Fixed Power Allocation for Outage Performance Analysis on AF-assisted Cooperative NOMA Xem nội dung đầy đủ tại: https://123docz.net/document/11923410-issn-2315-4462.htm

ISSN 2315 4462 Fixed Power Allocation for Outage Performance Analysis on AF assisted Cooperative NOMA Dinh Thuan Do and Tu Trinh T Nguyen Faculty of Electronics Technology, Industrial University of Ho[.]

Journal of Communications Vol 14, No 7, July 2019 Fixed Power Allocation for Outage Performance Analysis on AF-assisted Cooperative NOMA Dinh-Thuan Do and Tu-Trinh T Nguyen Faculty of Electronics Technology, Industrial University of Ho Chi Minh City, Vietnam Email: dodinhthuan@iuh.edu.vn, tutrinhamber@gmail.com Abstract—In this paper, new radio access scheme that combining relaying protocol and Non-orthogonal Multiple access (NOMA) system is introduced In particular, different scenarios for fixed power allocation scheme are investigated In addition, the outage probability of both weak and strong user is derived and provided in closed-form expressions Such outage is studied in high SNR scenario and comparison performance between these NOMA scenarios is presented Numerical simulations are offered to clarify the outage performance of the considered scheme if varying several parameters in the existing schemes, and to verify the derived formula Index Terms—Cooperative non-orthogonal multiple access, outage probability, AF I INTRODUCTION As one favorable technology in future fifth-generation (5G) wireless networks, non-orthogonal multiple access (NOMA) has been proposed to increase spectral efficiency [1] By permitting multiple users served in the same time, frequency or code domain, spectral efficiency and user fairness are improved in NOMA compared with Orthogonal Multiple Access (OMA) In NOMA, the transmitter superposes multiple users’ messages and the receivers deploys successive interference cancellation (SIC) to distinct the mixture signals in the power domain [2] In [3], the system performance regarding outage probability (OP) and ergodic capacity were studied in typical dual-hop NOMA transmission The fixed relaying and adaptive relaying schemes have been suggested to implement cooperative communication The full-duplex and relaying network are investigated in [4], [5] Recently, in relaying networks, two well- known cooperative relaying protocols are studied, namely Amplify Forward (AF) and decode forward (DF) [6, 7] By AF protocols, received signal from the source is amplified to forward to the destination, while the received signal in DF protocols need be first decoded, then reencoded to forward to the destination The author in [8] presented hardware impairment as important impact on system performance of such relaying scheme The relaying scheme as consideration can be deployed together with NOMA Formerly, superposition coding is proposed in wireless network and currently it is named as NOMA Such scheme improves the throughput of a broadcast/multicast system and efficient broadcasting is Manuscript received November 12, 2018; revised June 3, 2019 doi:10.12720/jcm.14.7.560-565 ©2019 Journal of Communications 560 achieved Additionally, the influence of user coupling on the performance in NOMA is investigated [9], in which both the fixed power distribution assisted NOMA (FNOMA) and cognitive radio assisted NOMA (CRNOMA) systems were considered in term of the outage performance Furthermore, the outage balancing among users was investigated by deploying user grouping and decoding order selection [10] In particular, the optimal decoding order and power distribution in closed-form formula for downlink NOMA were performed In [11], only feed back one bit of its channel state information (CSI) to a base station (BS) is considered in term of outage behavior of each NOMA user in downlink NOMA As advantage of such model as providing higher fairness for multiple users, it lead to NOMA with better performance as comparison with conventional opportunistic one-bit feedback In order to increase the specific data rate, the wireless powered communication networks (WPCN) scheme is deployed with NOMA uplink system in [12] By using the harvested energy in the