Boya Di

Sub-Channel Assignment, Power Allocation, and User Scheduling for Non-Orthogonal Multiple Access Networks

In this paper, we study the resource allocation and user scheduling problem for a downlink non-orthogonal multiple access network where the base station allocates spectrum and power resources to a set of users. We aim to jointly optimize the sub-channel assignment and power allocation to maximize the weighted total sum-rate while taking into account user fairness. We formulate the sub-channel allocation problem as equivalent to a many-to-many two-sided user-subchannel matching game in which the set of users and sub-channels are considered as two sets of players pursuing their own interests. We then propose a matching algorithm, which converges to a two-side exchange stable matching after a limited number of iterations. A joint solution is thus provided to solve the sub-channel assignment and power allocation problems iteratively. Simulation results show that the proposed algorithm greatly outperforms the orthogonal multiple access scheme and a previous non-orthogonal multiple access scheme.

Radio Resource Allocation for Downlink Non-Orthogonal Multiple Access (NOMA) Networks Using Matching Theory

In this paper, we study the resource allocation and scheduling problem for a downlink non- orthogonal multiple access (NOMA) network where the base station (BS) allocates the spectrum resources and power to the set of users. We aim to optimize the sub-channel assignment and power allocation to achieve a balance between the number of scheduled users and total sum-rate maximization. To solve the above problem, we propose a many-to-many two-sided user-subchannel matching algorithm in which the set of users and sub-channels are considered as two sets of players pursuing their own interests. The algorithm converges to a pair-wise stable matching after a limited number of iterations. Simulation results show that the proposed algorithm can approach the performance of the upper bound and greatly outperforms the OFDMA scheme.

Incentive mechanism for collaborative smartphone sensing using overlapping coalition formation games

With the rapid growth of sensor technology, smartphone sensing has become an effective approach to help improve the quality of applications in smartphones. However, the quality and quantity of the sensed data uploaded by the users are not always satisfying due to the lack of incentives for users to participate. In this paper, we design an incentive mechanism in which the users can get satisfying rewards from the platform by efficiently allocating their resources, and meanwhile, the platform can achieve a relatively high social welfare. Specifically, to solve the resource allocation problem in the incentive mechanism, we consider a cooperative game model with overlapping coalitions, in which the smartphone users can self-organize into the overlapping coalitions for different sensing tasks. Then, we propose a distributed algorithm that converges to a stable outcome in which no user has the motivation to change its current resource allocation so as to increase its individual payoff unilaterally. Simulation results show that the proposed scheme achieves a better performance than the average distribution case and the single-task distribution case in various conditions.

Radio resource allocation for non-orthogonal multiple access (NOMA) relay network using matching game

In this paper, we study the resource allocation problem for a single-cell non-orthogonal multiple access (NOMA) relay network where an OFDM amplify-and-forward (AF) relay allocates the spectrum and power resources to the source-destination (SD) pairs. We aim to optimize the spectrum and power resource allocation to maximize the total sum-rate. This is a very complicated problem and the optimal approach requires an exhaustive search, leading to a NP hard problem. To solve this problem, we propose an efficient many-to-many two sided SD pair-subchannel matching algorithm in which the SD pairs and sub-channels are considered as two sets of rational and selfish players chasing their own interests. The algorithm converges to a pair-wise stable matching after a limited number of iterations with a low complexity compared with the optimal solution. Simulation results show that the sum-rate of the proposed algorithm approaches the performance of the optimal exhaustive search and significantly outperforms the conventional orthogonal multiple access scheme, in terms of the total sum-rate and number of accessed SD pairs.

Sub-Channel and Power Allocation for Non-Orthogonal Multiple Access Relay Networks With Amplify-and-Forward Protocol

In this paper, we study the resource allocation problem for a single-cell non-orthogonal multiple access (NOMA) relay network where an OFDM amplify-and-forward relay allocates the spectrum and power resources to the source–destination (SD) pairs. We aim to optimize the resource allocation to maximize the average sum-rate. The optimal approach requires an exhaustive search, leading to an NP-hard problem. To solve this problem, we propose two efficient many-to-many two-sided SD pair-subchannel matching algorithms, in which the SD pairs and sub-channels are considered as two sets of players chasing their own interests. The proposed algorithms can provide a sub-optimal solution to this resource allocation problem in affordable time. Both the static matching algorithm and the dynamic matching algorithm converge to a pair-wise stable matching after a limited number of iterations. Simulation results show that the capacity of both proposed algorithms in the NOMA scheme significantly outperforms the conventional orthogonal multiple access scheme. The proposed matching algorithms in NOMA scheme also achieve a better user-fairness performance than the conventional orthogonal multiple access.

