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Abstract—The Concept characterized by resource allocation of multi-RAT for a smooth user experience, ultra high reliability, and efficient signaling protocol with 5G effective radio spectrum which have ability to handle extreme device densities and to extend traffic capacity and transmission bandwidths 5G will extends the range of frequencies which includes new spectrum below and above 6GHz. Resource utilization improvement for targeting D2D, M2M communication, and solving issues like disagreements among the routers in the various networks require efficient techniques of spectrum optimization.Index Terms—5G mobile communication, RAT, Protocols, Computer Architecture, Resource allocation, Radio spectrum.IntroductionDespite of the availability of advanced network architecture and resource allocation mechanism, Service Providers (MSPs) are facing challenges and difficulties to cope up with tremendous increase in mobile applications and user requirements. Physical resource allocation, spectrum optimization and efficient network architecture are some of the major issues need to be targeted in 5G era. The objective of this research proposal is to propose “Efficient multi objective spectrum allocation optimization technique for heterogeneous multi-RAT’s 5G targeting indoor Communication” to pave the way for best possible method to deliver QoS and QoE. Existing literature target several network optimization techniques for previous wireless generations (1G/2G/3G/4G), which traditionally operates at lower side of frequency spectrum. In order to further extend traffic capacity and transmission bandwidths 5G will extend the range of frequencies used. This includes new spectrum below 6GHz, as well as spectrum in higher frequency bands above 6GHz. 5G is still waiting for permanent spectrum allocation for higher frequency bands therefore; at this stage entire frequency spectrum up to 100 GHz is being considered. Lower frequencies will be backbone of the 5G for ubiquitous connectivity and higher frequency bands are supposed to provide additional system capacity by employing small cell architecture at very wide bandwidths in dense networks 1.This architecture allow the improved system efficiency by employing small cells which supports less power requirements, large bandwidth availability, high spectral efficiency and throughput but due to small cell size, high inter cell interference and unnecessary handover may occur results in system performance degradation. Moreover, Dense Network (DenseNet) with heterogeneous multi RAT’s causes serious issues like interference in RAN, Poor backhaul efficiency and high signaling for traffic leads to degraded system performance. Therefore, understanding the best possible optimization issues at higher frequencies is key challenge to be targeted by addressing the whole 5G architecture. In 5G, for smooth operation of network event the role of SDN (Software Defined Network) cannot be ignored. Efficient and Effective SDN architecture is paramount requirement for 5G system to control cross layer communication. The ideal goal is to be able to communicate at any desirable frequency, bandwidth, modulation and data rate by simply loading the appropriate Software in reuse manner. This method is reasonably viable to up to UHF (Ultra High Frequency) range but becomes complex above UHF (which are the areas of interest in 5G) and inclusion of network optimisation techniques in SDN architecture not only support SDN but will play significant role to handle entire 5G system efficiently and effectively 2. Additionally the proposed research address the following issues in one or other ways, i.e effective implementation of different network protocols, relationship of suppliers and consumer demand , QoS, QoE, frequency spectrum re-utilization rate and security by taking into account multi-technology coverage targets, traffic sharing and offloading between layers, as well as installation and implementation constraints etc.literature review 5G (5th generation mobile networks or 5th generation wireless systems) denotes the next major phase of mobile telecommunications standards beyond the current 4G.Unlike previous four generation (1G/2G/3G and 4G), 5G is targeting very high data rate, low energy consumption, ultra high reliability, ability to handle extreme device densities, efficient signaling protocol, unprecedented numbers of antennas with high flexibility for seamless integration.  