first time slot, the strong users in NOMA can be forward signal to the weak users’ messages in the second time slot in case of using half-duplex (HD) scheme [13] The maximising the data rate in the strong user with guaranteeing the QoS of the weak user is considered as in [14] to solve tackle of SWIPT NOMA system related to half-duplex case Motivated by above analysis in [9], this paper presents a fixed power allocation scheme to show outage performance of separated users in the NOMA scheme in case of deployment of AF scheme II SYSTEM MODEL We consider a downlink cooperative NOMA scenario consisting of one base station denoted as BS, one relay R and two users (i.e., the nearby user D2 and distant user D1) The Amplify-and –Forward (AF) protocol is employed at each relay and only one relay is selected to assist BS conveying the information to the NOMA users in each time slot All wireless channels in the scenario considered are assumed to be independent non-selective block Rayleigh fading and are disturbed by additive white Gaussian noise with mean power  The wireless channel h CN (0,1), g1 CN (0,1), g2 CN (0,1), denote the complex channel coefficient of BS-R, R-D1, R-D2, respectively In principle of NOMA, two users are Journal of Communications Vol 14, No 7, July 2019 classified into the nearby user and distant user by their quality of service (QoS) not sorted by their channel conditions In this case, we assume transmit power at relay and the BS is the same a2  h g 2  2, x  2 a2  h g 2  Cell-center ipsic 2, x  D1 R Fig System model of AF-NOMA Based on the aforementioned assumptions, the observation at the relay R is given by  a1 Px1  a2 Px2  wr (8)  f   h   g  2 Remark 1: With regard to optimize of power allocation can be studied to obtain better performance as further work considered in our next papers However, such computation of power allocation needs more complexity in signal processing as overhead information of power allocation must be known to control power associated with each users BS D2  (7)  h   g2  In case of imperfect SIC, we have Cell-edge yR  h (1) III OUTAGE PERFORMANCE ANALYSIS where x1 , x2 are the normalized signal for D1, D2,   In this section, we performs analysis on the performance of AF-NOMA scheme in terms of outage probability for several signal processing cases To make its convenient in analysis, this paper presents exact expressions for the outage probability In order to reduce the computation complexity, a tight lower bound for the outage probability is provided in the high-SNR regime to better understand the behavior of the network In general, an outage event occurs at the strong or the weak user when the user fails to decode its own signal In this section, we denote the threshold SNR as  i , i  1, Based on the rate requirements of the users, we can choose different target rate values for R1 and R2, and we will demonstrate how the R1 and R2 affect the outage performance in the numerical result section For sake of brevity, we denote 1  22 R1  1,   22 R2    respectively It is assumed that E x12  E x22  , a1 , a2 are power allocation factors To stipulate better fairness between the users, we assume that a1  a2 satisfying a1  a2  Using AF scheme, the amplify gain is defined by  (2) P h  2 In the second phase, the received signal at user D1 is yD1   Pg1 h    a1 Px1  a2 Px2  wr   wd  (3) where wr , wd are additive white Gaussian noise terms with mean power  Similarly, the received signal at user D2 is given by yD   Pg2  A Outage Probability of D1 We first consider the outage probability for detecting x1 at D1 can be expressed as  a1 Px1  a2 Px2 h   Pg2 wr  wd (4) OP1 To evaluate system performance, we first consider the received signal to interference plus noise ratio (SINR) at D1 to detect x1 is given by a1  h g1 1  2 2 first calculate each component of outage event as below (5) OPD1, x1 In which, we denote   P  as signal to noise ratio (SNR) at the BS By considering in SIC is also invoked by D2 and the received SINR at D2 to detect x1 is given by a1  h g 2  2, x1  2 In the of h  a1  a21   1  , i.e h  1   a1  a21  , we have OPD1, x1  , else 2 event (10) (6)  1   1   a1  a21  561    