RIS-Assisted Backscatter V2I Communication System: Spectral-Energy Efficient Trade-Off
Abstract
1. Introduction
- To attain a balance between EE and SE for the distributed RIS-assisted backscatter V2I system, a novel multi-objective optimization framework is established for the first time using the linear weighting method. The optimization problem is transformed into a strictly convex problem by quadratic transformation. Then, an AO approach is applied to partition the original problem into two independent subproblems. The weighted minimization mean-square error (WMMSE) algorithm and the Riemannian conjugate gradient (RCG) algorithm are, respectively, used for the BS beamforming vectors and RIS phase shift matrices and converge rapidly through iterative optimization.
- Existing research predominantly overlooks the critical impact of the BD power reflection coefficient on RIS-assisted backscatter V2I system performance. To address this gap, this paper presents, to the best of our knowledge, the first investigation of its impact on both EE and SE performance in such systems. By jointly designing the beamforming for the BS and RIS, the BD power reflection coefficients are dynamically optimized subject to their activation requirements and the vehicle minimum QoS, thereby further enhancing the EE-SE trade-off performance.
- Unlike the conventional single RIS-assisted backscatter V2I communication system, distributed RIS is used in this paper to provide a high-quality link between the BS and BD, which overcomes the limitations of single RIS, such as high channel correlation and restricted beam steering range. It enables more parallel transmissions, thereby supporting a greater number of BDs and boosting the overall EE and SE performance of the backscatter V2I system. This distributed architecture also facilitates continuous signal transmission, which is crucial for the dynamic and mobile nature of V2I communication.
2. System Model
3. Optimization Problem Formulation
4. Optimization Scheme
4.1. BS Beamforming Optimization
Algorithm 1 WMMSE-based algorithm. |
Step 1. Initialize to feasible values, the iteration number t = 0. |
Iterate repeatedly |
Step 2. Equivalently transform (P3) into an equivalent convex form by introducing auxiliary variables , and . |
Step 3. Obtain the closed-form expression for the optimal values of and by problem (P6). |
Step 4. Rewrite and problem (P7). |
Step 5. Optimize by standard convex optimization algorithms. |
Step 6. = + 1 |
Until the value of the objective function P7 converges |
4.2. Phase Shift Optimization of RIS
- 1.
- Riemannian Gradient Computation: This key operation involves projecting the Euclidean gradient onto the complex circle manifold to obtain the Riemannian gradient:
- 2.
- Determine the Search Direction: The search direction is given by a tangent vector which is conjugate to :
- 3.
- Retraction: Apply the retraction operation to map the tangent vector back onto the complex circle manifold:
Algorithm 2 RCG-based algorithm. |
Step 1. Initialize to feasible values, the iteration number = 0, iteration search direction |
Iterate repeatedly |
Step 2. Update Euclidean gradient of the objective function by (37). |
Step 3. Calculate Riemannian conjugate gradient by (36). |
Step 4. Updating the search direction by (39). |
Step 5. Select the Armijo step size which satisfy |
Step 6. Retraction by (41) |
Step 7. = + 1 |
Until the value of the objective function (36) converges |
4.3. BD Power Reflection Coefficient Optimization
4.3.1. The Range of the BD Power Reflection Coefficient
4.3.2. Determination of the Optimal BD Power Reflection Coefficient
Algorithm 3 AO algorithm. |
Step 1. Equivalently transform expression of (P1) into (P3) by quadratic transform. |
Step 2. Initialize , and to feasible values. And set the iteration number ite = 0. |
Iterate repeatedly |
Step 3. Optimize by WMMSE algorithm. |
Step 4. Optimize by RCG algorithm. |
Step 5. Calculate of the feasible range (42) and (43) for the . |
Step 6. Optimize by (44). |
Step 7. = + 1 |
Step 8. Update , and . |
Until the value of the objective function P1 converges |
Step 9. Output , and . |
5. Simulations
5.1. Simulation Scenario Settings
- S-RIS-phaserand: Only the BS beamforming vector is optimized by the WMMSE algorithm while the single RIS has random phase shift matrices .
- D-RIS-phaserand: Only the BS beamforming vector is optimized by the WMMSE algorithm while distributed RIS has random phase shift matrices .
- S-RIS-WMMSE + RCG: The BS beamforming vector and RIS phase shift matrices undergo alternating optimization by WMMSE and RCG with single RIS assistance.
- D-RIS-WMMSE + RCG: The BS beamforming vector and RIS phase shift matrices undergo alternating optimization by WMMSE and RCG with distributed RIS assistance.
- without-RIS: The BS beamforming vector is optimized by the WMMSE algorithm without RIS assistance.
5.2. Simulation Results and Analysis
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Parameters | Value |
---|---|
Number of BS antennas () | 128 |
Number of RIS reflection elements () | 100 |
Number of BDs with single antennas () | 4 |
Carrier frequency | 28 GHz |
Transmission bandwidth | 100 MHz |
BD-BR sub-channel path loss | 22.55 + 35.3lg + 20g dB |
Backscattering period () | 4 s |
Noise power spectral density | −174 dBm/Hz |
Sampling frequency | 1 × 104 Hz |
BR moving speed | 2 m/s |
Width and height of the RIS elements | 0.234 times the wavelength |
RIS pose | [[0, 0, −1]; [−0.7071, 0.7071, 0]; [0.7071, 0.7071, 0]] |
Passive BD activation threshold () | −20 dBm |
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Dong, Y.; Xu, P.; Lan, X.; Wang, Y.; Li, Y. RIS-Assisted Backscatter V2I Communication System: Spectral-Energy Efficient Trade-Off. Electronics 2025, 14, 3800. https://doi.org/10.3390/electronics14193800
Dong Y, Xu P, Lan X, Wang Y, Li Y. RIS-Assisted Backscatter V2I Communication System: Spectral-Energy Efficient Trade-Off. Electronics. 2025; 14(19):3800. https://doi.org/10.3390/electronics14193800
Chicago/Turabian StyleDong, Yi, Peng Xu, Xiaoyu Lan, Yupeng Wang, and Yufeng Li. 2025. "RIS-Assisted Backscatter V2I Communication System: Spectral-Energy Efficient Trade-Off" Electronics 14, no. 19: 3800. https://doi.org/10.3390/electronics14193800
APA StyleDong, Y., Xu, P., Lan, X., Wang, Y., & Li, Y. (2025). RIS-Assisted Backscatter V2I Communication System: Spectral-Energy Efficient Trade-Off. Electronics, 14(19), 3800. https://doi.org/10.3390/electronics14193800