Proposed 5G spectrum along with LTE and WiFi is supposed to provide ubiquitous network coverage to support applications like 3D TV, HDTV, VoIP, mobile gaming, Virtual Reality, Augmented Reality, Autonomous driving/Connected cars, Wireless cloud-based office/Multi-person videoconferencing, Machine-to-machine connectivity (M2M) communication etc. Moreover, with requirement of high bandwidth and cost efficiency, 5G requires latency of ~1mS, which is considered to be one of the biggest technical challenges 3. The integral components of 5G technology will include massive multiple input and multiple output (MIMO), cooperative communications and network coding, full duplex (FD), device-to-device (D2D) communications, millimeter wave communications, automated network organization, cognitive radio (CR), and green communications. The proposed network architecture of 5G considers multiple base stations (BSs) with different transmitted power levels. Furthermore, it will integrate multi radio approach (eg. Picocell, microcell, femtocell, Wi-Fi hotspots etc) to be used in heterogeneous RATs (i.e GSM, HSPA, LTE, LTE-A, WiFi etc). In heterogeneous multi-RATs small cells, intercell interference is one of the biggest challenges and especially problematic with unplanned deployment of small cells, where the operators have little or no control of the location of the small cells. Additionally, the concurrent operation of small cells and traditional macro cells will produce irregular shaped cell sizes, and hence inter-tier interference develop, which will require advanced power control and resource allocation 4. Therefore, to improve resource utilization in heterogeneous multi RATs flexible spectrum management is used 5. This technique allows network operators to have freedom to flexibly allocate spectrum to the RATs at various frequency bands. Flexible Spectrum allocation has several different forms for example Spectrum reframing and opportunistic spectrum access. In addition, authorized-shared access (ASA) and licensed shared access (LSA) techniques can be used in dynamic sharing of spectrum. Collective use of spectrum is another approach which allows spectrum to be used by more than one user simultaneously without requiring a license. These solutions would be particularly useful in short-range devices, e.g. D2D or M2M applications 6. Little or no literature exist which evaluate the performance between different multi RATs in terms of throughput and QoS analysis. Prior work has targeted single- RAT cellular network, which cannot give guarantee of good system performance in heterogeneous multi-RAT system 7. On the other hand, Effective bandwidth and power allocation method in heterogeneous multi RAT system is imperative issue. To address this issue, researches proposed different approaches like rate allocation in parallel transmission 8-9 and Joint radio resource allocation for maximising the capacity 10. The prior approaches are effective in one or other ways and can be implemented in multi-RAT system after careful study and analysis experiments based on user QoE. Sound Efforts are needed to evaluate and maximise QoE based on spectrum allocation in 5G.  Network performance in heterogeneous multi RAT’s basically depends upon multi-standard base station, multi-standard controller or SDN. The key responsibilities for successful deployment of multi RATs are inter-RAT handover optimization, inter-RAT multi-cell joint camping and congestion management. One of the approaches of Spectrum optimization can be by done assigning UE to the cell, and monitors the KPI (Key Performance Indicators) of entire network and users QoE. Another is addition of adaptability by cognition to system architecture so system updated itself by own to target the strategies of load balancing and congestion control. Earlier Generation utilises centralised approaches to manage handovers. In case of 5G, centralised handover is not possible due to several factors. Better performances can be obtained by exploiting advantages of both decentralised and centralised RAT selection approach, where every BS executes a handover based on the basis of local information. This approach also helps to implement ultra-lean system design, as one of the objectives of 5G implementations. In addition, IEEE 802.21 protocol does not assure good performance in case of high mobility and does not provide to the upper layers all the facilities necessary for efficiently managing vertical handover 11. Here SDN (Software Defined networking) approach plays important role to efficiently distribute system resources. The main system requirements to implement SDN architecture are i) Portable design with reprogramability, reconfigurability and upgradability ii) Scalability, modularity and hierarchical to maintain system security iii) Energy efficient without increasing system cost iv) interoperability and