1  h    Pr  g1    h  a1  a21   1    Then the received SINR at D2 to detect its own information is given by ©2019 Journal of Communications 2   a1  h g1   Pr  1  2 2     h g1 a2   h   g1   OPD1, x1 a2  h g   h   g  (9) Here, we denote Pr . as probability function We a2  h g1   h   g1  OPD1, x1  Pr   1          1   z  1  z dz exp       z  a1  a21   1     (11) Journal of Communications Vol 14, No 7, July 2019 2  h g a2   h   g 2  Putting new variable t  1 t   z  a1  a21   1  z    a1  a21   a   2 2    a2   h g   h   g  1,       Pr    a2 2 2   h g2   h   g2       as Based on (11) we can find that:  OPD1, x1       a1  a2 1   1   1   z  1  z dz exp       z  a1  a21   1       a a  2 2    a2 ,   h g   h   2    Pr    1     g2   (12)   a1  a21       t  1 t  1  exp     dt  t   a  a    t   a  a    1   where  (13)  12  1  a1  a21   t  exp    dt   t  a1  a21    a1  a21    Final step, it can be expressed the outage event as below  can be calculated as OPD 2, x  In the case of  h   , the outage probability is given by     1   z 1    1  exp        t 1     1  dt t        1    t  exp   dt   exp     1  t      0      (18) Similarly steps to achieve (11), it can be found outage probability in such as  1 (15)   OPD 2, x   exp         Substituting (6) and (7) into (15), we have OPD 2, x   Pr  J1 , J    exp     z  1  z dz OPD 2, x     Pr   2, x1  1 ,  2, x       1) Perfect SIC Secondly, the outage probability for detecting x2 at D2 can be expressed as (16)  1  2     where J1  a a   a2 ,    2 a1  h g  1 , 2  h g a2   h   g 2  1    1    1    1    (19) 2) Imperfect SIC  ipsic OPDipsic 2, x  Pr  2, x1  1 or  2, x   and    Pr  2, x1  1 ,  2,ipsic x2   2 a2  h g J2   2  h   g2  In this paper,  2, x1  we   (20) approximate 2 SNR regime when    a1   1  OPDipsic 2, x   Pr  a   562 the a1  h g  a1 a2 in high  h g a2   h   g 2  Exact analysis is  a  h2 g2 2 2 OPD 2, x  Pr   a2  h 2g   , OPD 2, x  Pr   h 2  g 2   ,    h   2g   2  a1  h2 g2 2  a1  h g  1   2  1 2  h2 g2 a22   h 2  g    h g a2   h   g 2      a1   2 2    a1 a2   h2 g2 2  h 2  g 2 1,        h g h g  a      2   1 1,  2   Pr   ©2019 Journal Communications   ofPr a  2a2 h2 g2 2 2  h 2  g 2 2     h g   h   g    2    (17) inequality h   , the outage probability in this case 1  1   a1  a21   OPD 2, x  Pr  2, x1  1 or  2, x          B .Outage Probability of D2 OP2 In the case of  h   , it leads to following   21   exp     1  1  (14)    a  a    1     a1  a21     21 exp       a1  a21     a1  a21   where 1  2   h 1   Pr  g    h    It can be further manipulated as below OPD1, x1    Pr  h g   h   g   OPD1, x1    1    2   a2  h g  Pr   2  2   f   h   g2     Journal of Communications Vol 14, No 7, July 2019  a1   1  OPDipsic 2, x   Pr   a2  2   a2  h g    Pr     f   h   g 1    1asym  1  OP1  R (21)   21    R,  exp      a  a    1     Firstly, we consider the first item, if a1 a2  1 we obtain OPDipsic 2, x  , else a1 a2  1 we have where     a2  h g  OPDipsic  2  2, x   Pr 2 2   f   h   g 1    2  2  f   h 1  (22)    Pr  g    a2  h            2t   z      exp  t   exp    z dzdt    a2  z     2   a 2      a1  a21  The throughput at D2 will become  1  OP2  R  asym   1  1   a1  a21   (27)  2  exp     a2  where   2  a2   1   R,  (28)  2    1  a2  IV NUMERICAL RESULTS In the first case of a2  h    , it leads to In this section, the outage performance of the downlink AF-NOMA network under Rayleigh fading channel is evaluated via numerical examples to validate derived formula Moreover, the fixed power allocation is applied in order to further evaluation of such NOMA Without loss of generality, we assume the distance in each link of two-hop relaying NOMA is normalized to unity In the following simulations, we set the fixed power allocation factors for NOMA users as a1  0.9, a2  0.1 following equation h    a2 , outage probability in this case calculated as OPDipsic 2, x  In the second case, as a2  h     OPDipsic 2, x    exp   x      a2    2  x   z 1  exp    z dz dx     a2  z      (23) 1  2       exp       , 2 a a  a     2  2    1  a   where  b   a   2 exp  a    1, a       a, b  exp     a b   y  y 1 y exp    dy   a    (24) Proof: see in Appendix C Asymtotic Analysis And the lower bounds of the outage probability