Assessment of Dynamic Spectrum Allocation Technique in Heterogeneous Network

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International Journal of Future Generation Communication and Networking
Vol.10, No.3 (2017), pp.41-48
http://dx.doi.org/10.14257/ijfgcn.2017.10.3.05
ISSN: 2233-7857 IJFGCN
Copyright ⓒ 2017 SERSC
Assessment of Dynamic Spectrum Allocation Technique in
Heterogeneous Network
Ahmad Fadzil Ismail1, Mohammad Kamrul Hasan1, N. I. Othman1 and Wahidah
Hashim2
Department Electrical and Computer Engineering
Faculty of Engineering
International Islamic University Malaysia
College of Computer Science and Information Technology, Universiti Tenega
Nasional (UNITEN), Malaysia
nurzati.iwani90@yahoo.com, af_ismail@iium.edu.my, hasankamrul@ieee.org,
wahidah@uniten.edu.my
Abstract
Mobile devices are becoming the priority of access to a growing trend of online
services. As services use higher quality images & video, an increase of wireless network
capacity is required. In this case, spectrum is a way to go. Even though capacity is
important, there are other factors as well, for example, coverage, flexibility and
resilience. Dynamic spectrum access technology allows higher transmission power
according to location & safe sharing with licensed users (LU). Dynamic spectrum
allocation (DSA) technique enhances the spectrum efficiency for the users in
Heterogeneous Network. This paper explains about the findings that are observed by two
different researches that are related to our research title. The first paper is about the
basic OFDM structure using GNU Radio software and implemented using USRP
hardware. The second research is about the implementation of Dynamic Resource
Allocation for LTE using GNU Radio. The first research explained about the advantages
and disadvantages of OFDM configuration. The second research explained more about
the implementation of Dynamic Resource Allocation in the uplink and downlink
configuration, and are tested using three algorithms; Max-sum, max-min and max-
product. All the results are obtained from GNU Radio. However, the results are not
implemented using USRP because of the short amount of time. Based on these two
researches, we identified the advantages and disadvantages of the proposed designs and
develop our own design to mitigate the cross-tier interference in multi-tiers HetNets.
Keywords: We would like to encourage you to list your keywords in this section
1. Introduction
Latest advancements in 4th generation cellular technology; the Long Term Evolution
/Advanced (LTE/LTE-A) are mainly directed towards the pursuit of increased throughput.
As it can be observed, both frequency and time domains had been overworked to augment
this Orthogonal Frequency Division Multiplexing (OFDM) system's capacity. There are
many mitigation methods that have been discussed to mitigate the interference that exists
in communication networks. Frequency Partitioning Method is one of them. It uses the
cochannel access approach in femtocell networks and partitions the whole frequency band
into several non-overlapping parts and allocate different parts to the macrocell and
femtocells in different regions [1]. Intelligent Scheduling is also one of the mitigation
methods for co-tier interference that exists between LTE femtocells. This method helps to
reduce the Cross-tier interference that maximizes the cell total throughput. It also gives

International Journal of Future Generation Communication and Networking
Vol.10, No.3 (2017)
42 Copyright ⓒ 2017 SERSC
better SINR ratio that is useful to implement in LTE network [2]. Besides that, Resource
Partitioning Technique proposed muting of tiny cells. It is said to offer better quality of
service to the macrocell users, eliminating macrocell coverage holes, which are present in
the regions between neighboring picocells. The proposed function adds fairness to the
system by offering corresponding bitrates to the users [3]. Spectrum Efficiency and
Management of Cross-Tier Interference in Femtocell Network has additionally been
broke down in [4]. It presents Dynamic cross-level impedance coordination component
(D-CTIC) and is utilized just when the meddled client hardware can't guarantee its
Quality of administration requirement. Consequently, higher cell spectrum effectiveness
can be accomplished by enduring a specific level of cross-level interference. In view of
the perceptions made in the specified past papers, the interference mitigation strategies
disregard the usage of Dynamic Spectrum Allocation. In view of [5], adjoining
designation still uses neighboring squares of range allotted to various systems, and are
isolated by a reasonable monitor band. This plan permits the range dividing to change to
the detriment of the frightfully contiguous other framework's range. The improvement of
element frequency allotment strategies that consider the application necessities, nearness
of different gadgets in the area and connection picks up between the transmit-get sets [6].
Examine in [7] planned an incorporated DSA plan to upgrade the range usage and boost
the benefit of administrators for agreeable remote systems. Other than that, DSA are
likewise utilized for other sort of systems too. For instance, in [8-9], they presented the
DSA calculation for psychological systems by concentrate the specialized practicality of
DSA in a multi-innovation and multi-administrator perspective.
.
2. OFDM Configuration
All The study conducted in [10] showed the step by step instructions on how to
construct the basic OFDM configuration using GNU Radio software. GNU Radio is a
software development toolkit that provides signal processing blocks to implement
software-defined radios and signal-processing systems [11]. The blocks for the
transmission and reception flow graphs are as shown in Figures 1, 2, 3 and 4 below [11]:
Figure 1. Mapping the Data in Packets for Transmission

