Energy-efficient Antenna Selection Research Articles

Improved Butterfly Optimization Algorithm for Energy Efficient Antenna Selection Over Wireless Cellular Networks

Improved Butterfly Optimization Algorithm for Energy Efficient Antenna Selection Over Wireless Cellular Networks

XL-MIMO energy-efficient antenna selection under non-stationary channels

Massive multiple-input-multiple-output (M-MIMO) is a key technology for 5G networks. Within this research area, new types of deployment are arising, such as the extremely-large regime (XL-MIMO), where the antenna array at the base station (BS) has extreme dimensions. As a consequence, spatial non-stationary properties appear as the users see only a portion of the antenna array, which is called visibility region (VR). In this challenging transmission–reception scenario, an algorithm to select the appropriate antenna-elements for processing the received signal of a given user in the uplink (UL), as well as to transmit the signal of this user during downlink (DL) is proposed. The advantage of not using all the available antenna-elements at the BS is the computational burden and circuit power consumption reduction, improving the energy efficiency (EE) substantially. Numerical results demonstrate that one can increase the EE without compromising considerably the spectral efficiency (SE). Under few active users scenario, the performance of the XL-MIMO system shows that the EE is maximized using less than 20% of the antenna-elements of the array, without compromising the SE severely.

Energy-Efficient Resource Allocation in Single-RF Load-Modulated Massive MIMO HetNets

Due to the dramatic increase in wireless data traffic and the associated increase in energy consumption, designing energy-efficient wireless networks with improved spectral efficiency is a pressing concern. The focus of this article is the design of a green, highly energy-efficient cellular heterogeneous network (HetNet) by taking advantage of multiple-input-multiple-output (MIMO) structure and deployment of small cells. We consider the downlink of a two-tier HetNet, in which multiple-antenna small cells are coordinated to serve users. Even though the deployment of MIMO together with small cells improves the communication system's performance in terms of data rate and reliability, circuit energy consumption in such a network is a critical issue. To address this, an energy-efficient antenna selection and radio resource block assignment algorithm is proposed for the small cells, and a single radio-frequency (RF) chain structure is considered for the massive MIMO macro base station. Then, while coordinating transmissions between cells subject to user-centric clustering, an energy-efficient beamforming design and power allocation optimization problem with respect to the quality of service requirement of users, transmit power budget of base stations, and fronthaul capacity is formulated; the problem is solved using the Dinkelbach method. Simulation results demonstrate the performance potential of our proposed algorithm in terms of energy efficiency and spectral efficiency.

Energy-efficient antenna selection in green MIMO relaying communication systems

In existing literature on multiple-input multiple-output (MIMO) relaying communication systems, antenna selection is often implemented by maximizing the channel capacity or the output single-to-noise ratio (SNR). In this paper, we propose an energy efficient low-complexity antenna selection scheme for MIMO relaying communication systems. The proposed algorithm is based on beamforming andmaximizing the Frobenius norm to jointly optimize the transmit power, number of active antennas, and antenna subsets at the source, relaying and destination. We maximize the energy efficiency between the link of source to relay and the link of relay to destination to obtain the maximum energy efficiency of the system, subject to the SNR constraint. Compared to existing antenna selection methods forMIMO relaying communication systems, simulation results demonstrate that the proposedmethod can save more power in term of energy efficiency, while having lower computational complexity.

Invited Paper: Antenna selection in energy efficient MIMO systems: A survey

With the explosive growth and need for high-speed wireless communications, more and more energy is consumed to support the required quality of service. Therefore, energy efficient or green communication has become a very hot topic under the ground of limited energy resource and environmentally friendly transmission schemes. MIMO technique is capable of reducing the transmission power thanks to its diversity and multiplexing gain. Moreover, antenna selection (AS) is an alternative to extract many of the benefits in MIMO systems with a reduced cost of complexity and power. Although many works including several survey papers have investigated AS in MIMO systems, the goal of these works is only the capacity maximization or error rate minimization, which fails to guarantee the optimality of the energy efficiency in MIMO systems. In this paper, we overview the state of the art in the AS schemes in energy efficient MIMO systems, the goal of which is to optimize the energy efficiency of the whole system. Specifically, we introduce energy efficient AS in point-to-point MIMO, cooperative MIMO, multiuser MIMO and largescale MIMO systems, respectively. Several challenging and practical issues in this area are also addressed.

Energy efficiency of massive MIMO wireless communication systems with antenna selection

Massive multiple-input multiple-output (MIMO) requires a large number (tens or hundreds) of base station antennas serving for much smaller number of terminals, with large gains in energy efficiency and spectral efficiency compared with traditional MIMO technology. Large scale antennas mean large scale radio frequency (RF) chains. Considering the plenty of power consumption and high cost of RF chains, antenna selection is necessary for Massive MIMO wireless communication systems in both transmitting end and receiving end. An energy efficient antenna selection algorithm based on convex optimization was proposed for Massive MIMO wireless communication systems. On the condition that the channel capacity of the cell is larger than a certain threshold, the number of transmit antenna, the subset of transmit antenna and servable mobile terminals (MTs) were jointly optimized to maximize energy efficiency. The joint optimization problem was proved in detail. The proposed algorithm is verified by analysis and numerical simulations. Good performance gain of energy efficiency is obtained comparing with no antenna selection.