Source-linked AI summary
Cooperative Non-Orthogonal Multiple Access in 5G Systems
Zhiguo Ding, Mugen Peng, H. V. Poor
TL;DR
The paper addresses how to exploit prior message knowledge created by NOMA to improve reception reliability. It proposes cooperative NOMA with inter-user relaying, analyzes outage and diversity, and introduces user pairing for practical deployment. The scheme can provide diversity order K to all users, while numerical results show 1.7 BPCU at 10% outage and 15 dB transmit SNR.
Problem
NOMA users with better channel conditions know other users’ messages, but the paper seeks to exploit this prior information for cooperative reception.
Method
The paper proposes cooperative NOMA in which users relay decoded message combinations over short-range links, and studies user pairing to reduce implementation complexity.
Results
Cooperative NOMA ensures diversity order K for all users, and supports 1.7 BPCU at 10% outage probability with 15 dB transmit SNR.
Takeaways & Limitations
Pairing users with substantially different channel conditions can provide significant gain while mitigating coordination overhead and short-range resource costs.
Abstract
from arXiv · showhide
Non-orthogonal multiple access (NOMA) has recently received considerable attention as a promising candidate for 5G systems. A key feature of NOMA is that users with better channel conditions have prior information about the messages of the other users. This prior knowledge is fully exploited in this paper, where a cooperative NOMA scheme is proposed. Outage probability and diversity order achieved by this cooperative NOMA scheme are analyzed, and an approach based on user pairing is also proposed to reduce system complexity in practice.
I. INTRODUCTION
NOMA lets users transmit simultaneously with different power levels, enabling stronger-channel users to decode weaker users’ messages. The paper proposes cooperative NOMA to exploit this prior information through relaying and analyzes its reliability and diversity gains.
- NOMA allows multiple users to transmit simultaneously on the same code and frequency with different power levels.
- Better-channel users receive less power and use successive interference cancellation to decode their own information.
- Cooperative NOMA uses better-channel users as relays for users with poor base-station connections.Short-range technologies such as Bluetooth and UWB can deliver relayed messages.
- Analytical results show that cooperative NOMA can achieve the maximum diversity gain for all users.
- User pairing is proposed because coordinating all users consumes system overhead and extra short-range communication resources.
II. SYSTEM MODEL
The system model is a broadcast channel with one base station acting as source and K users acting as destinations. Cooperative NOMA is organized into two phases.
- The model contains one base station and K destination users connected through a broadcast channel.
- Cooperative NOMA transmission consists of two phases.
A. Direct Transmission Phase
In the direct phase, the base station sends all users’ messages using NOMA superposition transmission. Users are ordered by channel quality, and the strongest user successively detects other messages before decoding its own.
- The base station transmits a superposition of K messages, with each message weighted by a power allocation coefficient.
- Users are ordered according to channel quality, with channel coefficients modeled as Rayleigh fading and additive Gaussian noise.
- NOMA assigns nonincreasing power coefficients across the ordered users.
- The strongest ordered user successively decodes the other users’ messages before decoding its own information.
- Successful decoding of the strongest user requires log(1 + SNRK,k) > Rk for every user k.Rk denotes the targeted data rate for the k-th user.
B. Cooperative Phase
In the cooperative phase, users forward combinations of decoded messages over short-range links, and receivers combine direct and relayed observations. This cooperation boosts reception reliability.
- The cooperative phase uses K −1 time slots for inter-user short-range transmissions.
- The strongest user first broadcasts a coefficient-weighted combination of the other K −1 messages.
- The (K −1)-th user applies maximum ratio combining to observations from the direct and cooperative phases.
- At later time slots, progressively weaker users broadcast combinations of messages already decoded for users below them in channel order.
- Cooperation can boost reception reliability compared with direct transmission.
III. PERFORMANCE ANALYSIS
The analysis derives outage-probability bounds and diversity orders for cooperative NOMA, then motivates user pairing as a practical complexity reduction. Cooperative NOMA can provide diversity order K to users under stated reliable-detection conditions, while pairing users with disparate channel qualities improves NOMA’s rate advantage.
- Cooperation assumptions: Short-range cooperation does not reduce the data rate or consume cellular frequency resources.Without short-range communication, cooperation instead requires additional time slots and modifies the targeted receive SNR.
- Diversity-order analysis: Under the assumption that the (n−1) best users reliably detect messages, the (K−n)-th ordered user achieves diversity order K.The result is obtained by combining the outage-probability expressions and high-SNR approximations.
- Outage-probability analysis: The overall outage event occurs when any user cannot achieve reliable detection, and its probability is analyzed using independent source-destination channels.The derivation applies outage definitions, probability bounds, order statistics, and high-SNR approximations.
- Diversity-order analysis: All users can achieve diversity order K with cooperative NOMA, compared with diversity order n for the n-th ordered user under non-cooperative NOMA.The worst user gains K independent source-to-user paths through cooperation.
- User pairing: Pairing users with significantly different channel fading is preferable because the NOMA sum-rate gap depends on channel disparity rather than power-allocation coefficients.The same pairing conclusion is stated to apply to cooperative NOMA, while the weaker user’s rate is bounded by the stronger user’s decoding requirement.
IV. NUMERICAL STUDIES
Numerical studies compare cooperative NOMA with orthogonal MA and non-cooperative NOMA across outage probability, outage capacity, and user pairing. Cooperative NOMA performs best in the reported comparisons, while pairing the strongest and weakest users yields a significant rate gain.
- Outage probability: Cooperative NOMA outperforms orthogonal MA and non-cooperative NOMA in outage probability, particularly because all users can achieve maximum diversity gain.The comparison uses K = 2 and varies SNR.
- Outage capacity: At 10% outage probability and 15 dB transmit SNR, outage capacity is 0.7 BPCU for orthogonal MA, 0.95 BPCU for non-cooperative NOMA, and 1.7 BPCU for cooperative NOMA.The setting uses R1 = R2.
- Resource constraints: Cooperative NOMA still outperforms the comparable schemes at high SNR when local short-range communication bandwidth resources are unavailable.In that case, cooperation transmissions use extra (M −1) time slots.
- User pairing: Pairing the best-channel user with the worst-channel user can yield a significant sum-rate gain over orthogonal MA.The results confirm that careless user scheduling diminishes NOMA’s benefit.
V. CONCLUSIONS
The paper proposes cooperative NOMA that fully exploits prior information about other users’ messages and reports analytical performance gains. It also identifies user pairing as relevant to practical NOMA performance.
- The proposed cooperative NOMA transmission scheme fully exploits prior information about other users’ messages.
- Analytical results demonstrate performance gains for the cooperative NOMA scheme.
- Figure 3 evaluates outage probability for cooperative NOMA without local short-range communications at R1 = 1.2 BPCU and R2 = 1.9 BPCU.
- Figure 4 investigates the impact of user pairing on the sum rate with K = 10.