in (14)and (19) are shown to be tight bounds in the mediumand high-SNR regimes At high SNR, the outage probability at D1 will become   21 OPD1, x1  exp      a  a      Fig Outage probability vs the transmit SNR Fig plots the outage probability of considered scheme versus SNR for a simulation setting R1  bits/s/Hz, R2  bits/s/Hz It can be seen that the exact analytical results and simulation results are matched very well In particular, it shown that as the system SNR increases, the outage probability decreases Another important observation is that the outage probability for User D1 of NOMA outperforms for User D2 Note that the results related to such outage performance resulted from power allocation for each user in NOMA In Fig 3, the outage probability versus system SNR is presented in different threshold SNR parameters In this case, our parameters are R1 , R2   1, 2 bits/s/Hz, (25) At high SNR, the outage probability at D2 will become  2  OPD 2, x  exp      a2  (26) To further evaluation of system, we consider the throughput in delay-limited mode In particular, the throughput mainly depends on the outage probability The throughput at D1 will become ©2019 Journal of Communications R1 , R2   0.5,1.5 bits/s/Hz 563 for target rates Obviously Journal of Communications Vol 14, No 7, July 2019 in this case, the outage probability curves match exactly with the Monte Carlo simulation results One can observe that adjusting the target rates of NOMA users will affect the outage behaviors of considered scheme As the value of target rates increases, the outage performance will becomes worse It is worth noting that the setting of reasonable threshold SNR or target rate for NOMA users is prerequisite based on the specific application requirements of different scenarios Fig Throughput performance vs the transmit SNR V CONCLUSIONS This paper presented a novel downlink cooperative communication system that combines NOMA with AF relaying techniques in analytical model for outage analysis The proposed scheme in term of outage performance is considered under impacts of various parameters in cooperative NOMA systems Furthermore, impact of the transmit SNR of the source node in cooperative relaying NOMA on the throughput is performed via simulation and acceptable threshold can be shown to the system evaluation The superior performance of the proposed schemes was demonstrated by the numerical results As a future work, it will be interesting to investigate the user fairness problem only with relative locations of the users as in group More importantly, the outage probability of both strong and weak users in the system is derived and verified by comparing numerical simulations and analytical simulation Fig Outage probability vs the transmit SNR with different threshold SNR Fig plots system outage probability versus SNR in high SNR mode It can be observed that the analytical results meet with that in high SNR case In Fig 4, the outage performance comparison in high SNR regime, in which we setup R1  bits/s/Hz, R2  bits/s/Hz This illustration indicates that our derived expressions are tight result for evaluation in related NOMA networks APPENDIX (PROOF OF PROPOSITION 1) In (23), we can express in following formula 1  x       a2     2  x   z 1  exp    z dz     a2  z       4   2     t  exp     exp     x   1  dt  4t a2  a a   2  a2       2    exp     a2   a2  Fig Outage performance comparison in high SNR regime           x   1 ,  a2   a2    Fig plots system throughput versus SNR in delaylimited transmission mode Here, we set R1  0.5 The intergal expression in (23) becomes bits/s/Hz, R2  bits/s/Hz Furthermore, the AF-based NOMA scheme for D1 outperform D2 in terms of system throughput This phenomenon indicates that it is of significance to consider the impact of power allocation for such scheme when designing practical cooperative NOMA systems ©2019 Journal of Communications  2    x   1 a2     2      2 exp   x  exp     x   1  a2  a2   a2     2 1   a2   564  2     x   1  dx a2    (A.1) Journal of Communications Vol 14, No 7, July 2019 Now consider a following integration form      a, b  2 exp   x  ax  b 1 ax  b dx [10] b    b   y   exp       