Throughput enhancement by exploiting spatial reuse opportunities with smart antenna systems in wireless ad hoc networks
Introduction
Wireless ad hoc networks are characterized by low cost and high transmission rates without requiring the use of any infrastructural support. The greatest challenge for improving the network throughput of ad hoc networks involves exploiting spatial reuse opportunities at which multiple packets can be exchanged simultaneously in an area without colliding with each other. Recent advances in antenna technology have increased spatial reuse opportunities.
Omnidirectional antennas transmit or receive signals equally well in all directions. Transmissions using omnidirectional antennas might easily create spatial bottlenecks that severely limit the overall network throughput. Unidirectional antennas [1], [2], [3], [11], [15] focus radio-frequency (RF) energy in a particular direction and exploit stronger beamforming, thereby saving energy and resulting in a smaller interference area compared to that of omnidirectional antenna systems. Although unidirectional antennas were originally applied for exploiting spatial reuse, they permit only one transmission or reception by a node at a given time. Recently, multiple-beam smart antennas [6], [7], [8], [10], [12], [13], [14] used in ad hoc networks have received attention because of their potential to improve network throughput. Through the application of complex digital signal processing techniques, multiple-beam smart antennas can support the simultaneous transmissions (or receptions) of multiple packets in different beams by using the same channel. This is the case with switched-beam smart antenna comprised of multiple beam antenna array (SB-MBA) [7], [13]. Numerous MAC scheduling approaches [6], [7], [14], [15], [16] have been proposed for increasing the opportunities for simultaneous transmissions (or receptions) and improving network throughput through smart antennas. However, enhanced scheduling to increase the parallel degree of transmissions with smart antenna systems is required.
Several studies [6], [7] have proposed scheduling protocols with smart antennas to improve the spatial reuse opportunities for unidirectional antennas. Although smart antenna systems can support multiple-beam formations in multiple directions, they cannot be used for data transmissions and receptions simultaneously. This constraint is referred to as the Tx/Rx constraint in this study. A host with smart antennas has the data diversity constraint, which restricts its communication with only one neighboring host in each beam; that is, a host equipped with k-beam smart antennas may communicate with a maximum of k different hosts during any given period. How to protect the packet transmission from interference for a given set of communication requests and minimize the transmission latency by considering the Tx/Rx and data diversity constraints are the key challenges for maximizing network throughput.
This study develops transmission scheduling schemes with multiple-beam smart antennas to improve network throughput and reduce delay time. The proposed mechanisms use clustering, and they centralize the intra-cluster scheduling but schedule the inter-clustering by using a distributed approach. In intra-cluster scheduling, each cluster header collects all transmission demands from its members, schedules parallel transmission pairs, and broadcasts the scheduling results to the cluster members. The proposed intra-cluster scheduling schemes exploit the opportunities for parallel transmissions and consider communication restrictions and packet sizes, to minimize the average latency and maximize the network throughput. Furthermore, the proposed schemes consider the transmission time of packets and regulate the orders of packet transmissions to minimize their packet delays.
The remainder of this study is organized as follows: Section 2 introduces related studies. Section 3 specifies the network environment and problem formulation. The proposed transmission scheduling algorithms for intra-cluster scheduling are presented in Sections 4 Scheduling mechanisms for a smart antenna system, 5 The S shows the proposed algorithms for scheduling inter-cluster transmissions. Section 6 provides a performance evaluation of the proposed schemes in contrast to those of existing studies, and finally, Section 7 offers a conclusion.
Section snippets
Related studies
Exploring spatial reuse opportunities to increase network capacity has become one of the most critical challenges for wireless ad hoc networks in recent years. Generally, advanced antenna technologies can be classified into unidirectional and multiple-beam smart antennas. Although multiple-beam smart antennas are more expensive than unidirectional antennas, they can sense neighboring hosts in each beam and support simultaneous transmissions (or receptions) of multiple packets in different
Network model
Let V denote the set of n hosts h1, h2, … , hn and E denote the set of neighboring connections between hosts, where E ∈ V × V. The topology of the ad hoc network can be defined by G = (V, E). Let Ni represent the set of single-hop neighbors of host hi. Each host has a unique ID and is equipped with a wide azimuth switched-beam smart antenna (SB-MBA), which comprises a k-beam antenna array [7], [13] to sense neighboring hosts in each beam of smart antennas. The antenna beam patterns of the SB-MBA are
Scheduling mechanisms for a smart antenna system
Two scheduling mechanisms, referred to as the Intra-S3 and S3 schemes, are proposed for the smart antenna system. The Intra-S3 scheme is proposed to schedule the communication pairs for each cluster, and the S3 scheme extends the Intra-S3 mechanism to the inter-cluster environment. In a cluster, the head is responsible for collecting the transmission requirements of the members and for arranging the transmission slots for the requirements. The proposed Intra-S3 scheme partitions the duration of
The S3 scheme
The proposed S3 scheme extends Intra-S3 to permit the consideration of inter-cluster scheduling. The applied inter-cluster scheduling operates on a cluster-based [9] network topology where several stations referred to as gateways participate in more than one cluster.
