Base Station Cooperative Transmission Research Articles

Cooperative Caching in HetNets With Mutual Information Accumulation

Caching is a promising technique in the next generation cellular network, reducing backhaul traffic while improving network efficiency. In this letter, we introduce a cache-enabled small base station cooperative transmission scheme while considering the macro base station (MBS) silence and mutual information accumulation (MIA). A tractable analytical framework for characterizing the successful transmission probability (STP) of the introduced scheme is described. The STP is maximized by optimizing the caching placement policy based on a constrained cross entropy optimization algorithm. Simulation results demonstrate that the proposed SBS cooperative transmission with MBS silence and MIA achieves higher STP than other compared schemes.

Feedback Overhead Analysis for Base Station Cooperative Transmission

In this paper, we analyze the feedback overhead of channel direction information for downlink coherent base station (BS) cooperative transmission. The per-cell codebooks are considered, which are of practice importance. Instead of analyzing the required number of bits for feedback to keep a constant rate loss, we analyze the required overhead to ensure a target average signal-to-interference-plus-noise ratio (SINR) of each user. To this end, we formulate an optimization problem of bit allocation among the codebooks for local and cross channels that minimizes the total number of bits under the constraint of the average SINR, and find the explicit expression of the solution. We proceed to study the impact of various system parameters and channel features on the overall feedback overhead. Analytical and simulation results reveal that the overhead scales linearly with the overall number of transmit antennas, but decreases with the grow of the cell-edge signal-to-noise ratio. Moreover, the overhead can be significantly reduced by exploiting the diverse performance requirements of the users and the heterogeneous channel features through allocating the number of bits for feedback among multiple users and multiple per-cell links. This provides useful insight for the feedback strategy design of BS cooperation systems.

Training Resource Allocation for User-Centric Base Station Cooperation Networks

User-centric base station (BS) cooperative transmission strives to satisfy the quality of service of each user no matter where the user is located. The resulting user-dependent cooperative clusters are inevitably overlapped. To minimize the mean square error of channel estimation assisting user-centric downlink cooperative transmission, the training signals sent from the BSs in each cluster or from the users selecting the same BS in their clusters should be mutually orthogonal. In this paper, we study the orthogonal training resource-allocation problem for user-centric cooperative network aiming at minimizing the overall training overhead. We find the optimal solution through a graph-theoretic approach. To provide a feasible solution for large-scale networks, a low-complexity algorithm is then proposed. Simulation results show that the algorithm performs closely to the optimal solution, and both provide remarkably higher net throughput than the system with fixed clustering.

Energy Efficient Downlink Cooperative Transmission With BS and Antenna Switching off

In this paper, we strive to improve the energy efficiency (EE) of downlink base station (BS) cooperative transmission systems by switching off some BSs and antennas and allocating power to the users according to the required data rate and channel of each user. To show the potential of EE gain, we first propose an optimal dynamic switching off scheme using instantaneous channel information that maximizes the EE under per-user data rate and per-BS power constraints. To provide a feasible scheme for practical systems, we proceed to propose a semi-dynamic scheme where the BS-antenna operation pattern selection is based on average channel gains. Low complexity iterative algorithms are provided to find solutions for the dynamic and semi-dynamic strategies. Simulation results with typical circuit power consumption show that the semi-dynamic scheme performs close to the dynamic scheme and both schemes provide a substantial EE gain over the scheme with all antennas at all BSs active, when the data rate requirement is low. By comparing the overall power consumption for the systems of two extreme cases in deploying the active antennas, we find that the scheme only switching off BSs is more cost-effective in terms of energy than the scheme switching off antennas when the data rate requirement is low and the number of active antennas far exceeds that of the users.

Downlink Base Station Cooperative Transmission Under Limited-Capacity Backhaul

Coordinated multi-point transmission (CoMP) joint processing (CoMP-JP) is a promising technique for supporting high spectral efficiency in future cellular systems. However, this technique requires high-capacity backhaul links for connecting multiple base stations (BSs), which leads to high deployment costs. CoMP coordinated beamforming (CoMP-CB) needs less backhaul capacity, but with lower maximal multiplexing gain. In this paper, we study downlink CoMP strategies with limited-capacity backhaul. We start by investigating the optimal interference-free transmission strategy under backhaul rate constraints, where only a part of the data is shared among the BSs. We then study soft and hard switching between the CoMP-JP and CoMP-CB modes. Finally, a closed-form semi-dynamic distributed hard switching scheme is proposed, which depends on the local large-scale channel gains of the users. Simulation results show that both the soft and hard mode switching transmission perform closely to the optimal strategy and outperform the single-mode CoMP transmission especially when the backhaul capacity is very limited.

Impact of Nonorthogonal Training on Performance of Downlink Base Station Cooperative Transmission

Base station (BS) cooperative transmission is a promising technique to improve the spectral efficiency of cellular systems, and by using it, the channels become asymmetric in average gain. In this paper, we study the impact of the asymmetric channel gains on the performance of coherent cooperative transmission systems, when minimum mean square error (MMSE) and least square (LS) channel estimators are applied to jointly estimate the channel state information (CSI) under nonorthogonal training. We first derive an upper bound of rate loss caused by both channel estimation errors and CSI delay. We then analyze the mean square errors of the MMSE and LS estimators under both orthogonal and nonorthogonal training, which finally reveals the impact of different kinds of training on the precoding performance. It is shown that nonorthogonal training for the users in different cells leads to minor performance degradation for the MMSE channel-estimator-assisted downlink precoding. The performance degradation induced by channel estimation errors is almost independent of the user's location. By contrast, the performance loss caused by the CSI delay is more severe for users located at the cell center than that for users located at the cell edge. Our analysis is verified via simulation results.