y  y exp    dy   a   a      (A.2) The integral formula in can be obtained by using [15, vol 4, eq (1.1.2.3)] and re-expressed as The first term in (23) can be fulfilled by applying [15, vol 4, eq (3.16.2.4)]    a  x 1   4a x exp   x  dx [11] [12]  a    4a a   2 4a   4a   exp     1,      (A.3) [13] exp  a    1, a  The second term in (A.2) is difficult for producing closed-form because of the Bessel function and exponential function This is end of proof  [14] REFERENCES [1] Y Saito, et al., “Non-orthogonal multiple access (NOMA) for cellular future radio access,” in Proc IEEE Veh Tech Conf, Dresden, Germany, Jun 2013, pp 1-5 [2] S M R Islam, N Avazov, O A Dobre, et al, “Powerdomain non-orthogonal multiple access (NOMA) in 5G systems: potentials and challenges,” IEEE Communications Surveys Tutorials, no 99, p 1, Oct 2016 [3] D T Do and C B Le, “Application of NOMA in wireless system with wireless power transfer scheme: Outage and ergodic capacity performance analysis,” Sensors, vol 18, no 10, 2018 [4] K T Nguyen, D T Do, X X Nguyen, N T Nguyen, and D H Ha, “Wireless information and power transfer for full duplex relaying networks: Performance analysis,” in Proc Recent Advances in Electrical Engineering and Related Sciences, HCMC, Vietnam, 2015, pp 53-62 [5] X X Nguyen and D T Do, “Maximum harvested energy policy in full-duplex relaying networks with SWIPT,” International Journal of Communication Systems (Wiley), vol 30, no 17, 2017 [6] D T Do, H S Nguyen, M Voznak, and T S Nguyen, “Wireless powered relaying networks under imperfect channel state information: System performance and optimal policy for instantaneous rate,” Radioengineering, vol 26, no 3, pp 869-877, 2017 [7] X X Nguyen, D T Do, “Optimal power allocation and throughput performance of full-duplex DF relaying networks with wireless power transfer-aware channel,” EURASIP Journal on Wireless Communications and Networking, p 152, 2017 [8] D T Do, “Power switching protocol for two-way relaying network under hardware impairments,” Radioengineering, vol 24, no 3, 765-771, 2015 [9] Z Ding, P Fan, and H V Poor, “Impact of user pairing on 5G non-orthogonal multiple-access downlink 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SWIPT NOMA systems,” IEEE Trans Signal Process., vol 65, no 18, pp 4874–4886, 2017 A P Prudnikov, Y A Brychkov, and O I Marichev, Integrals and Series, New York, NY, USA: Gordon and Breach, 1992 Dinh-Thuan DO received the B.S degree, M.Eng degree, and Ph.D degree from Viet Nam National University (VNU-HCMC) in 2003, 2007, and 2013 respetively, all in Communications Engineering He was a visiting Ph.D student with Communications Engineering Institute, National Tsing Hua University, Taiwan from 2009 to 2010 Prior to joining Ton Duc Thang University, he was senior engineer at the VinaPhone Mobile Network from 2003 to 2009 Dr Thuan was recipient of Golden Globe Award from Vietnam Ministry of Science and Technology in 2015 His research interest includes signal processing in wireless communications network, cooperative communications, full-duplex transmission and energy harvesting His publications include 25 + SCI/SCIE journals and 50+ conference papers He also serves as Associate Editor of Bulletin of Electrical Engineering and Informatics journal (SCOPUS) Tu-Trinh T Nguyen received the B.Sc degree in ElectricalElectronics Engineering from Industrial University of Ho Chi Minh City, Vietnam (2018) She is working at WICOM lab Her research interest includes signal processing in wireless communications network, NOMA, relaying networks 565 ... better performance as further work considered in our next papers However, such computation of power allocation needs more complexity in signal processing as overhead information of power allocation. .. signal for D1, D2,   In this section, we performs analysis on the performance of AF -NOMA scheme in terms of outage probability for several signal processing cases To make its convenient in analysis, ... probability for User D1 of NOMA outperforms for User D2 Note that the results related to such outage performance resulted from power allocation for each user in NOMA In Fig 3, the outage probability