Non-Orthogonal Multiple Access (NOMA) - Lancaster University
Non-Orthogonal Multiple Access (NOMA):Evolution towards 5G Cellular Networks28 April 2016Zhiguo DingSchool of Computing and CommunicationsLancaster UniversityA collaboration with Princeton, SWJTU, USTC, BUPT, FAU, AUTH,CMCC, Tsinghua, UT Dallas, XJTU, QMUL and Bell Labs
Outline: NOMA basicsMIMO-NOMACooperative NOMAInterplay between Cognitive Radio and NOMAResearch challenges
NOMA: BasicsMotivations for NOMA Orthogonal multiple access has been used during the past– FDMA/TDMA/CDMA/OFDMA Dilemma to realize a better trade-off between system throughputand user fairnessA promising solution is to break orthogonality PD-NOMA, SCMA, PDMA, LPMA, and MUSA are based on NOMAWhat have happened so far Included in various whitepapers for 5G (DOCOMO, METIS, NGMN,ZTE, SK Telecom, ) Recently proposed to 3GPP-LTE (MUST)
NOMA: BasicsKey ideas: All the users are served at the same time, frequency and code Users with better channel conditions get less power Successive interference cancellation is used at the receivers[1] Y. Saito, A. Benjebbour, Y. Kishiyama, and T. Nakamura, “System level performance evaluation ofdownlink non-orthogonal multiple access (NOMA),” in PIMRC 2013.[2] Z. Ding, Z. Yang, P. Fan and H. V. Poor, "On the Performance of Non-Orthogonal Multiple Access in 5GSystems with Randomly Deployed Users”, IEEE SPL, 2014.
NOMA: BasicsWhy NOMA is an ideal MA solution of 5G Consider the following two scenarios– If one user only needs to be served with a low data rate, e.g.sensors. The use of OMA gives the sensor more than it needs– If one user has a very poor channel condition The bandwidth allocated to this user via OMA is not used efficiently. The use of NOMA can accommodate the 5G requirements– High system throughput– Low latency– Massive connectivity
Standardization activities of NOMA- MUST: State of the art At the 3GPP meeting in May 2015, it was decided to include MUSTinto LTE Advance At the 3GPP meeting in August 2015, 15 forms of MUST have beenproposed by– Huawei, Qualcomm, NTT DOCOMO, Nokia, Intel, LG Electronics, Sharp,Samsung, ZTE, Alcatel Lucent, Finally accepted in December 2015 For example, Huawei proposed three forms of NOMA– Non-Orthogonal Multiple Access (NOMA)– Semi-Orthogonal Multiple Access (SOMA)– Rate-adaptive constellation Expansion Multiple Access (REMA)
Standardization activities of NOMA- MUST: State of the art All the forms of MUST can be categorized into three groups
MIMO-NOMA Motivations– The advent of advanced cell phones, tablet computers and other hightech hand-held devices– MIMO offers excessive degrees of freedom to further improve thesystem throughput of NOMA Challenge– The key feature of NOMA is to exploit the difference between users’channel conditions– In scenarios with single-antenna nodes, channels are scalar and it iseasy to order the users based their channel conditions– In MIMO, channels are in form of matrices/vectors, which makesdifficult to order users It is not clear how to design optimal precoding/detection strategies.
MIMO-NOMA: Approach I Assign different beams to different users
MIMO-NOMA: Approach I The QoS is satisfied by forcing the beams to satisfy a predefinedorder– In the following example, the message to User 1, a user close to thecell edge, is to be decoded first, at all users– Then the message to User 2 can be decoded, after subtracting themessage to User 1,– .[2] M. F. Hanif, Z. Ding, T. Ratnarajah and G. K. Karagiannidis “A Minorization-Maximization Method forOptimizing Sum Rate in Non-Orthogonal Multiple Access Systems, IEEE TSP, 2015.
