Boosting Fronthaul Capacity: Global Optimization of Power Sharing for Centralized Radio Access Network

The limited fronthaul capacity imposes a challenge on the uplink of centralized radio access network (C-RAN). We propose to boost the fronthaul capacity of massive multiple-input multiple-output (MIMO) aided C-RAN by globally optimizing the power sharing between channel estimation and data transmission both for the user devices (UDs) and the remote radio units (RRUs). Intuitively, allocating more power to the channel estimation will result in more accurate channel estimates, which increases the achievable throughput. However, increasing the power allocated to the pilot training will reduce the power assigned to data transmission, which reduces the achievable throughput. In order to optimize the powers allocated to the pilot training and to the data transmission of both the UDs and the RRUs, we assign an individual power sharing factor to each of them and derive an asymptotic closed-form expression of the signal-to-interference-plus-noise for the massive MIMO aided C-RAN consisting of both the UD-to-RRU links and the RRU-to-baseband unit (BBU) links. We then exploit the C-RAN architecture's central computing and control capability for jointly optimizing the UDs' power sharing factors and the RRUs' power sharing factors aiming for maximizing the fronthaul capacity. Our simulation results show that the fronthaul capacity is significantly boosted by the proposed global optimization of the power allocation between channel estimation and data transmission both for the UDs and for their host RRUs. As a specific example of 32 receive antennas (RAs) deployed by RRU and 128 RAs deployed by BBU, the sum-rate of 10 UDs achieved with the optimal power sharing factors improves 33\% compared with the one attained without optimizing power sharing factors

Adaptive Coding and Modulation for Large-Scale Antenna Array Based Aeronautical Communications in the Presence of Co-channel Interference

This dataset supports the publication: Zhang, Jiankang; Chen, Sheng; Maunder, Robert; Zhang, Rong; Hanzo, Lajos. Adaptive Coding and Modulation for Large-Scale Antenna Array Based Aeronautical Communications in the Presence of Co-channel Interference. IEEE Transactions on Wireless Communications This dataset contains which are used for generating Fig.3 to Fig.9. These figures are plotted using GLE (Graphics Layout Engine). The scripts of Gle are also included in the folds for each figures. In order to generate these figures, you should install GLE http://glx.sourceforge.net/ </span

Adaptive coding and modulation for large-scale antenna array based aeronautical communications in the presence of co-channel interference

In order to meet the demands of ‘Internet above the clouds’, we propose a multiple-antenna aided adaptive coding and modulation (ACM) for aeronautical communications. The proposed ACM scheme switches its coding and modulation mode according to the distance between the communicating aircraft, which is readily available with the aid of the airborne radar or the global positioning system. We derive an asymptotic closed-form expression of the signal-to-interference-plus-noise ratio (SINR) as the number of transmitting antennas tends to infinity, in the presence of realistic co-channel interference and channel estimation errors. The achievable transmission rates and the corresponding mode-switching distance-thresholds are readily obtained based on this closed-form SINR formula. Monte-Carlo simulation results are used to validate our theoretical analysis. For the specific example of 32 transmit antennas and 4 receive antennas communicating at a 5 GHz carrier frequency and using6 MHz bandwidth, which are reused by multiple other pairs of communicating aircraft, the proposed distance-based ACM iscapable of providing as high as 65.928 Mbps data rate when the communication distance is less than 25 km