- Open Access
Interference cancellation for non-orthogonal multiple access used in future wireless mobile networks
© The Author(s). 2016
- Received: 30 June 2016
- Accepted: 15 September 2016
- Published: 27 September 2016
Non-orthogonal multiple access (NOMA) is suggested as a radio access candidate for future wireless mobile networks. It utilizes the power domain for user multiplexing on the transmitter side and adopts a successive interference cancellation (SIC) as the baseline receiver scheme, considering the expected mobile device evolution in the near future. However, recent research focuses more on the performance evaluation of NOMA in context of assuming the perfect SIC at receiver side. In order to clarify the performance gap between the perfect and the practical SIC in NOMA schemes, and to examine the possibility of applying NOMA with practical SIC, this paper investigates the performance of NOMA applying multi-input multi-output (MIMO) technology with zero-forcing (ZF) and minimum mean square error (MMSE) SIC schemes. We propose an analysis on error effects of the practical SIC schemes for NOMA and in addition propose an interference-predicted minimum mean square error (IPMMSE) IC by modifying the MMSE weight factor using interference signals. According to the IPMMSE IC and analysis of IC error effect, we further suggest the remaining interference-predicted MMSE (RIPMMSE) IC to cancel the remaining interference. The simulation results show that by considering practical IC schemes, the bit error rate (BER) is degraded compared with conventional orthogonal multiple access (OMA). This validates that the proposed IC schemes, which can predict the interference signals, provide better performance compared to NOMA with conventional ZF and MMSE IC schemes.
- Non-orthogonal multiple access
- Interference cancellation
- Minimum mean square error
In the fourth-generation (4G) mobile communication systems, such as Long-Term Evolution (LTE), WiMAX, LTE-Advanced, and V2V networks [1–3], orthogonal access based on orthogonal frequency division multiple access (OFDMA) or single carrier-frequency division multiple access (SC-FDMA) was adopted. Orthogonal access is a reasonable choice for achieving good system throughput with a simplified receiver design. However, due to the vastly increased need for high-volume services, such as image transfer, video streaming, and cloud-based services, a new mobile communications system with further enhancement of system throughput is required for the next-generation (5G) mobile communication systems. In order to fulfill such requirements, non-orthogonal multiple access (NOMA) with a successive interference cancellation (SIC) receiver in downlink was presented as one of several promising candidate radio access technologies [4–10]. For downlink NOMA, non-orthogonality is achieved by introducing the power domain, either in time/frequency/code domains, for user multiplexing. User de-multiplexing is obtained through the allocation of a large power difference between the users on the transmitter side and the application of SIC on the receiver side. In this case, everyone can use the overall transmission bandwidth to get higher spectrum efficiency, and better user fairness can be achieved, compared with conventional orthogonal multiple access (OMA), by assigning greater power to the users under poor channel conditions. Furthermore, NOMA is suitable for the situations of massive connectivity, because it can support more simultaneous connections.
NOMA is a candidate technology for further performance enhancements of LTE and LTE-Advanced, and both the concept and system performance are discussed and analyzed, considering the perfect SIC on the receiver side [11–16]. Therefore, in this paper, we exploit the system performance based on the link-level simulation (LLS) of NOMA with practical SIC schemes (i.e., zero-forcing [ZF] and MMSE SIC).
We analyzed the effect of the error that is caused by the interference cancellation (IC) by considering practical SIC schemes for NOMA in. Based on the analysis, we propose a novel interference-predicted minimum mean square error (IPMMSE) IC scheme for NOMA downlink, which is based on MMSE criteria from prediction about interference signals. Moreover, based on the IPMMSE IC and the analysis of the IC error effect, we propose the remaining interference-predicted MMSE (RIPMMSE) IC to cancel the remaining interference, which can further improve the system performance. The link-level evaluation is provided, and the simulation results show that by using the proposed IC schemes, the bit error rate (BER) performance is enhanced, compared with conventional IC schemes for NOMA.
The rest of the paper is organized as follows. Section 2 introduces the basics of NOMA and describes a NOMA system model with ZF and MMSE SIC schemes by using multi-input multi-output (MIMO) technology . In Section 3, we compare the conventional multiple access (MA) and NOMA with the practical IC scheme and analyze the IC error effect for NOMA. Based on IC error analysis, the proposed IPMMSE IC and RIPMMSE IC schemes are described in Section 4. Finally, we conclude this paper in Section 5.
