Research Activities in 2017 Computer Science Department
Faculty of Computing and Information Technology King Abdul Aziz University
DR. VIJEY THAYANANTHAN
Analysis of Non-Orthogonal Multiple Access (NOMA)
for Future Directions of 5G System
Outline
Basic Multiple Access (MA) and NOMA
Functionalities of 5G MA
Proposed research for enhancing energy
efficiency and security provisioning in 5G system
Current research projects
Future research direction of the 5G systems
Open research problems
Basic Multiple Access (MA) and NOMA
FDMA
Combination of FDMA & TDMA
CDMA
OMA NOMA
Comparison of OFDMA and NOMA/SOMA
OFDMA It is a flexible multiple-access technique that can accommodate many users with widely varying data rates.
NOMA It is recognized as a promising multiple access technique for the next generation cellular communication networks
SOMA In a given time-slot, some of the users are silent and appears orthogonal while some other users transmit
NOMA
General framework: Bit Interleaver, Modulation, Resources, etc.
Types: MUSA, PD-NOMA, SCMA, IDMA etc.
Massive connectivity, Low latency and high spectrum efficiency
NOMA via power domain multiplexing
• Basic NOMA with a SIC Receiver
• NOMA in Massive MIMO Systems
• Network NOMA
NOMA via code domain multiplexing
• Multi-User Shared Access (MUSA) - non-sparse matrix
• Low-Density Spreading CDMA
• Low-Density Spreading OFDMA
• SCMA
Illustration of SOMA transmission
PD-NOMA with SIC receiver in DL
PD-NOMA is more suitable for DL eMBB rather than for UL eMBB and UL mMTC
DL PD-NOMA has the feature of simplicity and many benefits
Spectral efficiency and system throughput, robust performance in high mobility scenarios and good affinity with MIMO technology.
UL PD-NOMA poses many challenges
Scheduling design and power control for eMBB,
Basic NOMA Scheme Transmitter and
Receivers in Downlink
Channel capacity comparison of uplink (left) and downlink (right) in an AWGN [5]
The uplink NOMA is able to achieve the capacity bound, while OMA schemes are in general suboptimal except at point C
Capacity region: NOMA achieves larger multi-user capacity compared to OMA
Functionalities of 5G MA [1]
Enhanced mobile broadband (eMBB) & ultra-reliable and low latency communications (URLLC)
Proposed research for enhancing energy efficiency and security provisioning in 5G system
Aims
• Analyzing the enhancement of energy efficiency (EE) through the understanding of NOMA which is key technique for
Improving 5G system requirements
• Enhancing security provisions using appropriate multiple access technology involved in the 5G systems
Objectives
• Proposing Adaptive NOMA (ANOMA) which uses the efficient adaptive algorithm and design.
• Enhancing EE and security provisions using ANOMA, adaptive LDPC (low density parity check) and massive MIMO with
feedback and manifold techniques
• Analyzing and comparing the expected results of 5G systems
with proposed techniques
Proposed Research: ANOMA
To improve overall performance, efficient adaptive algorithm will be employed with following concepts
Adaptive power control algorithms
Adaptive trellis coding (non binary (NB)-LDPC)
Adaptive modulation (NB-LDPC multi-dimensional modulation schemes)
Proposed Research: ANOMA
Why is ANOMA in 5G developments
Increases the EE because ANOMA reduces the overall hardware complexity
Reduces transmission latency, power consumption and signaling cost
Key idea of the ANOMA is to simplify the design with adaptive algorithms, exploit the power domain for multiple access and serve multiple users at the same time/frequency/code
Optimize the design using manifold techniques which increases the EE because it reduces the rank of the matrix based on massive MIMO-NOMA channel [3, 7]
Increases capacity by several magnitudes
Increases the EE in the network NOMA
Interleave Division Multiple Access (IDMA)
IDMA uses specific interleaves for user segregation
Interleaves generally utilize a less complex iterative multiuser identification concept at the receiver
Interleaver which improves the computational complexity, reduces the bandwidth consumption and the memory requirements of the system.
