Energy Efficiency and Spectral Efficiency Tradeoff in Massive MIMO Multicast Transmission with Statistical CSI

Abstract

As the core technology of 5G mobile communication systems, massive multi-input multi-output (MIMO) can dramatically enhance the energy efficiency (EE), as well as the spectral efficiency (SE), which meets the requirements of new applications. Meanwhile, physical layer multicast technology has gradually become the focus of next-generation communication technology research due to its capacity to efficiently provide wireless transmission from point to multipoint. The availability of channel state information (CSI), to a large extent, determines the performance of massive MIMO. However, because obtaining the perfect instantaneous CSI in massive MIMO is quite challenging, it is reasonable and practical to design a massive MIMO multicast transmission strategy using statistical CSI. In this paper, in order to optimize the system resource efficiency (RE) to achieve EE-SE balance, the EE-SE trade-offs in the massive MIMO multicast transmission are investigated with statistical CSI. Firstly, we formulate the eigenvectors of the RE optimization multicast covariance matrices of different user terminals in closed form, which illustrates that in the massive MIMO downlink, optimal RE multicast precoding is supposed to be done in the beam domain. On the basis of this viewpoint, the optimal RE precoding design is simplified into a resource efficient power allocation problem. Via invoking the quadratic transform, we propose an iterative power allocation algorithm, which obtains an adjustable and reasonable EE-SE tradeoff. Numerical simulation results reveal the near-optimal performance and the effectiveness of our proposed statistical CSI-assisted RE maximization in massive MIMO.

Energy Efficiency Trade-off with Spectral Efficiency in MIMO Systems

“…2a and concluded in Tab. 5, for the optimal tradeoff the SE increases from 0 to 10 [Bit /s/Hz] when CP l wattage increased up to 15 watts but decreases the EE from 2 × 10 7 to 2.5 × 10 5 as [21] expresses this fact. The optimal points for the tradeoff of SE-EE are shown in Fig.…”

“…In [20][21][22], authors consider the channel state information of the transmitter to derive the expression of the signal-to-noise ratio based on the number of PCs and antennas to optimize the trade-off. In [23], the author proposed two algorithms for complex optimization methods to obtain optimization in EE-SE trade-off.…”

Spectral efficiency analysis for massive MIMO orthogonal frequency division multiplexing and filter bank multicarrier in a realistic scenario using signal‐to‐noise‐and‐distortion ratio and interpolation for different modulation coding schemes

“…This implies that intrinsic interference errors and other problems generated by the excessive number of antennas in the BS, are not being addressed. More recently, the authors in Reference 15 considers imperfections in the CSI, as a statistical CSI model is employed, although no regard to the possible modulation or coding schemes in the RF signal were made. Also, intending to increase SE in demodulation, the study in Reference 16 proposes a multiuser detector for MIMO‐OFDM systems as concurrent of MRC and ZF combiners, while considering the Rayleigh channel.…”