multichannel support.Network optimisation is paramount requirement for SDN architecture development in terms of spectrum efficiency because to achieve targets like ultra-lean system design, decouple network control and data plane, introduction of new services in upgrade require sufficient information and optimisation in the form of network intelligence which can improve user QoE to next level. It is desirable that operator can dynamically configure and manage resources. Open Networking Foundation (ONF) proposed communication protocol called OpenFlow which supports both centralized and distributed approaches for architecture and the OpenFlow is a currently representative protocol of SDN 12. Some of the famous attempts of SDN implementations are, FP7 CROWD, Cloud Mac, Soft RAN, Mobile flow and FP7 mobile cloud networking projects.In 5G architectural development, introduction of SDN at carrier level security is an open problem and no unified approach has been reported yet. On the other hand, multi-RAT multi-layer heterogeneous network deployment in wireless architecture with SDN compatibility is in developing shape, targeting the architectural design issues for example how to replace radio hardware and devices like filter, modulators, demodulator and receiver into fast processing DSP algorithms to integrate RAT’s (WiFi, GSM, WiMax etc.) in same equipment. To target above mentioned issues a unified optimisation approach is mandatory to achieve better spectrum efficiency. Cognitive approach can also be used, which can effectively reduce bandwidth requirements of control layer 13. A fundamental challenge with SDN is how to achieve sufficient computational capacity, in particular for processing wide-band high bit rate waveforms, within acceptable size, latency and acceptable power consumption with flexibility. This is particularly challenging for small handheld units. The power consumption must be below certain limits to keep the battery discharge time within acceptable limits, and with the smallest handheld units. Reconfiguration will need to be done in real-time without disturbing any operation of the radio system. Multiple-Input / Multiple Output (MIMO) technology have emerged in the last decade as a powerful means of increasing the throughput and system performance of wireless communication systems. This technique utilizes very high number of antennas to multiplex messages for very high number of devices by focusing the radiated energy towards the intended directions and minimising intracellular interference. “Beam forming requires large amount of channel information which reduces the spectrum efficiency”. Similarly, at frequencies below 10 GHz, system based on FDD is deployed which is not supported by MIMO. However, TDD gives satisfactory results in MIMO implementations. In future, MIMO expects effective Channel Modelling/Estimation, fast processing algorithm and improved method to get away from pilot contamination. Therefore, proposed research will play is crucial part for spectrum optimisation based on MIMO in indoor networks.   Orthogonal frequency division multiplexing is well known applied waveform design principle.  4G (LTE & LTE-A) and IEEE 802.11 (WiFi) is using OFDM to carry data. OFDM uses rectangular window in time domain which results sinc shaped subcarriers in frequency domain, therefore complex filtering techniques are required to remove these redundant spectrum bands, which introduce inter cell interference. Due to stringent oscillator requirement, LTE and LTE-A successfully integrated OFDM, but in case of 5G, to target IoT, M2M or D2D communication, the strict oscillator requirements are very difficult to full fill at low cost. Therefore, FBMC (Filter Bank Multi Carrier), OQAM, Single carrier modulation (To target frequency range above 10 GHz), FTN (Faster than Nyquist) and OTFS (Orthogonal Time and Frequency Space) are the possible contenders to replace OFDM 14. The proposed research will target this issue as well.Proposed Potential Solutions for efficient spectrum utilization in 5GTo support simultaneous association of multiple BSs by introducing efficient methods for cooperation and coordination among multiple tiers, spectrum efficiency can be improved, for example UE should be allowed to have dual connectivity by simultaneously connecting to the macrocell and the small cell for uplink and downlink communications or vice versa 15. By implementing effective RAT selection in Multi RAT systems using graph theory approach for example, if the number of user connected equipment’s has to be maximised Hopkroft-Karp algorithm can be used otherwise efficient use of ILP (Intelligent Linear Programming) can be used 16. Also