Orthogonal Interleaver (OI),
Random Interleaver (RI),
Nested Interleaver (NI)
Shifting Interleavers (SI) and
Deterministic Interleaver (DI)
Illustration example of PDMA technical framework in UL
EE in 5G wireless network [4]
Expected results of Downlink MIMO NOMA
systems with manifolds (Pn-manifold)
Enhancement of security provisions using appropriate MA technology
The security performance of the NOMA networks can be improved by
invoking the protected zone and by generating artificial noise at the BS [9-11]
Adopt a protected zone around the BS to establish an eavesdropper exclusion area with the aid of careful channel-ordering of the NOMA users
Artificial noise is generated at the BS for further improving the security of a beamforming-aided system
Secrecy diversity order increases with a number of antennas
SwDeMa: Securing control channels (when the packet is passed to the controller over the secure channel)
NOMA: Securing receivers (analyzing secrecy rate and outage probability of the channel)
Proposed ANOMA for future security in 5G
• New trust models for the future industries (NOMA, ANOMA, etc.)
• New service models for evolving technologies (SwDeMa)
• Dynamic approach of increasing privacy (ANOMA)
• Evolved threat landscape (Infrastructure with all MA)
Analysis of security gap approaches for future 5G
Average secrecy sum rate (SSR) versus the transmit power [9]
With increasing the number of users, SSR increases, the secrecy outage probability decreases and the connection outage probability increases.
Comparisons of NOMA schemes
Summary of performance of different NOMA schemes [1]
Current Research
Adaptive Multiple Access Technology for Enhancing Energy Efficiency in 5G System
Wireless Inter-technology handover between Wi-Fi and 5G based cellular system with SDN
Analytical Cyber Security model based on lightweight Cryptography for IoT
Risk-based decision method for Vehicular ad hoc networks (KACST 2015)
Information Security against the big data breaches in cloud
environment (DSR- 2016)
Conclusions
Analysis of NOMA is investigated basic MIMO and massive MIMO
New model based on NOMA is designed for enhancing EE and security provisions
Uplink and down link NOMA schemes promises to improve the 5G system requirements (increases the capacity, improve the spectral and latency
mechanism) while maintaining the security in
physical layer.
Future research direction of the 5G systems
Energy saving for next generation network (5G+)
• Efficient multiple access technology (An important future direction is to study how MIMO-NOMA transmission can be realized with limited CSI feedback)
• Combination with D2D and V2V multi-hop direct
communication using dynamic graph and Stochastic geometry
• EE optimization for the fading MIMO NOMA systems with statistical channel state information (CSI) at the transmitter.
Security for 5G based M2M communication
• Enhancing secrecy rate
• Dynamic security solutions
• Mobile cyber security
Network NOMA
Precoding solution increases the EE and SE.
To mitigate the inter-cell interference, joint precoding of NOMA users’ signals across neighboring cells can be considered.
The multi-user precoding used for single-cell NOMA maybe not be feasible for the network NOMA scenario
Multi-cell joint precoder is applied only to cell edge users
Network NOMA with 2 cells and 4 users
EE can be achieved through the gains used between the users and base stations.
Here, the single cell NOMA is extended to the network NOMA, with a zero- forcing (ZF) precoding scheme applied to users with weak channel conditions to efficiently mitigate the intercell interference.
Furthermore, the single cell NOMA is extended to network NOMA, with a
Illustration of a two-user NOMA network
Cross-layer optimization is important to maximize the performance of NOMA in practice and meet the diversified demands of 5G, e.g, spectral efficiency, energy efficiency, massive connectivity, and low latency.
Outage probability of the user pair
NOMA in massive MIMO systems
The application of MIMO techniques to NOMA systems is important to enhance the performance gains of NOMA.
A general MIMO-NOMA framework is applicable to both downlink and uplink transmission
A larger diversity gain can be achieved, e.g., for a scenario in which all nodes are equipped with M antennas, a diversity order of M is achievable.
The MIMO-NOMA framework is more general, and also applicable to the case where the users have fewer antennas than the base station.
Downlink MIMO NOMA systems with statistical CSI
An important future direction is to study how MIMO-NOMA transmission can be realized with limited CSI feedback
However, in practice, the perfect CSI is usually hard to obtain in fading channels, the long term power control schemes (LTPC) with statistical CSI is preferred to reduce the CSI feedback overhead.
