Efficient iterative massive MIMO detection using Chebyshev acceleration

Implementation of the deep learning method for signal detection in massive-MIMO-NOMA systems

“…The throughput and intricacy of the suggested technique are equal to those of the current methods in Ref. [ 18 ] based on the BER and number of convolutions. The results demonstrated that the recommended approach significantly lowers the computational complexity while providing the required performance with a constrained number of repeats.…”

Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systems

“…According to random matrix theory [6], the spectral radius of $$\mathbf {B}$$ is given by $$\begin{equation} \rho (\mathbf {B})=\max |\lambda (\mathbf {B})|, \end{equation}$$where $$\lambda (\mathbf {B})$$ donates the eigenvalue of matrix $$\mathbf {B}$$. The spectral radius of $$\mathbf {W}$$ [2] and the largest and smallest eigenvalues of $$\mathbf {W}$$ can be approximated as $$\begin{equation} \rho (\mathbf {W})=|\lambda _{\text{max}}(\mathbf {W})|=N {\left(1+\sqrt {\xi } \right)}^{2}, \end{equation}$$ $$\begin{equation} \rho (\mathbf {W})=|\lambda _{\text{min}}(\mathbf {W})|=N {\left(1-\sqrt {\xi } \right)}^{2}, \end{equation}$$where $$\xi =N/K$$ is the ratio between the number of antennas and the number of users. The optimal iteration polynomials …”

“…Introduction: Massive MIMO is a key technology for fifth-generation (5G) communication systems to achieve higher data rate, lower latency, higher reliability, and more connected users [1,2]. Despite all of its advantages, massive MIMO requires complex transceiver signal processing.…”

“…where λ(B) donates the eigenvalue of matrix B. The spectral radius of W [2] and the largest and smallest eigenvalues of W can be approximated as…”

Deep Unfolding of Chebyshev Accelerated Iterative method for Massive MIMO Detection

“…While iterative methods can be attractive due to their simplicity, the convergence rate can be further improved through the Chebyshev acceleration [25]. Recent studies have applied the Chebyshev acceleration technique to improve the convergence rates of iterative methods in massive MIMO detection [26], [27].…”