2020
DOI: 10.1109/tsp.2020.2986391
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Spectral Efficiency and Energy Efficiency Tradeoff in Massive MIMO Downlink Transmission With Statistical CSIT

Abstract: As a key technology for future wireless networks, massive multiple-input multiple-output (MIMO) can significantly improve the energy efficiency (EE) and spectral efficiency (SE), and the performance is highly dependant on the degree of the available channel state information (CSI). While most existing works on massive MIMO focused on the case where the instantaneous CSI at the transmitter (CSIT) is available, it is usually not an easy task to obtain precise instantaneous CSIT. In this paper, we investigate EE-… Show more

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Cited by 69 publications
(44 citation statements)
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“…where H ki is the real decomposition of H ki , and Γ is given by (21). Treating interference as noise, we can derive the rate of user k ∈ {1, 2, ..., K} as [40], [52], [58]…”
Section: System Modelmentioning
confidence: 99%
“…where H ki is the real decomposition of H ki , and Γ is given by (21). Treating interference as noise, we can derive the rate of user k ∈ {1, 2, ..., K} as [40], [52], [58]…”
Section: System Modelmentioning
confidence: 99%
“…2 in Section IV. As discussed, the approaches based on the ergodic capacity might achieve better average performance [6]- [8], [17]. However, they are not suitable to quasi-static channels considered in this paper [9].…”
Section: System Model and Problem Formulationmentioning
confidence: 92%
“…The reason for considering the stochastic model is that it can properly represent several types of CSI error such as the error caused by the minimum mean squared error estimator [5] or time delay in reciprocity-based channel estimation [3], [4]. For the longterm performance, a popular approach is focusing on sum ergodic data rate [6]- [8]. This approach can achieve good average performance, but, it is inapplicable to slow fading channel and delay-sensitive users since the codeword should be sufficiently long to experience all possible fading states [9,Chap.…”
Section: Introductionmentioning
confidence: 99%
“…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.…”
Section: Related Workmentioning
confidence: 99%