Subchannel Assignment for SWIPT-NOMA based HetNet with Imperfect Channel State Information

Energy management of mobile devices is a crucial issue in fifth generation (5G) network due to their limited battery capacity. Simultaneous Wireless Information and Power Transfer (SWIPT) is an emerging technique which allows mobile devices to harvest energy from radio frequency (RF) signals. Moreover, Non-Orthogonal Multiple Access (NOMA) serves multiple users simultaneously using the same subchannel inter-user interference mitigation. By considering the aforementioned issues, in this paper, we propose a subchannel assignment scheme for SWIPT-NOMA based pico base station/femto base station with macro-cellular networks. The energy-efficient subchannel assignment is a probabilistic mixed non-convex optimization problem by considering imperfect channel state information (CSI). To address this problem, many-to-many matching theory is used in the proposal. Numerical results show that the proposed algorithm performs better in terms of numbers of PUs/FUs, average energy efficiency (EE) of the Picocells/Femtocells, in comparison to the orthogonal frequency division access scheme and conventional NOMA.

[1]  Pingzhi Fan,et al.  On the Performance of Non-Orthogonal Multiple Access in 5G Systems with Randomly Deployed Users , 2014, IEEE Signal Processing Letters.

[2]  Derrick Wing Kwan Ng,et al.  Energy-Efficient Resource Allocation in OFDMA Systems with Large Numbers of Base Station Antennas , 2012, IEEE Trans. Wirel. Commun..

[3]  D. Colle,et al.  Worldwide electricity consumption of communication networks. , 2012, Optics express.

[4]  Vijay K. Bhargava,et al.  On Downlink Resource Allocation for SWIPT in Small Cells in a Two-Tier HetNet , 2016, IEEE Transactions on Wireless Communications.

[5]  Derrick Wing Kwan Ng,et al.  Wireless Information and Power Transfer: Energy Efficiency Optimization in OFDMA Systems , 2013, IEEE Transactions on Wireless Communications.

[6]  Zhiguo Ding,et al.  Joint Beamforming and Power-Splitting Control in Downlink Cooperative SWIPT NOMA Systems , 2017, IEEE Transactions on Signal Processing.

[7]  Daniel Benevides da Costa,et al.  Transmit antenna selection schemes for MISO-NOMA cooperative downlink transmissions with hybrid SWIPT protocol , 2017, 2017 IEEE International Conference on Communications (ICC).

[8]  Salama Ikki,et al.  Two-Way Amplify-and-Forward Relaying with Gaussian Imperfect Channel Estimations , 2012, IEEE Communications Letters.

[9]  Victor C. M. Leung,et al.  Joint User Scheduling and Power Allocation Optimization for Energy-Efficient NOMA Systems With Imperfect CSI , 2017, IEEE Journal on Selected Areas in Communications.

[10]  Khaled Ben Letaief,et al.  Throughput and Energy Efficiency Analysis of Small Cell Networks with Multi-Antenna Base Stations , 2013, IEEE Transactions on Wireless Communications.

[11]  Shahid Mumtaz,et al.  Energy-Efficient Stable Matching for Resource Allocation in Energy Harvesting-Based Device-to-Device Communications , 2017, IEEE Access.

[12]  Wei Chen,et al.  Outage Minimization for a Fading Wireless Link With Energy Harvesting Transmitter and Receiver , 2015, IEEE Journal on Selected Areas in Communications.

[13]  Werner Dinkelbach On Nonlinear Fractional Programming , 1967 .

[14]  Khaled Ben Letaief,et al.  Energy efficiency analysis of small cell networks , 2013, 2013 IEEE International Conference on Communications (ICC).

[15]  Derrick Wing Kwan Ng,et al.  Optimal Resource Allocation for Power-Efficient MC-NOMA With Imperfect Channel State Information , 2017, IEEE Transactions on Communications.

[16]  Zhiguo Ding,et al.  The Impact of Power Allocation on Cooperative Non-orthogonal Multiple Access Networks With SWIPT , 2017, IEEE Transactions on Wireless Communications.

[17]  Ying Wang,et al.  Transceiver design for cooperative non-orthogonal multiple access systems with wireless energy transfer , 2016, IET Commun..

[18]  Lav R. Varshney,et al.  Transporting information and energy simultaneously , 2008, 2008 IEEE International Symposium on Information Theory.