2.1 NOMA basics
2.2 NOMA-MIMO with practical SIC schemes
Sets of achievable rates for NOMA have been found by Cover , and the proof for the optimality of the sets of achievable rates for additive white Gaussian noise broadcast channels was given by Bergmans . The capacity region of the uplink fading channel with receiver channel state information (CSI) was derived by Gallager , where he also showed that CDMA-type systems are inherently capable of higher rates than systems such as slow frequency hopping that maintain orthogonality between users. In , Tse gave a conclusion that NOMA is strictly better than OMA (except for the two corner points where only one user is being communicated to) in terms of sum rate, i.e., for any rate pair achieved by OMA, there is a power split for which NOMA can achieve rate pairs that are strictly larger. However, this conclusion is intended for single antenna systems and Tse did not give a proof for this conclusion. Here, one should be noted that the capacity gain of NOMA over OMA is achieved at the cost of more decoding complexity at the receivers for NOMA. The application of multiple-input multiple-output (MIMO) technologies to NOMA is important since the use of MIMO provides additional degrees of freedom for further performance improvement. The transceiver design for a special case of MIMO-NOMA downlink transmission, in which each user has a single antenna and the base station has multiple antennas, has been investigated in  and . In , a multiple-antenna base station used the NOMA approach to serve two multiple-antenna users simultaneously, where the problem of throughput maximization was formulated and two algorithms were proposed to solve the optimization problem. In many practical scenarios, it is preferable to serve as many users as possible in order to reduce user latency and improve user fairness. Following this rationale, in , users were grouped into small-size clusters, where NOMA was implemented for the users within one cluster and MIMO detection was used to cancel inter-cluster interference. Different from conventional works, this paper focuses on the NOMA-MIMO with practical SIC instead of using perfect SIC assumption in conventional studies.
respectively. Since NOMA allows UEs to share the same resources, and differentiates UE by power, IC is performed for UE with lower power to cancel the inter-user interference. Because UE2 is a far user with greater power, the element H 21 x 2 is cancelled by the IC from y 1, whereas y 2 can be demodulated directly without IC.
After the canceling the interference signal with high power, UE1 can detect the desired information, s 1, from the updated received signal.
3.1 Comparison between conventional MA and NOMA with practical IC scheme
Subcarriers per resource block
Symbols per packet
Number of bits per packet (n bit/packet)
Power for NOMA (case_1)
p 1 = 0.2, p 2 = 0.8
Power for without NOMA (case_2)
p 1 = 0.8, p 2 = 0.2
From the simulation results shown in Fig. 4, we determine that in NOMA, UE2 can detect information with greater power than interference from UE1. Without NOMA, UE2 cannot detect information owing to the lower power compared to the interference signal from UE1. On the other hand, UE1 with NOMA can benefit from IC, even though the power of the interference signal is much higher than the target signal. Without NOMA, UE1 has performance similar to UE2 with NOMA, owing to the existing interference from the lower power user. As the results shown in Fig. 5, NOMA can increase the sum throughput and improve the fairness between the near and far users, compared with the situations without NOMA.
4.1 ZF IC error under single-path Rayleigh channel
4.2 MMSE IC error under single-path Rayleigh channel
5.1 Proposed interference-predicted MMSE IC scheme
5.2 Proposed remaining interference-predicted MMSE IC scheme
In this paper, we exploit the performance of a NOMA-MIMO system for the perfect and the practical SIC schemes, which clarifies the necessity for the investigation into IC schemes for NOMA. Because many previous works focused on NOMA, some of the research topics, such as employment of the practical SIC and the error effect due to IC, are still in the early stages or not fully developed. In this paper, we perform the error analysis considering ZF and MMSE SIC schemes for NOMA; and based on the analysis, we propose a novel IPMMSE IC scheme by predicting the MMSE weight factor using information about interference signals. In addition, based on the IPMMSE IC scheme and the analysis of the IC error effect, we propose RIPMMSE IC to further boosts the system performance. We provide the link-level evaluations for a 2-UE scenario under NOMA-MIMO system on the single-path Rayleigh channel, and the simulation results show that the RIPMMSE IC scheme outperforms ZF and MMSE IC schemes by around 1.5 and 0.5 dB, respectively, at a target BER of 10−3. In the future work, a more general case, i.e., larger number of users will be examined with our proposed schemes.
This work was supported in part by Fundamental Research Funds for the Central Universities under Grant 2015B30614, in part by the Natural Science Foundation of Jiangsu Province under Grant BK20160287, and in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science, ICT and Future Planning) (No. NRF-2015R1C1A1A01053301).
