MAC-LEAP: Multi-antenna, cross layer, energy adaptive protocol☆
Introduction
In wireless networks, reducing the energy dissipation is paramount in order to extend the lifetime of the network. One approach to reducing the energy required for communication is to employ Multiple-Input Multiple-Output (MIMO) or multi-antenna communication [1], [2], [3]. This communication paradigm is not only a promising solution for improving the spectral efficiency, but it additionally improves the overall energy efficiency of wireless networks. Using MIMO communications, the transmit power is spread among more than one antenna that, for a particular Bit-Error-Rate (BER) requirement, results in an overall higher power gain, therefore improving the spectral efficiency [4].
While previous work has shown the benefit of using adaptive MIMO communications in wireless networks [5], [6], [7], none of these previous work has addressed the problem of energy conservation. An essential factor in reducing the node energy consumption lies in the trade-off between the transmit power and the energy consumption of the transmitter circuit. Although multi-antenna systems require a complex transceiver circuitry design that entails a high power consumption at the circuit level, using multiple antennas enables a reduction in the actual power consumption of the power amplifier thanks to the increased spectral efficiency. As a result, both the circuit power consumption and the transmit power consumption must be considered together in order to optimize the energy consumed by the communication link [8].
A number of researchers have developed approaches to optimize multi-antenna networks by selecting the optimal MIMO scheme to use for communication. Different antenna selection algorithms can be employed at both the transmitter and the receiver sides in order to choose the number of antennas based on the channel Signal-to-Noise Ratio (SNR), the system capacity, and spatial diversity [9]. For example, in a multi-user MIMO system, by considering a signal-to-interference plus noise ratio (SINR) threshold that must be met, one possible solution is to select the number of antennas that maximizes the SINR of the worst above-the-threshold user [10]. Alternatively, the number of antennas can be chosen dynamically for each node based on their transmission distance to minimize the total energy consumption [11] or based on the Channel State Information (CSI) [12], [13]. If no CSI feedback is available at the transmitter, as is the case for the cross-layer protocol presented in [8] that dynamically switches between MIMO and Single-Input Multiple-Output (SIMO) communications, the number of antennas is determined by the receiver and sent back to the sender.
In this paper, we present Multi-Antenna, Cross Layer, Energy Adaptive Protocol (MAC-LEAP), which is an energy efficient cross layer protocol designed for MIMO-based wireless networks that employs dynamic antenna selection to use the most energy efficient approach for data transmission. MAC-LEAP dynamically adjusts the number of transmitter and receiver antennas to use for the communication on a per-packet basis, based on the current remaining energy of the nodes, their distance, BER requirements, and other physical layer parameters. Based on a standard CSMA/CA protocol, MAC-LEAP utilizes Request-To-Send (RTS) and Clear-To-Send (CTS) packets to provide collision avoidance. Information regarding the transmitter location and current energy, which is required for the dynamic antenna selection, is included in the RTS packet. Using this information, MAC-LEAP runs a dynamic antenna selection algorithm at the receiver to find the most energy efficient MIMO scheme that provides the highest link lifetime. The receiver piggybacks this information onto the CTS packet so that both nodes know what MIMO scheme to use for the subsequent data transmission.
Unlike traditional protocols that use a fixed number of antennas for a specific distance and channel BER, MAC-LEAP adapts the MIMO scheme to be used for the communication according to the current remaining energy levels of both the transmitter and receiver nodes. The specific contributions of this paper are:
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We propose various dynamic antenna selection policies that consider the immediate remaining energy of the nodes as well as other factors such as distance and BER. Based on the energy level of the transmitting and receiving nodes, the algorithm selects the number of antennas that maximizes the link lifetime.
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The dynamic antenna selection policies are integrated in a cross layer protocol, MAC-LEAP, which selects the best set of antennas on a per-packet basis for the communication for both single-hop and multi-hop networks. The protocol selects the most energy-efficient MIMO scheme for both the transmitter and the receiver and uses the RTS/CTS handshake to transfer some information required by the dynamic antenna selection policy prior to the data transmission.
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We introduce a MIMO-based framework for wireless communication into Network Simulator 3 (ns-3), which, to the best of our knowledge, has not been implemented before. Based on this framework, wireless nodes in the ns-3 simulator may use more than one antenna for MIMO communication.
The remainder of the paper is organized as follows. In Section 2, we provide a review of related work in the area of MIMO technology in wireless networks. In Section 3, we present the energy consumption model of MAC-LEAP as well as the equations for meeting the BER requirements in MIMO channels. In Section 4, we describe different dynamic antenna selection policies employed in MAC-LEAP, and in Section 5, we introduce the proposed MAC-LEAP protocol. In Section 6, we compare the performance of MAC-LEAP with both fixed antenna schemes (e.g., MISO) and the E-Basic protocol [11] via extensive simulations, and discuss the results and the improvement of MAC-LEAP compared to these other protocols. Finally, conclusions are drawn in Section 7.