by introduction of multi-objective optimization techniques like NSGA-II, SPEA-II and multi-objective ant colony optimization (MOACO) into the system 17 may leads to high flexibility in RAT. Inclusion of Bayesian Monte Carlo methods could offer a novel paradigm for tackling spectrum issues 18. To increase data rates and computations requirements much more aggressive modulations techniques can be deployed for example QAM-64, complex OFDM, FBMC, OTFS etc. Efficient MIMO utilisation of beam forming is necessary as it require large amount of channel information which needs to take care. Therefore, by knowledge of optimisation of above mentioned issues in system with respect to spectrum leads to efficient and effective 5G architecture deployment in multi-RAT 5G communications.ConclusionAbove mentioned description from existing literature highlight the relevant issues of 5G and emphasise the importance of concurrent efficient operation of all the techniques to achieve efficient and effective spectrum utilisation. For effective spectrum utilisation for multi RAT heterogeneous networks, the role of MIMO, Carrier frequency, SDN architecture, RAT selection approaches, throughput vs QoS, and latency has to be taken into account with utmost care.  Resource utilisation improvement for targeting D2D, M2M communication, and solving issues like disagreements among the routers in the various networks require efficient techniques of spectrum optimization.Therefore, to serve the objective of spectrum optimisation in RAT’s and SDN architecture, the proposed research is going to play significant role.ReferencesDahlman, Erik, et al. “5G radio access.” Ericsson Review 6 (2014): 2-7.Akyildiz I F, Lee W Y, Vuran M C, et al. Next generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Comput Netw, 2006, 50: 2127–2159Andrews, Jeffrey G., et al. “What will 5G be?.” Selected Areas in Communications, IEEE Journal on 32.6 (2014): 1065-1082.Galinina, Olga, et al. “5G Multi-RAT LTE-WiFi Ultra-Dense Small Cells: Performance Dynamics, Architecture, and Trends.” (2015).V. Sridhar, T. Casey, and H. Hammainen, “Flexible spectrum management for mobile broadband services: How does it vary across advanced and emerging markets?” Telecommun. Policy, vol. 37, no. 2–3, pp. 178–191, 2013. Chin, Woon Hau, Zhong Fan, and Robert Haines. “Emerging technologies and research challenges for 5G wireless networks.” Wireless Communications, IEEE 21.2 (2014): 106-112.Ding, Xu, et al. “Coexisting Coverage and Throughput of Multi-RAT Wireless Networks with Unlicensed Band Access.” arXiv preprint arXiv:1505.04944(2015).X. Zhu, P. Agrawal and J. P. Singh, “Distributed Rate Allocation Policies for Multihomed Video Streaming Over Heterogeneous Access Networks,” IEEE Transactions on Multimedia, vol. 11, no. 4, pp. 752-764, June 2009.H. Chen, X. Ding and Z. Wang, “A Rate Allocation Scheme for Multi-User over Heterogeneous Wireless Access Networks,” in proc. of IEEE Vehicular Technology Conference Fall (VTC Fall), pp. 1-5, Sept. 2010.Y. Choi, H. Kim and S. Han, “Joint Resource Allocation for Parallel Multi-Radio Access in Heterogeneous Wireless Networks,” in proc. of IEEE Transactions on Wireless Communications, vol. 9, pp. 3324-3329, Nov.2010.R. Qureshi, A. Dadej, Qiang Fu,”Issues in 802.21 mobile node controlled handovers,” Telecommunication Networks and Applications Conference, 2007. ATNAC 2007., vol., no., pp.53,57, 2-5 Dec, 2007.N. Cvijetic, A. Tanaka, P. N. Ji, K. Sethuraman, S. Murakami, and T. Wang, ”SDN and OpenFlow for dynamic flex-grid optical access and aggregation networks,” J. Lightw. Technol., vol. 32, no. 4, pp. 864–870, Feb. 15, 2014.Cho, Hsin-Hung, et al. “Integration of SDR and SDN for 5G.” Access, IEEE 2 (2014): 1196-1204.Schaich, Frank, and Thorsten Wild. “Waveform contenders for 5G—OFDM vs. FBMC vs. UFMC.” Communications, Control and Signal Processing (ISCCSP), 2014 6th International Symposium on. IEEE, 2014.D. Astely, E. Dahlman, G. Fodor, S. Parkvall, and J. Sachs, “LTE release 12 and beyond accepted from open call,” IEEE Communications Magazine, vol. 51, no. 7, pp. 154–160, 2013.Zakrzewska, Anna. 4G and Beyond-Exploiting Heterogeneity in Mobile Networks. Networks Technologies and Service Platforms, DTU Fotonik, 2013.Berre, Matthieu Le, Faicel Hnaien, and Hichem Snoussi. “Multi-objective optimization in wireless sensors networks.” Microelectronics (ICM), 2011 International Conference on. IEEE, 2011Wang, Xiaodong, Rong Chen, and Jun S. Liu. “Monte Carlo Bayesian signal processing for wireless communications.” Journal of VLSI signal processing systems for signal, image and video technology 30.1-3 (2002): 89-10 

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