Abstract
This paper investigates the energy efficiency (EE) optimization for massive multiple-input multiple-output (MIMO) systems powered by wireless power transfer (WPT) with hardware impairments at sensor nodes (SNs). In the considered system, the SNs are first powered by the WPT from power beacon (PB). Then, the SNs use the harvested energy to transmit data to the base station (BS) with large scale of multiple antennas. Finally, the BS employs maximal-ratio combining (MRC) to detect the data symbols transmitted by the SNs. As the EE optimization problem is a non-convex problem which is difficult to solve directly. A lower bound approximation and variable substitution method are used to transform the EE maximization problem into a concave-linear fractional programming. Then, an energy efficient resource allocation algorithm that combines time and power allocation is proposed by fractional programming to maximize the EE of the system. Finally, simulation results are presented to show the effectiveness of the proposed algorithm and the impact of the hardware impairments on the system performance.
Highlights
Wireless devices such as wireless sensor networks are powered by battery which needs manual charging in wired mode or battery replacement
In [23], we proposed an energy-efficient resource allocation algorithm for massive multiple-input multiple-output (MIMO) systems powered by wireless power transfer (WPT) with hardware impairments at sensor nodes (SNs)
We prove that the power beacon (PB) should transmit the maximum power
Summary
Wireless devices such as wireless sensor networks are powered by battery which needs manual charging in wired mode or battery replacement. In [9], the authors studied a wireless-energytransfer (WET)-enable massive MIMO system and proposed a joint time and energy resource allocation algorithm to maximize throughput. Z. Wang et al.: EE Optimization for WPT Enabled Massive MIMO Systems With Hardware Impairments power allocation of the base station (BS) under the delay outage requirements of different users. As the EE is a key performance indicator of future mobile communication system [21], we consider the EE maximization problem for WPT-enabled massive MIMO systems under hardware impairments in this paper. In [23], we proposed an energy-efficient resource allocation algorithm for massive MIMO systems powered by WPT with hardware impairments at SNs. the feasible of quality of service (QoS) of each SN are not discussed.
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