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
- K Maxim, C Andrey, P Anton, K Igor, Technique of data visualization: example of network topology display for security monitoring. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA) 7(1), 79–96 (2016)Google Scholar
- B Bharat, AM Johnson, M Gisele Izera, A Pelin, A systematic approach for attack analysis and mitigation in V2V networks. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA) 7(1), 97–117 (2016)Google Scholar
- U Kim, J Kim, Research on object-oriented relational database model and its utilization for dynamic geo-spatial service through next generation ship navigation system, IT Convergence Practice 1(2), 1–10 (2013)Google Scholar
- Y. Saito, Y. Kishiyama, A. Benjebbour, T. Nakamura, A. Li, and K. Higuchi, Non-orthogonal multiple access (NOMA) for cellular future radio access, in Proc. of IEEE VTC-Spring, 2013, pp. 1-5.Google Scholar
- Umehara, and Y. Kishiyama, Enhancing user fairness in non-orthogonalaccess with successive interference cancellation for cellular downlink, in Proc. of IEEE ICCS, 2012, 324-328Google Scholar
- K. Beomju, Non-orthogonal multiple access in a downlink multiuser beamforming system, in Proc. of IEEE MILCOM, 2013, 1278-1283.Google Scholar
- A. Benjebbour, System-level performance of downlink NOMA for future LTE enhancements, in Proc. of IEEE GC Workshop, 2013, 66-70Google Scholar
- L Dai, B Wang, Y Yuan, S Han, I Chih-Lin, Z Wang, Non-orthogonal multiple access for 5G: solutions, challenges, opportunities, and future research trends. IEEE Communications Magzine 53(9), 74–81 (2015)View ArticleGoogle Scholar
- B. Wang, K. Wang, Z. Lu, T. Xie, and J. Quan, Comparison study of non-orthogonal multiple access schemes for 5G, in Proc. IEEE International Symposium on BMSB, 2015, 1-5Google Scholar
- A Kitana, I Traore, I Woungang, Impact study of a mobile botnet over LTE networks. J Internet Serv Info Sec 6(2), 1–22 (2016)Google Scholar
- N. Otao, Y. Kishiyama, and K. Higuchi, Performance of nonorthogonal access with SIC in cellular downlink using proportional fairbased resource allocation, in Proc. of IEEE ISWCS, 2012, 476-480Google Scholar
- Q. Liu, B. Hui, and K.H. Chang, A survey on non-orthogonal multiple access schemes, in Proc. of KICS Winter Conf., 2014, 98-101.Google Scholar
- A. Benjebbour, A. Li, Y. Saito, Y. Kishiyama, A. Harada, and T. Nakamura, System-level performance of downlink NOMA for future LTE enhancements, in Proc. of IEEE Globecom, 2013, 66-70Google Scholar
- Saito, A. Benjebbour, Y. Kishiyama, and T. Nakamura, System-level performance of downlink non-orthogonal multiple access (noma) under various environments, in Proc. of IEEE VTC, 2015, 1-5Google Scholar
- T. Seyama and H. Seki, Efficient selection of user sets for downlink non-orthogonal multiple access, in Proc. of IEEE PIMRC, 2015, 1062-1066Google Scholar
- M.R. Hojeij, J. Farah, C.A. Nour, and C. Douillard, Resource allocation in downlink non-orthogonal multiple access (NOMA) for future radio access. in Proc. of IEEE VTC-Spring, 2015, 1-6Google Scholar
- X Liu, H Miao, X Huang, A novel approach for blind estimation of a MIMO channel including phase unwrapping ambiguity elimination. IT Convergence Practice 1(2), 20–33 (2013)Google Scholar
- TM Cover, Broadcast channels. IEEE Trans. Inf. Theory 18(1), 2–14 (1972)MathSciNetView ArticleMATHGoogle Scholar
- PP Bergmans, A simple converse for broadcast channels with additive white Gaussian noise. IEEE Trans. Inf. Theory 20(2), 279–280 (1974)MathSciNetView ArticleMATHGoogle Scholar
- RG Gallager, An inequality on the capacity region of multiaccess multipath channels, in Communications and Cryptography: Two Sides of One Tapestry (Kluwer, Boston, 1994), pp. 129–139View ArticleGoogle Scholar
- D. Tse and P. Viswanath, Fundamentals of wireless communication. Cambridge, Cambridge Univ. Press, 2005, ch. 6.Google Scholar
- J Choi, Minimum power multicast beamforming with superposition coding for multiresolution broadcast and application to NOMA systems. IEEE Trans. Commun. 63(3), 791–800 (2015)View ArticleGoogle Scholar
- MF Hanif, Z Ding, T Ratnarajah, GK Karagiannidis, A minorization-maximization method for optimizing sum rate in nonorthogonal multiple access systems. IEEE Trans. Signal Process 64(1), 76–88 (2006)MathSciNetView ArticleGoogle Scholar
- Q Sun, S Han, I C-L, Z Pan, On the ergodic capacity of MIMO NOMA systems. IEEE Wireless Commun. Lett. 4(4), 405–408 (2015)View ArticleGoogle Scholar
- Z Ding, F Adachi, HV Poor, The application of MIMO to nonorthogonal multiple access. IEEE Trans. Wireless Commun. 15(1), 537–552 (2016)View ArticleGoogle Scholar