A Quasi-Optimal Clustering Algorithm for MIMO-NOMA Downlink Systems
In this letter we consider a resource allocation problem for multi-user MIMO non orthogonal multiple access (MU-MIMO-NOMA) downlink transmissions. Under the NOMA paradigm, users are organized in clusters of strong/weak pair and our aim is to find an optimal clustering, beamforming and power allocati...
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| Vydané v: | IEEE wireless communications letters Ročník 9; číslo 2; s. 152 - 156 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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01.02.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| Abstract | In this letter we consider a resource allocation problem for multi-user MIMO non orthogonal multiple access (MU-MIMO-NOMA) downlink transmissions. Under the NOMA paradigm, users are organized in clusters of strong/weak pair and our aim is to find an optimal clustering, beamforming and power allocation scheme to minimize the power transmitted subject to a rate constraint for each user. Since the joint optimization problem is intractable, we split it in three sub-problems: clustering, which is formulated as a mixed integer linear programming (MILP) problem, beamforming and power allocation. Simulations results show that the our proposed scheme greatly outperforms both the classical OMA scheme and state-of-the-art NOMA techniques. |
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| AbstractList | In this letter we consider a resource allocation problem for multi-user MIMO non orthogonal multiple access (MU-MIMO-NOMA) downlink transmissions. Under the NOMA paradigm, users are organized in clusters of strong/weak pair and our aim is to find an optimal clustering, beamforming and power allocation scheme to minimize the power transmitted subject to a rate constraint for each user. Since the joint optimization problem is intractable, we split it in three sub-problems: clustering, which is formulated as a mixed integer linear programming (MILP) problem, beamforming and power allocation. Simulations results show that the our proposed scheme greatly outperforms both the classical OMA scheme and state-of-the-art NOMA techniques. |
| Author | Abrardo, Andrea Moretti, Marco Saggese, Fabio |
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| SubjectTerms | Algorithms Array signal processing Beamforming Clustering Computer simulation Covariance matrices Downlink Integer programming Interference Linear programming MIMO MIMO (control systems) Mixed integer NOMA non-orthogonal multiple access Nonorthogonal multiple access Optimization Receivers Resource allocation Resource management weighted bipartite matching |
| Title | A Quasi-Optimal Clustering Algorithm for MIMO-NOMA Downlink Systems |
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