Non-Orthogonal Multiple Access (NOMA) in 5G Systems for Future Radio Access

S.M. Riazul Islam, PhD www.riazulislam.com

A Tutorial for ITRC Graduate Students at Inha University

Contents

Motivation

Part 1: NOMA Basics

Part 2: NOMA Advanced Topics

Motivation

5G: Mobility, Throughput, Latency, Reliability Peak data rate: 10-20 Gbps (4Gx10-20)

User experienced data rate: 1 Gbps (4Gx100)

Researchers from NTT DOCOMO, INC have investigated on NOMA for both uplink and downlink for future radio access

Y. Saito, Y. Kishiyama, A. Benjebbour, and T. Nkamura, A. Li, and K. Higuchi, “Non-orthogonal multiple access (NOMA) for future radio access,” IEEE VTC, Germany, Jun. 2013

Y. Saito, A. Benjebbour, Y. Kishiyama, and T. Nkamura, “System level performance evaluation of downlink non-orthogonal multiple access (NOMA),” IEEE PIMRC, London, Sep. 2013

NOMA: a promising multiple access technique for 5G networks

Part 1: NOMA Basics

From Noise to Interference Cancellation

• What happened in CDMA: (say, uplink) an optimal multiple access strategy is for all users to spread their signal across the entire bandwidth. Decoding every user treating the interference from other users as noise.

• What happened if: a successive interference cancellation (SIC) receiver is used. That is, after one user is decoded, its signal is stripped away from the aggregate received signal before the next user is decoded.

• In downlink, with signals for the users superimposed on top of each other and SIC done at the mobiles.

Capacity Enhancement Instead

Downlink AWGN Channel • Single Tx and multiple Rx

• At receiving side, users separately decode their data from the signals they receive.

• The regions of the rate (R1, R2) at which two users simultaneously can communicate

Received Signal at User k at time m

Superposed Transmitted

Signal

Average Power of P Joules/symbol

Downlink AWGN Channel

• This upper bound on Rk can be attained by using all the power and degrees of freedom to communicate to user k (with the other user getting zero rate). Thus, we have the two extreme points:

We can obtain any rate pair that is a combination of these two extreme points.

Can we achieve a rate pair outside this triangle?

Consider a symmetric case:

Downlink AWGN Channel

Let us now think for another idea: if user 1 can successfully decode its data from y1, then user 2 which has the same SNR should also be able to decode the data of user 1 from y2. (Both y1 and y2 contains the superposed transmitted signal)

Then, user 2 can subtract the codeword of user 1 from its received signal y2 to better decode its own data, i.e., it can perform successive interference cancellation.

Consider the superposed signal:

The transmitter encodes the information for each user over the entire bandwidth (and powers P1 and P2 with P1 + P2 = P)

Downlink AWGN Channel

User 1 treats the signal for user 2 as noise and can hence be communicated to reliably at a rate of

User 2 first decodes the data of user 1, subtracts the user 1 signal from y2 and extracts its own data. Thus, user 2 can support reliably a rate

Downlink AWGN Channel

Superposition encoding example: The QPSK constellation of user 2 is superimposed on top of that of user 1.

Downlink AWGN Channel

Superposition decoding example: The transmitted constellation point of user 1 is decoded first, followed by decoding of the constellation point of user 2.

Downlink AWGN Channel

We see that the rate pair achieved in the figure (from slide 5) can also be achieved by the SIC strategy (Equations below)

Downlink AWGN Channel Not symmetric channel: Let us consider the user 2 has better channel conditions than that of user 1

Note: α represents the fraction of the bandwidth devoted to user 1

Orthogonal Schemes Non-Orthogonal Schemes

Downlink AWGN: Orthogonal vs. Non-Orthogonal

Orthogonal Schemes

Non-Orthogonal Schemes SNR1= 0dB and

SNR2=20 dB

P1=P2=P/2

Orthogonal vs. Non-Orthogonal Schemes

Note: Capacity boundary of NOMA depends on the differences in channel gains and power allocation.

A Numerical Example

Power allocation for each UE greatly affects the user throughput performance!

• NOMA achieves superior spectral efficiency compared to OMA.

NOMA Basics Learned

NOMA exploits power domain multiplexing.

Superposition coding at Tx.

Successive interference cancellation at Rx.

A pair of users can be served by NOMA if their channel gains are considerably different.

Power allocation strategies play an pivotal role in capacity enhancement.

Generalization: From Two Users to K Users

ℎ12 ≤ ℎ2

2… ≤ ℎ𝐾2

Consider a general case of K users and channels are sorted as

note: hk means the kth smallest instantaneous channel

Then, the capacity regions can be obtained by

The cancellation order at every receiver is always to decode the weaker users before decoding its own data.

Noise from other users after SIC

Part 2: NOMA Advanced Topics

Outage Performance of NOMA • Consider a cell of radius RD with a Tx and some N randomly deployed users

• The outage at the ith user will be occurred if the ith user cannot decode any of the users of lower order.

