational complexity, supporting practical deployment in ultra-high-speed mobile communication systems. Methods The proposed low-complexity receiver algorithm applies MRC in the DD domain to iteratively extract and coherently combine multipath components. This approach enhances Bit Error Rate (BER) performance by optimizing signal aggregation while avoiding computationally intensive operations. To further reduce complexity, the algorithm incorporates interleaving and deinterleaving operations that restructure the channel matrix into a sparse upper triangular Heisenberg form. This transformation enables efficient matrix decomposition and facilitates simplified processing. To address the computational burden associated with matrix inversion during symbol detection, a low-complexity LDL decomposition algorithm is introduced. Compared with conventional matrix inversion techniques, this method substantially reduces computational overhead. Furthermore, a low-complexity inversion method for lower triangular matrices is implemented to further improve efficiency during the decision process. Simulation results confirm that the proposed receiver achieves BER performance comparable to that of traditional MRC algorithms while significantly lowering computational complexity. Results and Discussions Simulation results confirm that the proposed low-complexity MRC receiver achieves BER performance comparable to that of conventional MRC receivers while substantially improving computational efficiency under high-mobility conditions (Fig. 3). The algorithm is evaluated across a range of environments, including scenarios characterized by high-speed motion and complex multipath interference. It outperforms Linear Minimum Mean Square Error (LMMSE) equalizers and Gauss–Seidel iterative equalization algorithms. Despite its reduced complexity, the proposed receiver maintains the same BER performance as traditional MRC methods. The algorithm demonstrates effective scalability as the number of symbols and subcarriers increases. Under conditions of increased system complexity, the receiver sustains computational efficiency without performance degradation (Fig. 4, Fig. 5). These results support its suitability for practical deployment in high-speed mobile communication systems employing OTFS modulation. The receiver also exhibits strong resilience to variations in wireless channel models. Across both typical urban multipath scenarios and high-velocity vehicular conditions, it maintains stable BER performance (Fig. 8). In addition, the receiver demonstrates robust tolerance to Doppler shift fluctuations and variable noise levels. These characteristics enable its application in dynamic environments with rapidly changing channel conditions. The algorithm’s efficiency and performance stability make it particularly well suited for real-time implementation in ultra-high-mobility networks, including UAV systems, high-speed rail communications, and other next-generation wireless platforms. By reducing computational complexity without compromising detection accuracy, the proposed receiver supports large-scale deployment of OTFS-based systems, addressing key performance and scalability challenges in emerging communication infrastructures. Conclusions This study proposes a low-complexity MRC receiver algorithm for OTFS systems. By introducing an interleaver and deinterleaver, the channel matrix is transformed into a sparse upper triangular form, enabling efficient inversion with reduced computational cost. In addition, the receiver integrates a low-complexity LDL decomposition algorithm and an upper triangular matrix inversion method to further minimize the computational burden associated with matrix operations. Simulation results confirm that the proposed receiver achieves equivalent BER performance to conventional MRC receivers. Moreover, under identical channel conditions, it demonstrates superior BER performance relative to linear receivers.
- Maximum Ratio Combining (MRC),
- Low complexity,
- Interleaver,
- Orthogonal Time Frequency Space (OTFS),
- Delay-Doppler(DD) domain

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References(16)

References

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