There are two challenges when extending the Intra-S3 algorithm from an intra-cluster to inter-cluster scenario. First, according to the beam mode constraint, a gateway cannot be scheduled to send a message from one cluster and
Simulation study
This section examines the performance improvement of the proposed Intra-S3 and S3 schemes against the ROMA [6] and ESIF [7] approaches in terms of aggregated throughput and average packet delay. Each node is equipped with an SB-MBA [13], and the transmitting range of the beam is set at 100 units at a data rate of 11 Mbps. The MAC protocol depicted in Subsection 4.4 is applied to the proposed schemes. Each node generates packets with sizes randomly chosen from 500, 1000, 1500, and 2000 bytes.
Conclusion
This paper proposes Intra-S3 and S3 approaches for scheduling transmissions using smart antenna systems. The Intra-S3 scheme with the MaxPTranscheduling approach considers the beam mode, data diversity, and interference constraints, and is designed to arrange a maximal number of simultaneous transmissions in different beams for exploiting spatial reuse opportunities. Furthermore, Intra-S3 with DAS further adjusts the transmissions among parallel groups to initiate each parallel group earlier,
Chao-Tsun Chang received the Ph.D. degree in Computer Science and Information Engineering from National Central University, Taiwan, in 2006. He is with the Department of Department of Information Management, Hsiuping University of Science & Technology, Taiwan, as an Associate Professor in 2012. In the recent ten years, he has directed eleven researching projects including seven national NSC projects and seven information system developments. He published thirteen SCI indexed journal papers,
References (18)
- et al.
Medium access control protocols using directional antennas in ad hoc networks
IEEE INFOCOM
(2000) - et al.
Directional virtual carrier sensing for directional antennas in mobile ad hoc networks
ACM MobiHoc
(2002) - et al.
CDR-MAC: a protocol for full exploitation of directional antennas in ad hoc wireless networks
IEEE Transactions on Mobile Computing
(2008) - et al.
Handling asymmetry in gain in directional antenna equipped ad hoc networks
IEEE PIMRC
(2005) - et al.
MDA: an efficient directional MAC scheme for wireless ad hoc networks
IEEE Globecom
(2005) - et al.
Receiver-oriented multiple access in ad hoc networks with directional antennas
Wireless Networks
(2005) - et al.
A cross layer MAC with explicit synchronization through intelligent feedback for multiple beam antennas
IEEE Globecom
(2005) On the performance of ad hoc networks with beamforming antennas
ACM MobiHoc
(2001)- et al.
CLTC: a cluster-based topology control for ad hoc networks
IEEE Trans. on Mobile Computing
(2004)
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Chao-Tsun Chang received the Ph.D. degree in Computer Science and Information Engineering from National Central University, Taiwan, in 2006. He is with the Department of Department of Information Management, Hsiuping University of Science & Technology, Taiwan, as an Associate Professor in 2012. In the recent ten years, he has directed eleven researching projects including seven national NSC projects and seven information system developments. He published thirteen SCI indexed journal papers, including IEEE TVT,IEEE Sensors,Computer Networks, ACM/Baltzer Journal of Wireless Networks, and Journal of Parallel and Distributed Computing. He is a member of the IEEE Computer Society and Communication Society. His current research interests include Ad Hoc wireless networks, wireless sensor networks, cooperative radio networks, and mobile computing.
Chih-Yung Chang received the Ph.D. degree in Computer Science and Information Engineering from National Central University, Taiwan, in 1995. He is currently a Full Professor with the Department of CSIE at Tamkang University, Taiwan. He served as an Associate Guest Editor of many SCI indexed Journals, including International Journal of Ad Hoc and Ubiquitous Computing (IJAHUC 2011 and 2012), International Journal of Distributed Sensor Networks (2012), IET Communications (2011), Telecommunication Systems (TS, 2010), Journal of Information Science and Engineering (JISE, 2008), and Journal of Internet Technology (JIT, 2004 and 2008). He was an Area Chair of IEEE AINA’2005, TANET’2000, TANET’2010, Vice Chair of IEEE WisCom’2005, EUC’2005 and IEEE ITRE’2005, IEEE AINA 2008, Program Co-Chair of IEEE MNSA’2005, UbiLearn’2006, WASN’2007, ACM SAMnet’2008, IEEE AHUC’2008, iCube’2010, iCube’2011, Workshop Co-Chair of MSEAT’2003, MSEAT’2004, IEEE INA’2005, ICS’2008, NCS’2009, IEEE VCNA’2009 and Publication Chair of MSEAT’2005 and SCORM’2006. He is a member of the IEEE Computer Society and Communication Society. His current research interests include Internet of Things, Wireless Sensor Networks, Ad Hoc Wireless Networks, and WiMAX broadband technologies.
Tzu-Lin Wang received the B.S. and M.S. degrees in computer science and information engineering in 2007 and 2009, respectively, from Aletheia University, Taiwan. She is currently working toward the Ph.D. degree in the Department of Computer Science and Information Engineering at Tamkang University, Taiwan. She won numerous scholarships in Taiwan and has participated in many wireless sensor networking projects. Her current research interests include wireless sensor networks, Ad Hoc wireless networks, mobile/wireless computing, and WiMAX.
Yun-Jung Lu received the Ph.D. degree from Computer Science and Information Engineering of Tamkang University, Taiwan, in 2012. Currently, he is a software engineer in NVIDIA Corporation.