Radio resource allocation for uplink sparse code multiple access (SCMA) networks using matching game

In this paper, we study the codebook-based resource allocation problem for an uplink sparse code multiple access (SCMA) network. The base station (BS) assigns to each user a set of subcarriers corresponding to a specific codebook, and each user performs power control over multiple subcarriers. We aim to optimize the subcarrier assignment and power allocation to maximize the total sum-rate. To solve the above problem, we formulate it as a many-to-many two-sided matching problem with externalities. A novel swap-matching algorithm is then proposed in which the users and the subcarriers are considered as two sets of players, and every two users can cooperate to swap their matches so as to improve each others profits. The algorithm converges to a pair-wise stable matching after a limited number of iterations. Simulation results show that the proposed algorithm greatly outperforms the orthogonal multiple access scheme and a random allocation scheme.

Joint User Pairing, Subchannel, and Power Allocation in Full-Duplex Multi-User OFDMA Networks

In this paper, the resource allocation and scheduling problem for a full-duplex (FD) orthogonal frequency-division multiple-access network is studied where an FD base station simultaneously communicates with multiple pairs of uplink (UL) and downlink (DL) half-duplex (HD) users bidirectionally. In this paper, we aim to maximize the network sum-rate through joint UL and DL user pairing, OFDM subchannel assignment, and power allocation. We formulate the problem as a non-convex optimization problem. The optimal algorithm requires an exhaustive search, which will become prohibitively complicated as the numbers of users and subchannels increase. To tackle this complex problem more efficiently, we formulate the user-pairing and subchannel allocation problem as a three-sided matching problem, and propose a novel low-complexity near-optimal matching algorithm. The algorithm is analyzed, and we prove that it converges to a stable matching. Simulation results show that the FD scheme can significantly improve the spectrum efficiency compared with the HD scheme. The proposed algorithm performs very close to the optimal algorithm, and significantly outperforms other resource allocation schemes.

Collaborative Smartphone Sensing Using Overlapping Coalition Formation Games

With the rapid growth of sensor technology, smartphone sensing has become an effective approach to improve the quality of smartphone applications. However, due to time-varying wireless channels and lack of incentives for the users to participate, the quality and quantity of the data uploaded by the smartphone users are not always satisfying. In this paper, we consider a smartphone sensing system in which a platform publicizes multiple tasks, and the smartphone users choose a set of tasks to participate in. In the traditional non-cooperative approach with incentives, each smartphone user gets rewards from the platform as an independent individual and the limit of the wireless channel resources is often omitted. To tackle this problem, we introduce a novel cooperative approach with an overlapping coalition formation game (OCF-game) model, in which the smartphone users can cooperate with each other to form the overlapping coalitions for different sensing tasks. We also utilize a centralized case to describe the upper bound of the system sensing performance. Simulation results show that the cooperative approach achieves a better performance than the non-cooperative one in various situations.

Non-Orthogonal Multiple Access for High-Reliable and Low-Latency V2X Communications in 5G Systems

In this paper, we consider a dense vehicular communication network where each vehicle broadcasts its safety information to its neighborhood in each transmission period. Such applications require low latency and high reliability, and thus, we exploit non-orthogonal multiple access to reduce the access latency and to improve the packet reception probability. In the proposed two-fold scheme, the BS performs semi-persistent scheduling and allocates time-frequency resources in a non-orthogonal manner while the vehicles autonomously perform distributed power control with iterative signaling control. We formulate the centralized scheduling and resource allocation problem as equivalent to a multi-dimensional stable roommate matching problem, in which the users and time/frequency resources are considered as disjoint sets of objects to be matched with each other. We then develop a novel rotation matching algorithm, which converges to an

Cross-Layer Protocol Design for Distributed Full-Duplex Network

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