International Journal of Future Generation Communication and Networking
Vol.10, No.3 (2017)
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Figure 2. Implementing OFDM and Transmission
Reception flow graph:
Figure 3. Reception and Equalization through Frames

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44 Copyright ⓒ 2017 SERSC
Figure 4. Fetching Data Back after Demodulation
3. DSA System Model
By studying the research done in [12], Dynamic Resource Allocation is implemented
for LTE System Using GNU Radio. It studied about the vital issues in wireless
communication and dynamic resource allocation for OFDM based systems. It also
implements a simplified signal processing structure for an LTE communication system
using GNU Radio. Our design will be made to mitigate the cross tier interference that
exists at HetNets. This research is also implemented using USRP hardware. The
considered interference scenario is presented in Figure 5.
Figure 5. Interference Scenario in Heterogeneous Network [2]
Our design will consist of two base stations and several user devices. In our
flow graph, we will construct new blocks that will represent different base stations
and user devices. From this, cross tier interference will occur, and by
implementing dynamic spectrum allocation scheme, the interference will then be
mitigated [13]. We will also add some additional noise to determine the best way
to mitigate the interference caused by the HetNets and also the noise. The result of
the project will be seen and analyzed using GNU Radio. Lastly, we will
implement the design using USRP to ascertain that our design is suitable for
communication technologies in real life. This research comprised of three typical
dynamic resource allocation algorithms; Max-sum, Max-min and Nash Bargaining
Game, and Water filling algorithm. The communication logic of user device &
base station is the establishment of communication using distinctive three-way
model and the packet allocation and identification. The flow graph of DSA is
shown in Figure6 and Figure7 [10].

International Journal of Future Generation Communication and Networking
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Figure 6. OFDM Modulator Flow Diagram Constructed Iin GNU Radio [10]
Figure 7. The Flow Graph of OFDM Demodulator Built by GNU Radio [10]
4. Result and Discussion
The figure shows the signal received from the flow graph of the Transmission
blocks without additional noise. Based on the results, we can know the advantages
and disadvantages of OFDM.

International Journal of Future Generation Communication and Networking
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Figure 9. OFDM Signal from [10]
The advantages of OFDM include reduced ISI because of the presence of
Cyclic Prefix block. It eliminates ISI in single-path channels and minimizes it in
multi-path channels. Spectrum use is additionally one of the upsides of OFDM it
permits simple channel estimation and leveling, through known settled images
(pilot images). It is only backings parcel exchanging progressively [14]. One of
the prevalent methods is MIMO frameworks which can be fundamental to
alleviate impedance in OFDM. Another procedure is versatile regulation and
element control portion which additionally can be actualized utilizing GNU radio
to moderate obstruction as a part of OFDM framework. The primary issue of
OFDM framework is the affected ability to synchronization blunders and
especially with recurrence synchronization issues and everything can turn out
severely. To be sure, demodulation of an OFDM motion with a balance in the
recurrence can prompt to a high piece blunder rate. We could watch this impact
plainly while accepting the flag through an RTL-SDR dongle when little
recurrence blunders prompt to parcel drop. Therefore, the pieces actualized
keeping in mind the end goal to portray OFDM framework.
5. Conclusion
In conclusion, we have discovered several mitigation techniques that can help in
reducing or minimizing the interference occurrence in communication networks.
After observing the previous papers, there is no doubt that Dynamic Spectrum
Allocation is one of the best techniques for interference mitigation in cellular
networks. Based on the two studies that we have closely examined, we now know
how to construct the basic OFDM configuration and implementation of Dynamic
Spectrum Allocation by using a software defined radio called GNU Radio. The
future recommendation of this study is to implement the extended level of the
proposed DSA implementation in OFDMA system by using USRP based testbed.