• Define Ei,l as the event that the ith user cannot detect the jth user’s message (1≤l≤i). Then, the outage probability at the ith user:

𝑃𝑖𝑜𝑢𝑡 =𝜏𝑖𝑖𝜂𝑖 𝜓𝑖∗ 𝑖

𝑃𝑖𝑜𝑢𝑡=1-P(𝐸𝑖,1

𝑐 ⋂𝐸𝑖,2𝑐 ) ⋂... ⋂𝐸𝑖,𝑖

𝑐 )

Note that each event requires a minimum SNR

𝐸𝑖,𝑙𝑐 >> Assume, Rayleigh channel

>>CDF and PDF of channel gains >> Knowledge of order statistics

𝜏𝑖 =𝑁!

𝑖 − 1 ! 𝑁 − 𝑖 ! 𝜂 =

1

𝑅𝐷 𝛽𝑙𝐿

𝑙=1 𝛽𝑙 =

𝜋

𝑙1 − 𝜃𝑙

2𝑅𝐷2𝜃𝑙 +𝑅𝐷21 +𝑅𝐷2𝜃𝑙 +𝑅𝐷2

𝛼

𝜃𝑙 = 𝑐𝑜𝑠2𝑛 − 1

2𝐿𝜋 Complexity

trade-off parameter

Path-loss factor

Outage Performance of NOMA

Outage performance of NOMA with random users in a cell.

• NOMA User 1 • Also called weak user • Experiences weak channel • Assigned to more power • Performs better at low SNR

• NOMA User 2 • Also called strong user • Experiences strong channel • Assigned to less power • Performs better at high SNR

Cooperative Comm. with NOMA

• The users with better channel conditions decode the messages for the users with poor connections to the base station.

• Can be implemented by UWB and BT (strong users to weak users communications)

Performed in two phases

1) Direct Transmission (BS to NOMA users) BS sends N messages if there are N NOMA users

2) Cooperative Phase (N-1) time slots are required

At first time slot, the Nth user send sends (N-1) messages

At second time slot, the (N-1)th user send sends (N-2) messages

And so on

𝑃𝑜𝑢𝑡 ≜ 1 − 1− 𝑃𝑖𝑜𝑢𝑡

𝑁

𝑖=1

.

Cooperative Comm. with NOMA

Outage performance of a cooperative NOMA.

Users with the worst channel condition get assistance from the other 𝑁 − 1 users, along with their own direct links to the source

Non-cooperative NOMA can attain only a diversity order of 𝑖 for the ith ordered user

C-NOMA ensures that a diversity order of 𝑁 is achievable for all users by exploiting user cooperation.

NOMA with Beamforming

• NOMA-BF allows two users to share a single beamforming vector.

• BUT, inter-beam interference (from users of other beams) and intra-beam interference (from users sharing the same beamforming vector).

• To reduce the above interferences: clustering and power allocation algorithm based on correlation among users and channel gain difference, respectively.

• Improves the sum capacity, compared to the conventional multi-user beamforming system. Also, guarantees weak users’ capacity to ensure user fairness.

NOMA with Beamforming

• Two users in each cluster should be selected in such a way that they have high correlation and high channel gain differences.

• High correlation ensures that they can use same beamforming vector W

• High channel gain difference ensures the applicability of NOMA

NOMA with Beamforming

The Sum capacity of NOMA beamforming

The aim is to determine the set of power allocation coefficients for which the sum capacity becomes maximum

NOMA with Space-Time Code

• A cell-edge user usually experiences a lower data rate.

• Presently, coordinated multipoint (CoMP) transmission (and reception) techniques are usually employed to increase transmission rates to cell-edge users.

• The associated BSs for CoMP need to allocate the same channel to a cell-edge user. So, the spectral efficiency of the system worsens as the number of cell-edge users increases.

A coordinated superposition coding (CSC)-based NOMA scheme can solve this problem.

BSs transmit Alamouti (space-time) coded signals to user c (a cell-edge user), while each BS also transmits signals to a user near the BS.

BS 1 applies NOMA on user 1 and user c, whereas BS 2 applies NOMA on user 2 and user c.

NOMA with Space-Time Code

Sum capacity of CSC-based NOMA.

In CSC-based NOMA

• Data symbols to user c from BS 1: a(1) and -a*(2) over the first and second time slot

• Data symbols to user c from BS 2: a(2) and a*(1) over the first and second time slot

Non-CSC–based NOMA considers only one BS (either one) to employ SC to serve a pair of cell-edge and nearby users simultaneously.

Remarks

NOMA is getting huge attention to the researchers for 5G

Diversity comes from power domain

Many research results are found in favor of NOMA

Outage probability, sum capacity, ergodic capacity, week user’s rate guarantee

Successive interference cancellation is mandatory

Signal superposition coding (SC) and decoding is the game-changer

But, SC is not new: Higher order modulation is a kind of SC scheme

Impact of SIC error propagation

Practical considerations: Power allocation, mobility, and subband scheduling

“Concept and Practical Considerations of Non-orthogonal Multiple Access (NOMA) for Future Radio Access” (Benjebbour et al. 2013)