Abstract
This paper considers the quality-of-service (QoS)-based joint beamforming and compression design problem in the downlink cooperative cellular network, where multiple relay-like base stations (BSs), connected to the central processor via ratelimited fronthaul links, cooperatively transmit messages to the users. The problem of interest is formulated as the minimization of the total transmit power of the BSs, subject to all users' signal-to-interference-plus-noise ratio (SINR) constraints and all BSs' fronthaul rate constraints. In this paper, we first show that there is no duality gap between the considered joint optimization problem and its Lagrangian dual by showing the tightness of its semidefinite relaxation (SDR). Then, we propose an efficient algorithm based on the above duality result for solving the considered problem. The proposed algorithm judiciously exploits the special structure of an enhanced Karush-Kuhn-Tucker (KKT) conditions of the considered problem and approaches the solution that satisfies the enhanced KKT conditions via two fixed point iterations. Two key features of the proposed algorithm are: (1) it is able to detect whether the considered problem is feasible or not and find its globally optimal solution when it is feasible; (2) it is highly efficient because both of the fixed point iterations in the proposed algorithm are linearly convergent and function evaluations in the fixed point iterations are computationally cheap. Numerical results show the global optimality and efficiency of the proposed algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 2070-2086 |
| Number of pages | 17 |
| Journal | IEEE Transactions on Signal Processing |
| Volume | 73 |
| DOIs | |
| Publication status | Published - Apr 2025 |
Keywords
- Cooperative cellular network
- enhanced Karush-Kuhn-Tucker (KKT) conditions
- fixed point iteration
- Lagrangian duality
- tightness of semidefinite relaxation (SDR)
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering