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Resource Allocation for D2D Communications Underlaying a NOMA-Based Cellular Network
Yijin Pan, Cunhua Pan, Zhaohui Yang, Ming Chen
TL;DR
The paper studies D2D spectrum sharing with NOMA cellular users while preserving SIC decoding order and meeting cellular minimum-rate requirements. It derives cellular-user power conditions and proposes a dual-based iterative resource-allocation algorithm; simulations show the proposed scheme outperforms conventional OMA.
Problem
D2D reuse with NOMA-based cellular users complicates co-channel interference and may disrupt SIC decoding order, while the resulting resource-allocation problem has not been studied in the cited prior work.
Source: §I · p. 2Method
The paper derives optimal cellular-user power conditions, then uses a dual-based iterative algorithm for D2D power control and channel assignment.
Source: §I · p. 2, §III · p. 5Results
The simulations report that the NOMA-based scheme outperforms MCU-OFDMA in D2D sum rate, especially as the number of multiplexed CUs per subchannel grows.
Source: §IV · p. 9Takeaways & Limitations
The conclusion reports that the D2D-underlaid NOMA network still outperforms the conventional scheme for networks with high data requirements and many users despite added power constraints to preserve decoding order.
Source: §V · p. 9
Abstract
from arXiv · showhide
This letter investigates the power control and channel assignment problem in device-to-device (D2D) communications underlaying a non-orthogonal multiple access (NOMA) cellular network. With the successive interference cancellation decoding order constraints, our target is to maximize the sum rate of D2D pairs while guaranteeing the minimum rate requirements of NOMA-based cellular users. Specifically, the optimal conditions for power control of cellular users on each subchannel are derived first. Then, based on these results, we propose a dual-based iterative algorithm to solve the resource allocation problem. Simulation results validate the superiority of proposed resource allocation algorithm over the existing orthogonal multiple access scheme.
I. INTRODUCTION
D2D spectrum reuse can improve efficiency, and changing uplink–downlink traffic patterns motivate studying D2D underlay in downlink cellular networks. This work addresses D2D sharing with NOMA cellular users while preserving SIC decoding order and meeting cellular rate requirements.
I. INTRODUCTION
- Downlink D2D underlay warrants study as high-rate uplink applications make traffic less asymmetric than conventional networks assume.Conventional networks normally allocate uplink resources to D2D because downlink traffic is heavier.Source: §I · p. 1
- NOMA multiplexes multiple cellular users on a subchannel through different power levels and SIC, with the aim of increasing throughput and supporting massive connectivity.The paper distinguishes its setting from, where NOMA is implemented in D2D transmissions.Source: §I · pp. 1–2
- Combining D2D reuse with NOMA-based cellular users complicates co-channel interference and can disrupt the users’ SIC decoding order.Prior D2D-assisted NOMA work either groups D2D users through NOMA or uses exclusive channels for D2D pairs.Source: §I · p. 2
- The paper targets maximizing D2D-pair sum rate while meeting cellular users’ minimum-rate requirements under SIC decoding-order constraints.It derives optimal cellular-user power conditions, then proposes a dual-based iterative resource-allocation algorithm; simulations report gains over conventional OMA.Source: §I · p. 2
II. SYSTEM MODEL AND PROBLEM FORMULATION
The system combines downlink NOMA cellular users with underlaid D2D pairs sharing subchannels. Its formulation protects the SIC decoding order, enforces rate and power requirements, and maximizes D2D sum rate.
II. SYSTEM MODEL AND PROBLEM FORMULATION
- The model has a base station serving cellular users on N subchannels, with M users multiplexed per subchannel and K randomly distributed underlaid D2D pairs.CUs are multiplexed by power-domain splitting, and K ≤ N.Source: §II · pp. 2–3
- The SIC order follows increasing BS-to-CU channel gains, while underlaid D2D interference can affect that decoding order.The assumed channel gains are known through feedback.Source: §II · p. 3
- D2D interference must preserve the NOMA SIC order: a CU decoding another user’s signal needs received SINR at least as large as that user’s own SINR.The paper reduces the decoding-order conditions to M − 1 constraints per subchannel.Source: §II · pp. 3–4
- The optimization maximizes D2D-pair sum rate subject to cellular minimum-rate requirements, transmit-power limits, and channel-assignment constraints.To limit computation and signaling overhead, the model assigns each subchannel to at most one D2D pair, although allowing multiple pairs could improve spectrum efficiency.Source: §II · p. 4
III. POWER CONTROL AND CHANNEL ASSIGNMENT
The solution first derives optimal NOMA cellular-user power conditions on each subchannel, then uses a dual-based iterative method for D2D power control and channel assignment.
