Energy Efficiency Optimization for Massive MIMO Non-Orthogonal Unicast and Multicast Transmission with Statistical CSI
Abstract
:1. Introduction
- With statistical CSI, we formulate the EE maximization problem for NOUM transmission in the massive MIMO scenario.
- We determine the optimal transmit directions of the multicast and unicast transmission in closed-form, respectively, and then simplify the large-scale complex-matrix-valued precoding design problem into a real-vector-valued power allocation problem in the beam domain.
- We reduce the computational complexity of the EE optimization problem significantly by replacing the objective function with its deterministic equivalent (DE).
- With guaranteed convergence, we propose an algorithm on beam domain power allocation using the minorize maximize (MM) algorithm and Dinkelbach’s transform. We deal with the EE optimization problem by iteratively solving a series of related convex optimization problems.
- We adopt to represent real-valued vector space and to denote complex-valued vector space.
- represents the identity matrix of size .
- indicates that matrix is positive semidefinite.
- represents the expectation operation.
- ⊙ denotes the Hadamard product.
- Denote as the trace operation, as the transpose operation, as the conjugate operation, as the conjugate-transpose operation, and as the determinant operation.
- ∼ stands for “be distributed as”, and ≜ stands for “be defined as”.
2. System Model
3. NOUM Transmission in Massive MIMO
3.1. Problem Formulation
3.2. Optimal Transmit Directions
3.3. Energy-Efficient Power Allocation for NOUM Transmission
Algorithm 1 Energy-Efficient Power Allocation Algorithm in the Beam Domain for Massive MIMO NOUM Transmission |
Input: Beam domain channel statistics , initial power allocation matrix , outer iteration threshold and inner iteration threshold Output: Power allocation matrix in the beam domain 1: Initialization: 2: Calculate 3: while do 4: Initialization: , let , calculate with (38) 5: while do 6: Let 7: Calculate via solving problem (37) with 8: Calculate using (38) 9: end while 10: Let 11: Let 12: Calculate with (39) 13: end while 14: return |
4. Numerical Results
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A. Proof of Theorem 1
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Parameter | Value |
---|---|
Scenario | Suburban macro |
Channel model | 3GPP SCM |
Pathloss | −120 dB |
Array topology | ULA with antenna spacing half wavelength |
Noise variance | dBm |
Number of UTs | |
Number of BS antennas | |
Number of UT antennas | |
Transmission bandwidth | W= 10 MHz |
Amplifier drain efficiency | |
Circuit power consumption per antenna | dBm |
Static power consumption | dBm |
Weights |
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Wang, W.; Huang, Y.; You, L.; Xiong, J.; Li, J.; Gao, X. Energy Efficiency Optimization for Massive MIMO Non-Orthogonal Unicast and Multicast Transmission with Statistical CSI. Electronics 2019, 8, 857. https://doi.org/10.3390/electronics8080857
Wang W, Huang Y, You L, Xiong J, Li J, Gao X. Energy Efficiency Optimization for Massive MIMO Non-Orthogonal Unicast and Multicast Transmission with Statistical CSI. Electronics. 2019; 8(8):857. https://doi.org/10.3390/electronics8080857
Chicago/Turabian StyleWang, Wenjin, Yufei Huang, Li You, Jiayuan Xiong, Jiamin Li, and Xiqi Gao. 2019. "Energy Efficiency Optimization for Massive MIMO Non-Orthogonal Unicast and Multicast Transmission with Statistical CSI" Electronics 8, no. 8: 857. https://doi.org/10.3390/electronics8080857