Sparse Joint Transmission for Cloud Radio Access Networks With Limited Fronthaul Capacity
- Authors
- Han, Deokhwan; Park, Jeonghun; Park, Seok-Hwan; Lee, Namyoon
- Issue Date
- 5월-2022
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Downlink; Precoding; Optimization; Array signal processing; Noise measurement; Channel estimation; Quantization (signal); Cloud radio access network (C-RAN); cooperative transmission
- Citation
- IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, v.21, no.5, pp.3395 - 3408
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
- Volume
- 21
- Number
- 5
- Start Page
- 3395
- End Page
- 3408
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/141756
- DOI
- 10.1109/TWC.2021.3121398
- ISSN
- 1536-1276
- Abstract
- A cloud radio access network (C-RAN) is a promising cellular network, wherein densely deployed multi-antenna remote-radio-heads (RRHs) jointly serve many users using the same time-frequency resource. By extremely high signaling overheads for both channel state information (CSI) acquisition and data sharing at a baseband unit (BBU), finding a joint transmission strategy with a significantly reduced signaling overhead is indispensable to achieve the cooperation gain in practical C-RANs. In this paper, we present a novel sparse joint transmission (sparse-JT) method for C-RANs, where the number of transmit antennas per unit area is much larger than the active downlink user density. Considering the effects of noisy-and-incomplete CSI and the quantization errors in data sharing by a finite-rate fronthaul capacity, the key innovation of sparse-JT is to find a joint solution for cooperative RRH clusters, beamforming vectors, and power allocation to maximize a lower bound of the sum-spectral efficiency under the sparsity constraint of active RRHs. To find such a solution, we present a computationally efficient algorithm that guarantees to find a local-optimal solution for a relaxed sum-spectral efficiency maximization problem. By system-level simulations, we exhibit that sparse-JT provides significant gains in ergodic spectral efficiencies compared to existing joint transmissions.
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