- Open Access
Device discovery for D2D communication in in-band cellular networks using sphere decoder like (SDL) algorithm
© The Author(s). 2018
- Received: 11 September 2017
- Accepted: 18 March 2018
- Published: 3 April 2018
In the fifth generation (5G), it is anticipated that device-to-device (D2D) operation will be locally incorporated as a part without any bounds. In D2D network, multiple devices coexisting is a challenging subject of device discovery. The device discovery is performed under a visually impaired situation such as channel information, location, and the number of devices. In this paper, centralized device discovery is chosen due to power consumption and signaling overhead of the distributed system. A distinctive approach for device discovery in an in-band cellular network, based on the device’s power, is suggested with an efficient technique which enhances the implementation of D2D communication and improves the accomplishment by alleviating the discovery issues. The group of devices forms a lattice structure, and it is positioned in the coverage area. The hypersphere is constructed based on the power knowledge of a discoverer device which helps for accurate and fast device discovery in a lattice structure. Besides, sphere decoder like (SDL) algorithm is applied for quick and precise discovery in the lattice structure. Simulation results present the performance of the proposed QR factorized lattice structure scheme regarding device power, enhanced in the number of discovered devices and controlled signaling overhead.
- Device-to-device (D2D) communication
- Sphere decoder like (SDL) algorithm
- Device discovery
- Cellular network
- End users (EU)
Device-to-device (D2D) communication alludes to direct transmission between two devices without passing through the base station. It has been broadly anticipated to be an essential cornerstone to enhance system performance and bolster new amenities beyond 2020 in future fifth generation (5G) systems . In 5G networks, it is anticipated that controlled D2D communication offers the open door for short-distance communication and local management and permits the isolation of local activity from the global activity, for example, local data offloading. D2D communication evacuates the data traffic heap load on the backhaul and center systems and decreases the vital exertion for managing data traffic at the center system. Due to proximity services, D2D communication is viewed as a promising remedy for enhancing communication accomplishment and system capacity of long-term evolution-advanced (LTE-A) network. The potential enhancements in proximity services that can be given by D2D are not entirely exploited yet. In the 5G network, such confinement does not exist any longer, and it is anticipated that D2D operation in the in-band cellular network will be locally incorporated as a component without any bounds in the 5G network . The in-band cellular network is considered in this research because interference and resource allocation is controlled by the base station or center system .
An important technique in deploying D2D communication is device discovery. Device discovery is characterized into two categories which are distributed discovery and centralized discovery. In the distributed discovery design, optimal resources and legitimate transmission power are apportioned with the consent of base station. However, this strategy involves complex signaling overhead and multifaceted nature of multiple transmitters to be composed . In contrast, centralized device discovery design is adequately controlled by the base station and resources are managed by center system. Besides, the proximity services, for example, commercial announcement, public transport and municipality information, local programs, and impulsive social and corporate contacts infer decreased energy consumption and latency. Therefore, in D2D-enabled centralized networks, multiple devices coexisting is a challenging subject of device discovery for D2D communication to initiate the proximity services. However, latest reviews have concentrated on the D2D communication issues accepting that device discovery issue [5–7] is the vital problem and needs solution.
Discovery signal is designed in , minimizes collisions, and tries to improve the discovery process. A slight portion of resources used for device discovery and discovery signal which can be broadcasted with a minimum delay is proposed in [9, 10]. Distinguishing between different discovery signals is difficult which leads to an increment in power consumption. Compressive sensing method has been suggested in , in which user detection decreases the collision for device discovery. However, when many devices are involved, active congestion will occur, and actual discovery will also be problematic. Device beaconing system is offered in ; it makes a discovery in the background of cellular traffic. If the devices are moving, then beaconing design for high-speed moving devices is much complicated. Neighbour discovery in LTE network, where the distributed orthogonal frequency multiple access (OFDMA) radio resources are used as user identities, is projected in , in which device discovery in high dense areas is not considered. Recommended technique in  uses the base station for discovery in which signaling flow from the base station can be used for discovery. In the large number of devices, the signaling overhead and discovery interference become problematic. Bio-inspired and Firefly algorithm used for direct device discovery are advised in . Due to the computational complexity, probability of misdetection is high. A device discovery scheme based on clustering has been introduced in  for a heterogeneous network, but the deficiency in the work is the sluggish discovery, and needs some techniques to decide clustering. All the previous discussions are guided to design a novel algorithm for device discovery which perform well in all aspects.
We propose a device’s power-based device discovery to enhance the power efficiency and minimize the signaling overhead of typical D2D discovery.
We propose disseminated collision fortitude algorithm and scheme which can take care of the D2D impairment like device power issue happening during the discovery phase.