International Journal of Future Generation Communication and Networking
Vol.10, No.3 (2017)
Copyright ⓒ 2017 SERSC 47
References
[1] Chen, D., Jiang, T., & Zhang, Z. (2015). Frequency partitioning methods to mitigate cross-tier
interference in two-tier femtocell networks. IEEE Transactions on Vehicular Technology, 64(5), 1793-
1805.
[2] Hasan, M. K., Ismail, A. F., Abdalla, A. H., Abdullah, K., Ramli, H. A. M., Islam, S., & Badron, K.
(2014, November). Self-organizing joint sensing and power allocation scheme (SJSPA) to coordinate
cross-tier interference for LTE-A heterogeneous networks. In Telecommunication Technologies (ISTT),
2014 IEEE 2nd International Symposium on (pp. 11-16). IEEE.
[3] Singh, R., Mishra, S., & Murthy, C. S. R. (2014, May). A multi-tier cooperative resource partitioning
technique for interference mitigation in heterogeneous cellular networks. In Modeling and Optimization
in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 2014 12th International Symposium on (pp. 181-
187). IEEE.
[4] Zhou, F., Wang, B., Wang, W., Zhang, Y., Lei, M., & Jiang, L. (2013, September). Analysis of Spectral
Efficiency and Management of Cross-Tier Interference in Femtocell Network. In Vehicular Technology
Conference (VTC Fall), 2013 IEEE 78th (pp. 1-6). IEEE.
[5] Kim, S. J., Kim, E. C., Park, S., & Kim, J. Y. (2009, September). Dynamic spectrum allocation with
variable bandwidth for cognitive radio systems. In Communications and Information Technology, 2009.
ISCIT 2009. 9th International Symposium on (pp. 106-109). IEEE.
[6] Acharya, J., & Yates, R. D. (2009). Dynamic spectrum allocation for uplink users with heterogeneous
utilities. IEEE Transactions on Wireless Communications, 8(3), 1405-1413.
[7] Hasan, M. K., Ismail, A. F., Islam, S., Hashim, W., & Pandey, B. Dynamic Spectrum Allocation Scheme
for Heterogeneous Network. Wireless Personal Communications, 1-17. doi:10.1007/s11277-016-3893-5
[8] Sharma, P., & Tapaswi, S. (2009). Dynamic spectrum allocation technique in cognitive radio networks.
In 2009 First UK-India International Workshop on Cognitive Wireless Systems (UKIWCWS).
[9] Hasan, M. K., Ismail, A. F., Islam, S., & Hashim, W. (2016). Self-organized HGBBDSA approach for
the power allocation in OFDMA-based heterogeneous network. International Journal of Hybrid
Information Technology, 9(7), 419-428.
[10] Kshitiz Bansal and Vishrant Tripathi. “OFDM Tranmission and Reception of Packets using GNU Radio
and USRP”. Electrical Engineering, IIT, Bombay
[11] Bloessl, B., Segata, M., Sommer, C., & Dressler, F. (2013, August). An IEEE 802.11 a/g/p OFDM
Receiver for GNU Radio. In Proceedings of the second workshop on Software radio implementation
forum (pp. 9-16). ACM.
[12] Cheng, H. (2014). Implementation of Dynamic Resource Allocation for LTE System Using GNU Radio
(Doctoral dissertation, George Mason University).
[13] Ashish Bagwari, GS Tomar, Shekhar Verma "Cooperative Spectrum sensing based on Two-stage
detectors with Multiple Energy detectors and Adaptive Double-Threshold in Cognitive Radio Networks"
IEEE Canadian Journal of Electrical and Computer Engg,, Vol.36, No.4. pp 172-180, Fall 2013.
[14] Ashish Bagwari, GS Tomar, “Enriched the Spectrum Sensing Performance of Estimated SNR Based
Detector in Cognitive Radio Networks”, International Journal of Hybrid Information Technology Vol.8,
No.9, pp.143-156, 2015.

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48 Copyright ⓒ 2017 SERSC