MIMO-NOMA: Approach I The QoS is satisfied by forcing the beams to satisfy a predefinedorder– In the following example, the message to User 1, a user close to thecell edge, is to be decoded first, at all users– Then the message to User 2 can be decoded, after subtracting themessage to User 1,– .[2] M. F. Hanif, Z. Ding, T. Ratnarajah and G. K. Karagiannidis “A Minorization-Maximization Method forOptimizing Sum Rate in Non-Orthogonal Multiple Access Systems, IEEE TSP, 2015.
MIMO-NOMA: Approach I[3] P. Xu, Z. Ding, X. Dai and H. V. Poor, “A New Evaluation Criterion for Non-Orthogonal Multiple Accessin 5G Software Defined Networks”, IEEE Access, 2015
MIMO-NOMA: Approach I The QoS is satisfied by forcing the beams to satisfy a predefinedorder– In the following example, the message to User 1, a user close to thecell edge, is to be decoded first, at all users– Then the message to User 2 can be decoded, after subtracting themessage to User 1,– .[2] M. F. Hanif, Z. Ding, T. Ratnarajah and G. K. Karagiannidis “A Minorization-Maximization Method forOptimizing Sum Rate in Non-Orthogonal Multiple Access Systems, IEEE TSP, 2015.
MIMO-NOMA: Approach II Decompose MIMO-NOMA to SISO-NOMA
MIMO-NOMA: Approach II- without CSIT (1/2) Consider a BS with M antennas communicating with M groups ofusers, where there are K single-antenna users in each group The BS sends Each user receiveswhere P is an identity matrix.[4] Z. Ding, F. Adachi and H. V. Poor, “The Application of MIMO to Non-Orthogonal Multiple Access”, IEEETWC, 2015
MIMO-NOMA: Approach II- without CSIT (2/2) After applying a detection vectorwhere 𝒑1 [1 0 0]T. The detection vector is designed to satisfyfor different I and m. As a result, MIMO-NOMA can be reduced to separated SISO-NOMAsystems, where NOMA can be easily applied.
MIMO-NOMA: Approach II- with CIST (1/3) We can also use the concept of signal alignment to decomposeMIMO-NOMA into SISO-NOMA– Channel state information is needed at the BS. Consider a BS with M antennas communicating with M groups ofusers, where there are 2 single-antenna users in each group The base station will send a precoded version of symbols[5] Z. Ding, R. Schober, and H. V. Poor, “A General MIMO Framework for NOMA Downlink and UplinkTransmission Based on Signal Alignment”, IEEE TWC, 2016
MIMO-NOMA: Approach II- with CIST (2/3) After applying the detection vector, each receiver observes Directly using zero forcing precoding, means To align the signals transmitted by the two users from the same pair Now a zero forcing precoding vector only needs to satisfy
MIMO-NOMA: Approach II- with CIST (3/3) Now the system models at the two users from the same pair can bechanged as follows:and Therefore an MIMO-NOMA system can be decomposed into theseSISO-NOMA channels. There are other ways to carry out decomposing, for example, toapply generalized eigenvalue decomposition, etc. These decomposition methods can also be applied to– Uplink NOMA– SCMA and other 5G MA
MIMO-NOMA: Numerical results(1/2)The targeted data rates for two users are 5 BPCU and 0.5 BPCU. U1 is in a disc with radius of 10m andU2 is in a ring with radius of 10m and 20m. M N 3. U2 gets ¾ of the power. The path loss exponent isα 3. The noise power is 30dBm and the interference power is ρI 0.
MIMO-NOMA: Numerical results(2/2)The targeted data rates for two users are 5 BPCU and 0.5 BPCU. U1 is in a disc with radius of 10m andU2 is in a ring with radius of 10m and 20m. M N 3. U2 gets ¾ of the power. The path loss exponent isα 3. The noise power is 30dBm and the interference power is ρI 0.