III. POWER CONTROL AND CHANNEL ASSIGNMENT
- The proposed solution first investigates optimal cellular-user power conditions per subchannel, then applies a dual-based iterative method to determine D2D power control and channel assignment.Source: §III · p. 5
A. Optimal Power Control for CUs
For a subchannel assigned to a D2D pair, the paper derives optimal cellular-user transmit powers. The given rate constraints bind at the optimum, and cumulative powers are introduced to obtain explicit expressions.
A. Optimal Power Control for CUs
- For a subchannel assigned to a D2D pair, the subsection derives optimal transmit-power conditions for cellular users.Source: A. Optimal Power Control for CUs · p. 5
- Each cellular user’s minimum-rate constraint holds with equality at its optimal transmit power; otherwise, reducing that power can improve the D2D-pair sum rate.The passage states this condition for CU i and cites,.Source: A. Optimal Power Control for CUs · p. 5
- Because the optimal power expression is not readily explicit, the derivation introduces S_i as the sum of transmit powers from CU i through CU M and uses recursive relations.Source: A. Optimal Power Control for CUs · p. 5
B. D2D Power Control and Channel Assignment
The section derives D2D power and channel allocation through a dual-based iterative method, using cellular-user power conditions while preserving SIC decoding order. The resulting subgradient method converges to the optimal solution of the transformed problem for sufficiently small step sizes.
B. D2D Power Control and Channel Assignment
- Cellular-user transmit powers are determined by the transmit power of the multiplexed D2D pair.This relation is used to simplify the power constraint when a subchannel is assigned to a D2D pair.Source: B. D2D Power Control and Channel… · p. 6
- The D2D transmit-power constraint protects the cellular users’ SIC decoding order, which the derived conditions always satisfy.The constraint is applied when a D2D pair shares a subchannel with cellular users.Source: B. D2D Power Control and Channel… · p. 6
- The nonconvex P2 is transformed into convex P3 using an auxiliary variable and the perspective property, enabling a standard dual method.The text locates P2’s nonconvexity in constraints (25a) and (6), and describes P3 over a triangular region.Source: B. D2D Power Control and Channel… · p. 7
- For sufficiently small step sizes, the subgradient method converges to P3’s optimal solution, and the derivation is summarized as DBIRA.DBIRA is the proposed iterative resource-allocation algorithm for solving P1.Source: B. D2D Power Control and Channel… · p. 8
IV. SIMULATION RESULTS
Simulations compare the proposed NOMA-based scheme with MCU-OFDMA and examine convergence across different numbers of multiplexed cellular users. NOMA-based allocation achieves higher D2D sum rate, particularly at larger multiplexing levels, while DBIRA converges within 20 iterations in the considered cases.
IV. SIMULATION RESULTS
- The simulations use a 500 m × 500 m cell with the base station at its center, and compare against MCU-OFDMA with joint power control and channel assignment from [4].The D2D transmitter–receiver distance is at most 30 m; results are averaged over 1000 random realizations.Source: §IV · p. 8
- The D2D sum-rate performance converges within 20 iterations for all three considered cases.The sum rate monotonically increases during the initial iterations.Source: §IV · p. 9
- The NOMA-based scheme outperforms MCU-OFDMA in D2D sum rate, especially when more cellular users are multiplexed on each subchannel.The text attributes the comparison to lower cellular-user transmit power, and hence less interference to D2D pairs, under NOMA; D2D sum rate also decreases as cellular minimum-rate requirements rise.Source: §IV · p. 9
V. CONCLUSION
The conclusion reports that D2D underlaying NOMA outperforms the conventional scheme in high-demand, many-user networks despite additional power constraints for NOMA decoding order.
V. CONCLUSION
- The D2D underlaying NOMA network outperforms the conventional scheme with high data requirements and many users.The conclusion notes that this holds despite additional D2D power constraints for the NOMA decoding order.Source: §V · p. 9
- Additional D2D power constraints are introduced to preserve the NOMA decoding order.Source: §V · p. 9
- Fig. 1 covers DBIRA convergence, while Fig. 2 plots D2D sum rate against cellular users’ rate requirements.Source: Figure 1 · p. 10, Figure 2 · p. 10