Expected results of Future NOMA with manifold
20 40 60 80 100 120 140 160 180 200
1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8
Number of feedback bits
Rate
Energy efficiency for MIMO system with PN-manifold
STPC LTPC
Security taxonomy for 5G-based IoT middleware [6]
User Privacy and Data Protection
Big Data Security and Lightweight Approaches
Devices and Communication
Security provisioning in NOMA
We focus on secure beamforming and power allocation design optimization
problem which maximizes sum achievable secrecy rate of central users subject to transmit power constraint at base station and transmission rate requirements at cell-edge users.
Secrecy outage
probability captures the probability of both
reliability and secrecy for one transmission
Generalized Semi-Orthogonal Multiple-Access (GSOMA) for Massive MIMO
The advantage of GSOMA with respect to the conventional TDD is that it schedules more groups, which enhances the aggregate
rate.
Zero forcing receiver (ZF) removes the inter-user interference in
Open Research Problems
Analysis of energy efficiency (EE) with resource allocation under imperfect CSI
• Analysis of EE with NOMA for the perfect CSI because perfect CSI is usually hard to obtain in fading channels
• New network protocols using energy-efficient NOMA
Cyber security solution using software define multiple access (SoDeMa) or SDMA
• Security provisioning in NOMA
• SDN provides simple abstractions to describe the components, the functions they provide, and the protocol to manage the forwarding plane from a remote controller via a secure
channel. All layer security issues using SDN concepts
• Uses of NOMA for dynamic security in next-generation mobile
networks
References
1) Wang, Yingmin, Bin Ren, Shaohui Sun, Shaoli Kang, and Xinwei Yue. "Analysis of non-orthogonal multiple access for 5G." China Communications 13, no.
Supplement2 (2016): 52-66.
2) Liu, Yuanwei, Zhiguo Ding, Maged Elkashlan, and Jinhong Yuan. "Nonorthogonal Multiple Access in Large-Scale Underlay Cognitive Radio Networks." IEEE Transactions on Vehicular Technology 65, no. 12 (2016): 10152-10157
3) Thayananthan, Vijey, and Fahd Bahazaq. "Analytical Model of Energy Saving Approach in Wireless Sensor Network." In Computer Modelling and Simulation (UKSim), 2014 UKSim-AMSS 16th International Conference on, Cambridge University, pp. 505-510. IEEE, 2014.
4) Agiwal, Mamta, Abhishek Roy, and Navrati Saxena. "Next generation 5G wireless networks: A comprehensive survey." IEEE Communications Surveys & Tutorials 18, no. 3 (2016): 1617-1655.
5) Dai, Linglong, Bichai Wang, Yifei Yuan, Shuangfeng Han, I. Chih-Lin, and Zhaocheng Wang. "Non-orthogonal multiple access for 5G: solutions, challenges, opportunities, and future research trends." IEEE Communications Magazine 53, no. 9 (2015): 74-81.
References
6) Tiburski, Ramão Tiago, Leonardo Albernaz Amaral, and Fabiano Hessel. "Security Challenges in 5G-Based IoT Middleware Systems." In Internet of Things (IoT) in 5G Mobile Technologies, pp. 399-418. Springer International Publishing, 2016.
7) J. Chen, X. Chen, W. H. Gerstacker, and D. W. K. Ng, “Resource allocation for a massive mimo relay aided secure communication,” IEEE Transactions on Information Forensics and Security, vol. 11, no. 8, pp. 1700–1711, Aug. 2016.
8) Y. Wu, R. Schober, D. W. K. Ng, C. Xiao, and G. Caire, “Secure massive mimo transmission with an active eavesdropper,” IEEE Trans. Inf. Theory, vol. 62, no. 7, pp. 3880–3900, Jul. 2016.
9) Y. Zhang, H.-M. Wang, Q. Yang, and Z. Ding, “Secrecy sum rate maximization in non-orthogonal multiple access,” IEEE Commun. Lett., vol. 20, no. 5, pp. 930-933, May 2016.
10) Li, Yiqing, Miao Jiang, Qi Zhang, Quanzhong Li, and Jiayin Qin. "Secure Beamforming in Downlink MISO Non-Orthogonal Multiple Access Systems."
IEEE Transactions on Vehicular Technology (2017).
11) Liu, Yuanwei, Zhijin Qin, Maged Elkashlan, Yue Gao, and Lajos Hanzo.
"Enhancing the Physical Layer Security of Non-orthogonal Multiple Access in Large-Scale Networks." arXiv preprint arXiv:1612.03901 (2016).
