Sum Rate Maximization Versus MSE Minimization in FDD Massive MIMO Systems With Short Coherence Time

Abstract

The increasing demand for higher data rates motivates the exploration of advanced techniques for future wireless networks. To this end, massive multiple-input multiple-output (mMIMO) is envisioned as the most essential technique to meet this demand. However, the expansion of the number of antennas in mMIMO systems with short coherence time makes the downlink channel estimation (DCE) overhead potentially overwhelming. As such, the number of training sequence (TS) needs to be significantly reduced. However, reducing the number of TS reduces the mean-squared error (MSE) accuracy significantly and to date it is not clear to what extend can this TS reduction affects the achievable sum rate performance. Therefore, this paper develops a low complexity and tractable TS solution for DCE and establishes an analytical framework for the optimum TS. Furthermore, the tradeoff between the achievable sum rate maximization criteria and the MSE minimization criteria is investigated. This investigation is essential to characterize the optimum TS length and the actual performance of mMIMO systems when the channel exhibits a limited coherence time. To this end, the statistical structure of mMIMO channels is exploited. In addition, this paper utilizes a random matrix theory (RMT) method to characterize the downlink achievable sum rate and MSE in a closed-form. This paper shows that maximizing the downlink sum rate criterion is more important than minimizing the MSE of the SINR only, which is typically considered in the conventional MIMO systems and/or in the time division duplex (TDD) mMIMO systems. The results demonstrate that a feasible downlink achievable sum rate can be achieved in an frequency division duplex (FDD) mMIMO system. This finding is necessary to extend the benefit of mMIMO systems to high frequency bands such as millimeter-wave (mmWave) and Terahertz (THZ) communications.INDEX TERMS Massive MIMO transmission, downlink channel estimation, achievable sum rate maximization, frequency division duplex operation mode, second order channel statistics, random matrix theory, mean square error minimization.

The Role of Correlation in the Performance of Massive MIMO Systems

“…In a block-fading model, the channels are considered to be frequency flat, which remain unchanged during a constant period of time that corresponds to a channel coherence time of T [29]. Two common transmission modes are used in the current generation of wireless communications systems, namely time-division duplex (TDD) and frequency-division duplex (FDD) [30][31][32][33]. The canonical m-MIMO systems are typically considered to operate in TDD mode, where the uplink and downlink transmissions share the same frequency band.…”

Integrated Sensing and Secure Communication with XL-MIMO

“…It should be noted that all the aforementioned papers on secrecy ISAC address the far-field scenario, where both radar targets and communication users reside within the far-field region of the transmitter. Motivated by the great success of multiple-input multiple-output (MIMO) technology in 4G and 5G [ 12 , 13 ], in future 6G networks, extremely large-scale (XL)-MIMO is envisioned to be utilized. XL-MIMO, deploying hundreds, or even thousands, of antenna elements at base stations or reflecting elements at reconfigurable intelligent surfaces, can significantly improve performance, such as spectral efficiency [ 14 ].…”

Maximizing the Downlink Data Rates in Massive Multiple Input Multiple Output with Frequency Division Duplex Transmission Mode Using Power Allocation Optimization Method with Limited Coherence Time

“…Hence, this research concentrates on FDD transmission, where the downlink CSI estimation is determined using a dedicated downlink training sequence during the CSI estimation phase. Specifically, to acquire CSI estimation in the FDD mode, the BS needs to design a specific training sequence and direct this sequence to the users [18,19]. However, the BS with a MMIMO system operates with a large number of antenna elements, which poses a significant challenge in channel estimation, especially in FDD operation with limited coherence time (LCT).…”