Abstract
This paper proposes a dynamic resource allocation scheme to maximize the energy efficiency (EE) for Massive MIMO Systems. The imperfect channel estimation (CE) and feedback are explicitly considered in the EE maximization problem, which aim to optimize the power allocation, the antenna subset selection for transmission, and the pilot assignment. Assuming CE error to be bounded for the complex-constrained Cramer–Rao Bound (CRB), theoretical results show that the lower bound is directly proportional to its number of unconstrained parameters. Utilizing this perspective, a separated and bi-directional estimation is developed to achieve both low CRB and low complexity by exploiting channel and noise spatial separation. Exploiting global optimization procedure, the optimal resource allocation can be transformed into a standard convex optimization problem. This allows us to derive an efficient iterative algorithm for obtaining the optimal solution. Numerical results are provided to demonstrate that the outperformance of the proposed algorithms are superior to existing schemes.
Highlights
The foreseen demand increasing in data rate has triggered a research race for discovering new ways to enhance the spectral efficiency of the generation of mobile and wireless networks [1].Benefiting from spatial multiplexing, massive MIMO systems can enjoy asymptotically orthogonal channels, arbitrary small transmit power, and negligible noise, providing significant performance gains in terms of spectral efficiency (SE), security, and reliability compared with conventional MIMO [2].all of these benefits can be achieved through linear processing with low complexity.the usage of a large number of base station (BS) antennas in massive MIMO can significantly increase the radio frequency (RF) circuits and digital signal processing (DSP) power consumption, which has a severe impact on EE [3]
To overcome the drawbacks of channel state information (CSI) distortion in Traditional channel estimation (TCE) and feedback, the design of separated and bi-directional estimation can significantly increase the accuracy of CSI feedback
The simulation results show that the maximum EE obtained through the proposed resource allocation (RA) strategy under the separated and bi-directional estimation (SCE) model surpasses the strategy 5% when TCE is chosen and 6% less than the perfect CSI condition
Summary
The foreseen demand increasing in data rate has triggered a research race for discovering new ways to enhance the spectral efficiency of the generation of mobile and wireless networks [1]. Benefiting from spatial multiplexing, massive MIMO systems can enjoy asymptotically orthogonal channels, arbitrary small transmit power, and negligible noise, providing significant performance gains in terms of spectral efficiency (SE), security, and reliability compared with conventional MIMO [2] All of these benefits can be achieved through linear processing with low complexity. Most existing works optimizing the resource allocation strategies generally rely on a common assumption that the whole channel characteristics are perfectly known at both the receiver and the transmitter These assumptions seem impractical, especially in frequency division duplexing (FDD) system since noise interference poses significant challenges to channel estimation and channel state information (CSI) feedback.
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