3,624 research outputs found

    Resource allocation for NOMA wireless systems

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    Power-domain non-orthogonal multiple access (NOMA) has been widely recognized as a promising candidate for the next generation of wireless communication systems. By applying superposition coding at the transmitter and successive interference cancellation at the receiver, NOMA allows multiple users to access the same time-frequency resource in power domain. This way, NOMA not only increases the system’s spectral and energy efficiencies, but also supports more users when compared with the conventional orthogonal multiple access (OMA). Meanwhile, improved user fairness can be achieved by NOMA. Nonetheless, the promised advantages of NOMA cannot be realized without proper resource allocation. The main resources in wireless communication systems include time, frequency, space, code and power. In NOMA systems, multiple users are accommodated in each time/frequency/code resource block (RB), forming a NOMA cluster. As a result, how to group the users into NOMA clusters and allocate the power is of significance. A large number of studies have been carried out for developing efficient power allocation (PA) algorithms in single-input single-output (SISO) scenarios with fixed user clustering. To fully reap the gain of NOMA, the design of joint PA and user clustering is required. Moreover, the study of PA under multiple-input multiple-output (MIMO) systems still remains at an incipient stage. In this dissertation, we develop novel algorithms to allocate resource for both SISO-NOMA and MIMO-NOMA systems. More specifically, Chapter 2 compares the system capacity of MIMO-NOMA with MIMO-OMA. It is proved analytically that MIMO-NOMA outperforms MIMO-OMA in terms of both sum channel capacity and ergodic sum capacity when there are multiple users in a cluster. Furthermore, it is demonstrated that the more users are admitted to a cluster, the lower is the achieved sum rate, which illustrates the tradeoff between the sum rate and maximum number of admitted users. Chapter 3 addresses the PA problem for a general multi-cluster multi-user MIMONOMA system to maximize the system energy efficiency (EE). First, a closed-form solution is derived for the corresponding sum rate (SE) maximization problem. Then, the EE maximization problem is solved by applying non-convex fractional programming. Chapter 4 investigates the energy-efficient joint user-RB association and PA problem for an uplink hybrid NOMA-OMA system. The considered problem requires to jointly optimize the user clustering, channel assignment and power allocation. To address this hard problem, a many-to-one bipartite graph is first constructed considering the users and RBs as the two sets of nodes. Based on swap matching, a joint user-RB association and power allocation scheme is proposed, which converges within a limited number of iterations. Moreover, for the power allocation under a given user-RB association, a low complexity optimal PA algorithm is proposed. Furthermore, Chapter 5 focuses on securing the confidential information of massive MIMO-NOMA networks by exploiting artificial noise (AN). An uplink training scheme is first proposed, and on this basis, the base station precodes the confidential information and injects the AN. Following this, the ergodic secrecy rate is derived for downlink transmission. Additionally, PA algorithms are proposed to maximize the SE and EE of the system. Finally, conclusions are drawn and possible extensions to resource allocation in NOMA systems are discussed in Chapter 6

    Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks

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    Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be promising in the fifth generation (5G) wireless networks. H-CRANs enable users to enjoy diverse services with high energy efficiency, high spectral efficiency, and low-cost operation, which are achieved by using cloud computing and virtualization techniques. However, H-CRANs face many technical challenges due to massive user connectivity, increasingly severe spectrum scarcity and energy-constrained devices. These challenges may significantly decrease the quality of service of users if not properly tackled. Non-orthogonal multiple access (NOMA) schemes exploit non-orthogonal resources to provide services for multiple users and are receiving increasing attention for their potential of improving spectral and energy efficiency in 5G networks. In this article a framework for energy-efficient NOMA H-CRANs is presented. The enabling technologies for NOMA H-CRANs are surveyed. Challenges to implement these technologies and open issues are discussed. This article also presents the performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure

    Pattern Division Multiple Access with Large-scale Antenna Array

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    In this paper, pattern division multiple access with large-scale antenna array (LSA-PDMA) is proposed as a novel non-orthogonal multiple access (NOMA) scheme. In the proposed scheme, pattern is designed in both beam domain and power domain in a joint manner. At the transmitter, pattern mapping utilizes power allocation to improve the system sum rate and beam allocation to enhance the access connectivity and realize the integration of LSA into multiple access spontaneously. At the receiver, hybrid detection of spatial filter (SF) and successive interference cancellation (SIC) is employed to separate the superposed multiple-domain signals. Furthermore, we formulate the sum rate maximization problem to obtain the optimal pattern mapping policy, and the optimization problem is proved to be convex through proper mathematical manipulations. Simulation results show that the proposed LSA-PDMA scheme achieves significant performance gain on system sum rate compared to both the orthogonal multiple access scheme and the power-domain NOMA scheme.Comment: 6 pages, 5 figures, this paper has been accepted by IEEE VTC 2017-Sprin
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