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Register a new userA Fair Power Allocation Approach to NOMA in Multi-user SISO Systems
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Added by
Jose Armando Oviedo
Publication date
2017
fields
Informatics Engineering
and research's language is
English
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A non-orthogonal multiple access (NOMA) approach that always outperforms orthogonal multiple access (OMA) called Fair-NOMA is introduced. In Fair-NOMA, each mobile user is allocated its share of the transmit power such that its capacity is always greater than or equal to the capacity that can be achieved using OMA. For any slow-fading channel gains of the two users, the set of possible power allocation coefficients are derived. For the infimum and supremum of this set, the individual capacity gains and the sum-rate capacity gain are derived. It is shown that the ergodic sum-rate capacity gain approaches 1 b/s/Hz when the transmit power increases for the case when pairing two random users with i.i.d. channel gains. The outage probability of this approach is derived and shown to be better than OMA. The Fair-NOMA approach is applied to the case of pairing a near base-station user and a cell-edge user and the ergodic capacity gap is derived as a function of total number of users in the cell at high SNR. This is then compared to the conventional case of fixed-power NOMA with user-pairing. Finally, Fair-NOMA is extended to $K$ users and prove that the capacity can always be improved for each user, while using less than the total transmit power required to achieve OMA capacities per user.
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A non-orthogonal multiple access (NOMA) approach to user signal power allocation called Fair-NOMA is introduced. Fair-NOMA is the application of NOMA in such a way that two mobile users have the opportunity to always achieve at least the information capacity they can achieve by using orthogonal multiple access (OMA), regardless of the user selection criteria, making it suitable for implementation using any current or future scheduling paradigms. Given this condition, the bounds of the power allocation coefficients are derived as functions of the channel gains of the two mobile users. The NOMA power allocation is analyzed for two scheduled users that are selected randomly with i.i.d. channel gains. The capacity improvements made by each user and the sum capacity improvement are derived.
This paper investigates the application of non-orthogonal multiple access (NOMA) in millimeter wave (mmWave) communications by exploiting beamforming, user scheduling and power allocation. Random beamforming is invoked for reducing the feedback overhead of considered systems. A nonconvex optimization problem for maximizing the sum rate is formulated, which is proved to be NP-hard. The branch and bound (BB) approach is invoked to obtain the optimal power allocation policy, which is proved to converge to a global optimal solution. To elaborate further, low complexity suboptimal approach is developed for striking a good computational complexity-optimality tradeoff, where matching theory and successive convex approximation (SCA) techniques are invoked for tackling the user scheduling and power allocation problems, respectively. Simulation results reveal that: i) the proposed low complexity solution achieves a near-optimal performance; and ii) the proposed mmWave NOMA systems is capable of outperforming conventional mmWave orthogonal multiple access (OMA) systems in terms of sum rate and the number of served users.
The fundamental power allocation requirements for NOMA systems with minimum quality of service (QoS) requirements are investigated. For any minimum QoS rate $R_0$, the limits on the power allocation coefficients for each user are derived, such that any power allocation coefficient outside of these limits creates an outage with probability equal to 1. The power allocation coefficients that facilitate each users success of performing successive interference cancellation (SIC) and decoding its own signal are derived, and are found to depend only on the target rate $R_0$ and the number of total users $K$. It is then proven that using these power allocation coefficients create the same outage event as if using orthogonal multiple access (OMA), which proves that the outage performance of NOMA with a fixed-power scheme can matched that of OMA for all users simultaneously. Simulations confirm the theoretical results, and also demonstrate that a power allocation strategy exists that can improve the outage performance of NOMA over OMA, even with a fixed-power strategy.
For downlink multi-user non-orthogonal multiple access (NOMA) systems with successive interference cancellation (SIC) receivers, and a base-station not possessing the instantaneous channel gains, the fundamental relationship between the target rates and power allocation is investigated. It is proven that the total interference from signals not removed by SIC has a fundamental upper-limit which is a function of the target rates, and the outage probability is one when exceeding this limit. The concept of well-behaved power allocation strategies is defined, and its properties are proven to be derived solely based on the target rates. The existence of power allocation strategies that enable NOMA to outperform OMA in per-user outage probability is proven, and are always well-behaved for the case when the outage probability performance of NOMA and OMA are equal for all users. The proposed SIC decoding order is then shown to the most energy efficient. The derivation of well-behaved power allocation strategies that have improved outage probability performance over OMA for each user is outlined. Simulations validate the theoretical results, demonstrating that NOMA systems can always outperform OMA systems in outage probability performance, without relying on the exact channel gains.
In this work, we propose a globally optimal joint successive interference cancellation (SIC) ordering and power allocation (JSPA) algorithm for the sum-rate maximization problem in downlink multi-cell non-orthogonal multiple access (NOMA) systems. The proposed algorithm is based on the exploration of base stations (BSs) power consumption, and closed-form of optimal powers obtained for each cell. Although the optimal JSPA algorithm scales well with larger number of users, it is still exponential in the number of cells. For any suboptimal decoding order, we propose a low-complexity near-optimal joint rate and power allocation (JRPA) strategy in which the complete rate region of users is exploited. Furthermore, we design a near-optimal semi-centralized JSPA framework for a two-tier heterogeneous network such that it scales well with larger number of small-BSs and users. Numerical results show that JRPA highly outperforms the case that the users are enforced to achieve their channel capacity by imposing the well-known SIC necessary condition on power allocation. Moreover, the proposed semi-centralized JSPA framework significantly outperforms the fully distributed framework, where all the BSs operate in their maximum power budget. Therefore, the centralized JRPA and semi-centralized JSPA algorithms with near-to-optimal performance are good choices for larger number of cells and users.
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