Section snippets
Motivation and Related Work
In contrast to Single-Input Single-Output (SISO) systems, Multiple-Input Multiple-Output (MIMO) systems employ more than one antenna at both the transmitter and the receiver. Thus, MIMO provides two main advantages for the wireless communications: spatial diversity gain and spatial multiplexing gain. The spatial multiplexing gain is obtained by extending the degrees of freedom by sending multiple orthogonal data streams simultaneously [14] which results in having a higher data rate in the
System Model
In this section, we present the energy consumption model and the data transmission scheme employed in MAC-LEAP to meet a required BER. In the rest of the paper, we assume that each node is equipped with two antennas, and may use a different number of antennas adaptively for their communication. The number of antennas is selected such that the total number of received packets in the network is maximized. The required information for the antenna selection is transferred among the nodes using the
Dynamic Antenna Selection Policies
In a wireless network, the total remaining energy and, consequently, the total lifetime of the system, depends on the lifetimes of both the transmitter and the receiver. For instance, if the transmitter has enough energy but the receiver does not, or vice versa, by choosing a fixed communication scheme, the bottleneck node will eventually be depleted. The main goal of our solution is to extend the lifetime of the system by varying the MIMO scheme over time. In what follows, we first propose an
MAC-LEAP
In this section, we describe the details of the MAC-LEAP protocol.
Simulation Results
In this section, we evaluate the performance of MAC-LEAP using the different policies described in Section 4 and under various settings. We assume a Rayleigh fading wireless channel with an average path loss that falls off with square of distance (d2). The initial parameters for the simulation setting are listed in Table 1. We use the circuitry power consumption employed in [33], [34], [35], [36] and set the channel data rate Rb to 1 Mbps, the data generation rate at the transmitter node Rg to
Conclusions
In this paper, we proposed a new cross-layer energy-adaptive protocol (MAC-LEAP) for multi-antenna wireless networks. MAC-LEAP dynamically adjusts the number of antennas at the transmitter and the receiver sides based on the remaining energy of the nodes such that the number of received packets is maximized. Employing a CSMA/CA protocol, MAC-LEAP utilizes RTS and CTS packets to not only provide collision avoidance but also to transfer energy related information among the nodes. Thus, unlike the
Hoda Ayatollahi received her B.Sc. degree in Computer Engineering from Alzahra University, Tehran, Iran in 2006 and her M.Sc. degree from Sharif University of Technology, Tehran, Iran in 2010. In 2007, she visited MAGFA Information Technology Development Center, Tehran, Iran where she performed research on programming of the video camera specialized for auditorium. She is currently a PhD student in Wireless Communications and Networking Group (WCNG) in the Department of Electrical and Computer
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Hoda Ayatollahi received her B.Sc. degree in Computer Engineering from Alzahra University, Tehran, Iran in 2006 and her M.Sc. degree from Sharif University of Technology, Tehran, Iran in 2010. In 2007, she visited MAGFA Information Technology Development Center, Tehran, Iran where she performed research on programming of the video camera specialized for auditorium. She is currently a PhD student in Wireless Communications and Networking Group (WCNG) in the Department of Electrical and Computer Engineering at the University of Rochester, Rochester, NY. Her research interests lie in the area of wireless communications and networking, MIMO, and energy harvesting.
Cristiano Tapparello received the B.Sc. and the M.Sc. Degree (with honors) in Computer Engineering from University of Padova (Italy) in 2005 and 2008, respectively. He received the Ph.D. in Information Engineering from the same university in 2012. In 2011 he visited the Center for Wireless Communication and Signal Processing Research at New Jersey Institute of Technology, Newark, where he performed research on the design of networking protocols for energy harvesting wireless networks under the supervision of Prof. Osvaldo Simeone. From January 2012 to October 2013, he has been a Postdoctoral Researcher at the SIGNET group, Department of Information Engineering (DEI) at University of Padova. From October 2013 to June 2016, he has been a Postdoctoral Research Associate in the Wireless Communications and Networking Group (WCNG) in the Department of Electrical and Computer Engineering at the University of Rochester, Rochester, NY. He is currently a Research Associate in the Department of Electrical and Computer Engineering at the University of Rochester.
Wendi Heinzelman is a full professor in the Department of Electrical and Computer Engineering at the University of Rochester. She holds a secondary appointment in the Computer Science Department at Rochester. She is also currently the Dean of the Edmund A. Hajim School of Engineering and Applied Sciences. During spring 2008, she was a Visiting Erskine Fellow at the University of Canterbury in Christchurch, New Zealand. She received a B.S. degree in Electrical Engineering from Cornell University in 1995 and M.S. and Ph.D. degrees in Electrical Engineering and Computer Science from MIT in 1997 and 2000, respectively. Her current research interests lie in the area of wireless communications and networking, mobile computing, and multimedia communication. She is a member of N⌃2 Women and SWE, a Distinguished Scientist of ACM Sigmobile, and a Fellow of the IEEE Communications Society, the IEEE Signal Processing Society, and the IEEE Computer Society.
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This research was funded in part by the National Science Foundation under research grant CNS-1239423.