We evaluate the performance of the proposed algorithm by fusing the suppositions in recent LTE-A specialized reports .
The rest of the paper is organized as follows: Section 2 provides the overview of discovery resources which are used in discovery procedure, while Section 3 consists of the D2D discovery system model. In Section 4, power scheme for device discovery is elaborated, and Section 5 contains the results’ analysis. In the end, the paper is concluded in Section 6.
Each device surveys all RRB’s received power level and selects the RRB which has the most reduced power level . Appropriately, numerous devices situated far away may pick a similar resource. On the other hand, every device randomly chooses RRB resources for discovery signal transmission. We concentrate on a random choice due to the human mobility pattern . There are two scenarios for device discovery that depend on mobility, haphazard walk scenarios, and velocity scenarios in which discovery is computed. Haphazard walk model does not much depend on environment changes, while mobility depends on context and velocity, which might be unknown or partially known or measurable by some models . The sensing-based determination is wasteful when the sensing outcomes are obsolete rapidly, for example, under high-mobility situation. When two or more devices reuse similar discovery resources in the vicinity, a collision may happen because of the asynchronous transmission . Accordingly, these neighboring D2D devices can neither distinguish each other nor be recognized because of the mutual interference.
Appropriately, if various cellular devices have a place with various cells, reuse a common resource in a cell edge, a cellular device signal interferes with the neighboring base station. Then again, in D2D systems, there coexist numerous D2D devices which can be both receiver and transmitter. Under this topology, radiated signals from various transmitting D2D devices will reach proximal D2D device’s receiver. Note that various receivers are possibly presented to endure high interference by numerous D2D links. Accepting the quantity of k D2D devices in D2D systems, the greatest number of D2D links is k(k − 1), which has a polynomial ratio .
The SDL algorithm can reduce the complexity by searching for the closest device among the possible lattice devices that lie within a hypersphere of radius R around the discoverer device x. Mathematically, the SDL algorithm solves the problem as:
The SDL algorithm proceeds similarly to obtain the lattice devices within the hypersphere.
D2D communication isolates the local cellular traffic to the global cellular traffic. Accordingly, device discovery is an underlying strategy in D2D communication. In this research, device’s power-based discovery method is proposed in the centralized cellular network. This clear approach for device discovery enhances the accomplishment by alleviating the discovery issues as fast discovery, minimum signaling overhead, and power consumption. Our proposed methodology is the QR factorized lattice structure of devices in a specific area. Discoverer device creates a hypersphere around it and sends a discovery signal in the hypersphere using sphere decoder like an algorithm. Discoverer device visits all the lattice devices that lie in the hypersphere and finds the closest one to initiate the D2D communication. Using the hypersphere, the designed discovery scheme saves the discovery time and power for searching of unwanted devices. In future, this plan can be implemented on a distributed system and can spare the time by exhaustive search.
The authors would like to express their gratitude to the Ministry of Higher Education (MOHE) in Malaysia and Universiti Teknologi Malaysia (UTM) for providing the financial support for this research through the HICOE grant (R. J130000.7823.4J215). The grant is managed by Research Management Center (RMC) at UTM.
The Ministry of Higher Education (MOHE) in Malaysia and the Universiti Teknologi Malaysia (UTM) are providing the financial support for this research through the HICOE grant.
Availability of data and materials
Mostly, I got the writing material from different journals as presented in the references. A MATLAB tool has been used to simulate my concept.