Interplay between NOMA andCognitive Radio NOMA can be viewed as a specialcase of cognitive radio–The user with poorer channel stateinformation (CSI) can be viewed as aprimary user.–With orthogonal MA, bandwidthallocated to this user cannot bereused, which leads to poor spectralefficiency.–By using NOMA, a user with better CSIis admitted–Slight loss at the primary user, butsignificant improvement on systemthroughputThe base station is located at the origin,i.e., (0; 0). The user with the poor channelconditions, i.e., the primary user, islocated at (5m; 0). The x-y plan denotesthe location of the secondary user. Thepath loss exponent is 3. The transmitsignal-to-noise ratio is 20dB. A fixed powerallocation policy, (7/8, 1/8).
Interplay between NOMA andCognitive Radio The concept of cognitive radio isuseful to NOMA–The advantage of NOMA can beclearly demonstrated by usingcognitive radio–Cognitive radio can also be used tosimplify the power allocation NOMA power allocation needs tosatisfy users’ quality of service The use of cognitive radio providesan explicit expression for meetingsuch requirements.The power allocation coefficient needs to satisfy atargeted data rate of 0.5 BPCU at the primary user.[6] Z. Ding, P. Fan and H. V. Poor, “On the impact ofuser pairing on NOMA”, IEEE TVT, 2015 The application of NOMA is also beneficial to cognitive radio systems,– More secondary users can be admitted by using NOMA
Cooperative NOMA Motivations– The feature of heterogeneousnetworks means that differentusers have different capabilities– There is redundant informationinherited in NOMA systems Users with better channelconditions know theinformation sent to the otherusers. Solution – Cooperative NOMA[7] Z. Ding, M. Peng and H. V. Poor, "Cooperative Non-Orthogonal Multiple Access in 5G Systems”, IEEECommunication Letters, 2015.
Cooperative NOMA SWIPT Motivation– To improve the reliability of thefar NOMA users withoutdraining the near users’batteries consider the application ofSWIPT to NOMA, where SWIPTis performed at the near NOMAusers.[8] Y. Liu, Z. Ding, M. Elkashlan, and H. V. Poor, “Cooperative Non-Orthogonal Multiple Access withSimultaneous Wireless Information and Power Transfer”, IEEE JSAC, 2016
Future directions Different variants of NOMANew coding and modulation for NOMAHybrid multiple accessUser pairing/clusteringMIMO and cooperative NOMAInterplay between NOMA and cognitive radioImperfect CSI and limited channel feedbackSecurity provisioning in NOMACross-layer optimizationImplementation issues of NOMAEmerging applications of NOMA
Future directions MIMO-NOMA– Can we combine massive MIMO with NOMA? Solution: using spatial clustering [9] Z. Ding and H. V. Poor, “Design of Massive-MIMONOMA with Limited Feedback”, IEEE SPL, 2016– Can we do NOMA even if users have similar CSI? Solution: using users’ dynamic QoS requirements [10] Z. Ding, L. Dai and H. V. Poor, “MIMO-NOMA Designfor Small Packet Transmission in the Internet of Things”,IEEE Access, 2016
Thank you for your attention.Questions?Z. Ding, Y. Liu, J. Choi, Q. Sun, M. Elkashlan, C-L. I and H. V. Poor, “Application of Non-orthogonalMultiple Access in LTE and 5G Networks”, submitted to IEEE Communication Magazine.D. Fang, Z. Ding, Y. Huang, S. Shieh, G. Geraci, H. Claussen, and M. Zhang, Candidates for 5GDownlink Multiple Access, submitted to IEEE Communication il: z.ding@lancaster.ac.uk
downlink non-orthogonal multiple access (NOMA)," in PIMRC 2013. [2] Z. Ding, Z. Yang, P. Fan and H. V. Poor, "On the Performance of Non-Orthogonal Multiple Access in 5G Systems with Randomly Deployed Users", IEEE SPL, 2014. Key ideas: All the users are served at the same time, frequency and code
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