Coordinated beamforming for sum rate maximization in multi-cell downlink systems

• The downlink SRMax problem subject to a total power constraint is investigated.
• A new convex approximation dual form of the primal problem is then obtained.
• An efficient algorithm is then proposed to solve the convex dual problem.
• The SRMax problem subject to per-BS power constraints is also solved.
• The convergence and the computational complexity are analyzed.

In this paper, we propose novel approaches to maximize the sum rate in a multi-cell multi-input single-output (MISO) downlink system. First, considering a total power constraint, the uplink–downlink duality theory and the convex approximation approach are used to recast the original non-convex problem into an approximate problem of minimizing the sum of weighted inverse signal-to-interference-plus-noise-ratio (SINR). Then a lower complexity alternative optimization method with provable convergence is developed to solve this problem. Further, considering per-BS power constraints, the above algorithm is generalized and two novel lower complexity block coordinated beamforming methods are proposed to solve the sum rate maximization problem. Numerical results validate the effectiveness of the proposed algorithms and show that our algorithms converge to near-optimal performance within just a couple of iterations.