Abstract
Multicast beamforming is a key technology for next-generation wireless cellular networks to support high-rate content distribution services. In this letter, the coordinated downlink multicast beamforming design in multicell networks is considered. The goal is to maximize the minimum signal-to-interference-plus-noise ratio of all users under individual base station power constraints. We exploit the fractional form of the objective function and geometric properties of the constraints to reformulate the problem as a parametric manifold optimization program. Afterwards we propose a low-complexity Dinkelbach-type algorithm combined with adaptive exponential smoothing and Riemannian conjugate gradient iteration, which is guaranteed to converge. Numerical experiments show that the proposed algorithm outperforms the existing SDP-based method and DC-programming-based method and achieves near-optimal performance.
| Original language | English |
|---|---|
| Article number | 7898517 |
| Pages (from-to) | 1673-1676 |
| Number of pages | 4 |
| Journal | IEEE Communications Letters |
| Volume | 21 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Jul 2017 |
| Externally published | Yes |
Keywords
- Multicast beamforming
- Riemannian conjugate gradient
- manifold optimization
- max-min fair
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