اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدEnergy-Efficient Antenna Selection and Power Allocation for Large-Scale Multiple Antenna Systems with Hybrid Energy Supply
168
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
The combination of energy harvesting and large-scale multiple antenna technologies provides a promising solution for improving the energy efficiency (EE) by exploiting renewable energy sources and reducing the transmission power per user and per antenna. However, the introduction of energy harvesting capabilities into large-scale multiple antenna systems poses many new challenges for energy-efficient system design due to the intermittent characteristics of renewable energy sources and limited battery capacity. Furthermore, the total manufacture cost and the sum power of a large number of radio frequency (RF) chains can not be ignored, and it would be impractical to use all the antennas for transmission. In this paper, we propose an energy-efficient antenna selection and power allocation algorithm to maximize the EE subject to the constraint of users quality of service (QoS). An iterative offline optimization algorithm is proposed to solve the non-convex EE optimization problem by exploiting the properties of nonlinear fractional programming. The relationships among maximum EE, selected antenna number, battery capacity, and EE-SE tradeoff are analyzed and verified through computer simulations.
قيم البحث
اقرأ أيضاً
Large-scale distributed-antenna system (L-DAS) with very large number of distributed antennas, possibly up to a few hundred antennas, is considered. A few major issues of the L-DAS, such as high latency, energy consumption, computational complexity,
and large feedback (signaling) overhead, are identified. The potential capability of the L-DAS is illuminated in terms of an energy efficiency (EE) throughout the paper. We firstly and generally model the power consumption of an L-DAS, and formulate an EE maximization problem. To tackle two crucial issues, namely the huge computational complexity and large amount of feedback (signaling) information, we propose a channel-gain-based antenna selection (AS) method and an interference-based user clustering (UC) method. The original problem is then split into multiple subproblems by a cluster, and each clusters precoding and power control are managed in parallel for high EE. Simulation results reveal that i) using all antennas for zero-forcing multiuser multiple-input multiple-output (MU-MIMO) is energy inefficient if there is nonnegligible overhead power consumption on MU-MIMO processing, and ii) increasing the number of antennas does not necessarily result in a high EE. Furthermore, the results validate and underpin the EE merit of the proposed L-DAS complied with the AS, UC, precoding, and power control by comparing with non-clustering L-DAS and colocated antenna systems.
Large-scale antenna (LSA) has gained a lot of attention due to its great potential to significantly improve system throughput. In most existing works on LSA systems, orthogonal frequency division multiplexing (OFDM) is presumed to deal with frequency
selectivity of wireless channels. Although LSA-OFDM is a natural evolution from multiple-input multiple-output OFDM (MIMO-OFDM), the drawbacks of LSA-OFDM are inevitable, especially when used for the uplink. In this paper, we investigate single-carrier (SC) modulation for the uplink transmission in LSA systems based on a novel waveform recovery theory, where the receiver is designed to recover the transmit waveform while the information-bearing symbols can be recovered by directly sampling the recovered waveform. The waveform recovery adopts the assumption that the antenna number is infinite and the channels at different antennas are independent. In practical environments, however, the antenna number is always finite and the channels at different antennas are also correlated when placing hundreds of antennas in a small area. Therefore, we will also analyze the impacts of such non-ideal environments.
Large-scale antenna (LSA) or massive multiple-input multiple-output (MIMO) has gained a lot of attention due to its potential to significantly improve system throughput. As a natural evolution from traditional MIMO-orthogonal frequency division multi
plexing (OFDM), LSA has been combined with OFDM to deal with frequency selectivity of wireless channels in most existing works. As an alternative approach, single-carrier (SC) has also been proposed for LSA systems due to its low implementation complexity. In this article, a comprehensive comparison between LSA-OFDM and LSA-SC is presented, which is of interest to the waveform design for the next generation wireless systems.
In this work, we present a switched relaying framework for multiple-input multiple-output (MIMO) relay systems where a source node may transmit directly to a destination node or aided by relays. We also investigate relay selection techniques for the
proposed switched relaying framework, whose relays are equipped with buffers. In particular, we develop a novel relay selection protocol based on switching and the selection of the best link, denoted as Switched Max-Link. We then propose the Maximum Minimum Distance (MMD) relay selection criterion for MIMO systems, which is based on the optimal Maximum Likelihood (ML) principle and can provide significant performance gains over other criteria, along with algorithms that are incorporated into the proposed Switched Max-Link protocol. An analysis of the proposed Switched Max-Link protocol and the MMD relay selection criterion in terms of computational cost, pairwise error probability, sum-rate and average delay is carried out. Simulations show that Switched Max-Link using the MMD criterion outperforms previous works in terms of sum-rate, pairwise error probability, average delay and bit error rate.
In this paper, energy efficient resource allocation is considered for an uplink hybrid system, where non-orthogonal multiple access (NOMA) is integrated into orthogonal multiple access (OMA). To ensure the quality of service for the users, a minimum
rate requirement is pre-defined for each user. We formulate an energy efficiency (EE) maximization problem by jointly optimizing the user clustering, channel assignment and power allocation. To address this hard problem, a many-to-one bipartite graph is first constructed considering the users and resource blocks (RBs) as the two sets of nodes. Based on swap matching, a joint user-RB association and power allocation scheme is proposed, which converges within a limited number of iterations. Moreover, for the power allocation under a given user-RB association, we first derive the feasibility condition. If feasible, a low-complexity algorithm is proposed, which obtains optimal EE under any successive interference cancellation (SIC) order and an arbitrary number of users. In addition, for the special case of two users per cluster, analytical solutions are provided for the two SIC orders, respectively. These solutions shed light on how the power is allocated for each user to maximize the EE. Numerical results are presented, which show that the proposed joint user-RB association and power allocation algorithm outperforms other hybrid multiple access based and OMA-based schemes.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