OH, an assistant professor at NUML, H-9, Islamabad, and a student of PhD in Wireless Communication Center (WCC), Faculty of Electrical Engineering, UTM Johor Baharu, Malaysia under the supervision of associate professor RN, implemented the idea regarding device discovery. YZ, assistant professor at Department of Information and Communication Engineering, Basrah University College of Science and Technology, Basrah, Iraq, helped to implement and write this paper. Overall, this paper is built under the approval and supervision of RN. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
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- M Agiwal, A Roy, N Saxena, "Next generation 5G wireless networks: A comprehensive survey," IEEE Communications Surveys & Tutorials. 18(3), 1617–1655 (2016)Google Scholar
- O Hayat, R Ngah, Y Zahedi, "Cooperative Device-to-Device Discovery Model for Multiuser and OFDMA Network Base Neighbour Discovery in In-Band 5G Cellular Networks," Wireless Personal Communications. 97(3) 4681–4695 (2017)Google Scholar
- M Dohler, T Nakamura, 5G mobile and wireless communications technology. Cambridge University Press, University Printing House, Cambridge, (2016) Google Scholar
- G Fodor, S Roger, N Rajatheva, SB Slimane, T Svensson, P Popovski, et al., An overview of device-to-device communications technology components in METIS. IEEE Access 4, 3288–3299 (2016)View ArticleGoogle Scholar
- K Sharmila, V Mohan, C Ramesh, SP Munda, in Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), 2016 2nd International Conference on. Proximity services based device-to-device framework design for direct discovery (2016), pp. 499–502View ArticleGoogle Scholar
- D Tsolkas, N Passas, L Merakos, Device discovery in LTE networks: a radio access perspective. Comput. Netw. 106, 245–259 (2016)View ArticleGoogle Scholar
- Z Wu, VD Park, J Li, Enabling device to device broadcast for LTE cellular networks. IEEE Journal on Selected Areas in Communications 34, 58–70 (2016)View ArticleGoogle Scholar
- S-Y Lien, C-C Chien, F-M Tseng, T-C Ho, 3GPP device-to-device communications for BeyonD 4G cellular networks. IEEE Commun. Mag. 54, 29–35 (2016)View ArticleGoogle Scholar
- Qualcomm Technologies.Inc, "LTE Direct Always-on Device-to-Device Proximal Discovery," Qualcomm Technologies, 5775 Morehouse Drive San Diego, CA 92121 U.S.A. (2014)Google Scholar
- S Park, S Choi, in 2014 IEEE Global Communications Conference. Expediting D2D discovery by using temporary discovery resource (2014), pp. 4839–4844View ArticleGoogle Scholar
- L Zhang, J Luo, D Guo, Neighbor discovery for wireless networks via compressed sensing. Perform. Eval. 70, 457–471 (2013)View ArticleGoogle Scholar
- K Doppler, CB Ribeiro, J Kneckt, in Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology (Wireless VITAE), 2011 2nd International Conference on. Advances in D2D communications: energy efficient service and device discovery radio (2011), pp. 1–6Google Scholar
- F Baccelli, N Khude, R Laroia, J Li, T Richardson, S Shakkottai, et al., in 2012 Fourth International Conference on Communication Systems and Networks (COMSNETS 2012). On the design of device-to-device autonomous discovery (2012), pp. 1–9Google Scholar
- H Tang, Z Ding, BC Levy, Enabling D2D communications through neighbor discovery in LTE cellular networks. IEEE Trans. Signal Process. 62, 5157–5170 (2014)View ArticleMathSciNetGoogle Scholar
- S-L Chao, H-Y Lee, C-C Chou, H-Y Wei, Bio-inspired proximity discovery and synchronization for D2D communications. IEEE Commun. Lett. 17, 2300–2303 (2013)View ArticleGoogle Scholar
- D Xenakis, L Merakos, M Kountouris, N Passas, C Verikoukis, Distance distributions and proximity estimation given knowledge of the heterogeneous network layout. IEEE Trans. Wirel. Commun. 14, 5498–5512 (2015)View ArticleGoogle Scholar
- CJ Katila, C Buratti, MD Abrignani, R Verdone, Neighbors-aware proportional fair scheduling for future wireless networks with mixed MAC protocols. EURASIP J. Wirel. Commun. Netw. 2017, 93 (2017)View ArticleGoogle Scholar
- J Hong, S Park, S Choi, "Novel power control and collision resolution schemes for device-to-device discovery," Peer-to-Peer networking and applications, 9(5) 913–922 (2016)Google Scholar
- Y Liu, C Liu, NJ Yuan, L Duan, Y Fu, H Xiong, et al., Intelligent bus routing with heterogeneous human mobility patterns. Knowl. Inf. Syst. 50, 383–415 (2017)View ArticleGoogle Scholar
- AH Sayed, A Tarighat, N Khajehnouri, Network-based wireless location: challenges faced in developing techniques for accurate wireless location information. IEEE Signal Process. Mag. 22, 24–40 (2005)View ArticleGoogle Scholar
- M Klügel, W. Kellerer, "Dominant factors for device-to-device occurrence probabilities in cellular networks," Wireless Networks, 1–13 (2017)Google Scholar
- H Sun, M Sheng, X Wang, Y Zhang, Y Shi, Distributed cooperative device-to-device transmissions underlaying cellular networks. Wirel. Netw 21, 1411–1423 (2015)View ArticleGoogle Scholar
- O Hayat, M Qaisrani, M Akbar, in Emerging Technologies (ICET), 2010 6th International Conference on. Sphere decoding in the presence of channel uncertainty, 216–220 (2010)View ArticleGoogle Scholar
- N. Papalexidis, "Distributed Algorithms for Beamforming in Wireless Sensor Networks," DTIC Document, Naval Postgraduate School Monterey, CA, June 2007Google Scholar