Accurate channel estimation for multiple cells is essential in downlink coordinated multi-point (CoMP) transmission/reception. Therefore, this paper investigates a technique to improve the channel estimation for downlink CoMP in Long-Term Evolution (LTE)-Advanced. In particular, the performance of data signal muting, i.e., muting data signals that collide with the channel state information reference signal (CSI-RS) of a neighboring cell, is evaluated considering various CoMP schemes and intra-eNodeB and inter-eNodeB CoMP scenarios. In a multi-cell link level simulation, coordinated scheduling and coordinated beamforming (CS/CB) CoMP is employed. The simulation results show that data signal muting is effective in improving the channel estimation accuracy, which is confirmed by numerical analysis. Simulation results also show that it is effective in improving the throughput performance, especially for sets of user equipment at the cell boundary. Furthermore, the tradeoff relationship between accurate channel estimation by muting larger numbers of data signals and a high peak data rate, i.e., low overhead, is investigated. It is shown that when the number of coordinated cells is set to three, the CSI-RS reuse factor is set to three, and the well-planned CSI-RS pattern allocation is employed, the improvement in performance is almost saturated in a synchronized network.

A distributed antenna system, where the antennas of a base station are spatially distributed throughout the cell, can achieve better throughput at the cell edge than a centralized antenna system. On the other hand, the peak throughput degrades in general because each remote antenna unit has only a few antennas. To achieve both high peak and cell-edge throughputs, we need to increase the total number of antennas. However, this is not easy due to the pilot resource limitation when we use frequency division duplexing. In this paper, we propose using more antennas than pilot resources. The number mismatch between antennas and signals is solved by using a connection matrix. Here, we test two types of connection matrix: signal-distributing and signal-switching. Simulation results show that the sum throughput is improved by increasing the number of antenna elements per remote antenna unit under a constraint on the same number of pilot resources.

The interference rejection combining (IRC) receiver, which can suppress inter-cell interference, is effective in improving the cell-edge user throughput. The IRC receiver is typically based on the minimum mean square error (MMSE) criteria, which requires highly accurate channel estimation and covariance matrix estimation that includes the inter-cell interference. This paper investigates the gain from the IRC receiver in terms of the downlink user throughput performance in a multi-cell environment. In the evaluation, to assess the actual gain, the inter-cell interference signals including reference signals from the surrounding 56 cells are generated in the same way as the desired signals, and the channel propagation from all of the cells is explicitly taken into account considering pathloss, shadowing, and multipath fading. The results of simulations that assume the inter-site distance of 500 m, the spatial correlation at the transmitter and the receiver of 0.5, and the numbers of transmitter and receiver antennas of 2 and 2, respectively, show that the IRC receiver improves the cell-edge user throughput (defined as the 5% value in the cumulative distribution function) by approximately 15% compared to the simplified MMSE receiver that approximates the inter-cell interference as AWGN, at the cost of a drop in the average user throughput due to less accurate channel and covariance matrices. Furthermore, we consider dynamic switching between the IRC receiver and the simplified MMSE receiver according to the number of streams and modulation and coding scheme levels. The results show that with dynamic switching, both the cell-edge throughput and average user throughput are improved to the same level as that for the IRC receiver and the simplified MMSE receiver, respectively. Therefore, the best performance can be achieved by employing the dynamic switching in all throughput regions.

This paper investigates the dominant impact on the interference rejection combining (IRC) receiver due to the downlink reference signal (RS) based covariance matrix estimation scheme. When the transmission modes using the cell-specific RS (CRS) in LTE/LTE-Advanced are assumed, the property of the non-precoded CRS is different from that of the data signals. This difference poses two problems to the IRC receiver. First, it results in different levels of accuracy for the RS based covariance matrix estimation. Second, assuming the case where the CRS from the interfering cell collides with the desired data signals of the serving cell, the IRC receiver cannot perfectly suppress this CRS interference. The results of simulations assuming two transmitter and receiver antenna branches show that the impact of the CRS-to-CRS collision among cells is greater than that for the CRS interference on the desired data signals especially in closed-loop multiple-input multiple-output (MIMO) systems, from the viewpoint of the output signal-to-interference-plus-noise power ratio (SINR). However, the IRC receiver improves the user throughput by more than 20% compared to the conventional maximal ratio combining (MRC) receiver under the simulation assumptions made in this paper even when the CRS-to-CRS collision is assumed. Furthermore, the results verify the observations made in regard to the impact of inter-cell interference of the CRS for various average received signal-to-noise power ratio (SNR) and signal-to-interference power ratio (SIR) environments.

For multiple-input multiple-output (MIMO) precoded transmission that has individual constraints on the maximum power of each transmit antenna or a subset of transmit antennas, the transmit power optimization problem is a non-linear convex optimization problem with a high level of computational complexity. In this paper, assuming the use of the interior point method (IPM) to solve this problem, we propose two efficient techniques that reduce the computational complexity of the IPM by appropriately setting its parameters. Based on computer simulation, the achieved reductions in the level of the computational complexity are evaluated using the proposed techniques for both the fairness and the sum-rate maximization criteria assuming i.i.d Rayleigh fading MIMO channels and block diagonalization zero-forcing as a multi-user MIMO (MU-MIMO) precoder.

The interference rejection combining (IRC) receiver effectively improves the cell-edge user throughput by suppressing interference from the surrounding cells. The work item (WI) for the specification of the IRC receiver is now ongoing for Release 11 Long-Term Evolution (LTE)-Advanced. Furthermore, heterogeneous networks where low power nodes such as picocells are overlaid onto macrocells are important to further improve the system throughput per unit area. In heterogeneous networks, to achieve an offloading gain from macrocells to picocells, cell range expansion (CRE) is applied. Additionally, inter-cell interference coordination (ICIC) is applied to reduce the severe inter-cell interference imposed from the macrocells onto the sets of user equipment (UEs) connected to picocells. In such cases, the interference statistics are completely different from traditional well-planned macrocell deployments, which have been investigated for the IRC receiver. This paper clarifies the effect of the IRC receiver in a heterogeneous network employing CRE and ICIC. Simulation results show that when both CRE and ICIC are applied, the effect of the IRC receiver becomes small due to a reduction in the severe inter-cell interference from ICIC. However, we clarify that the user throughput gain at the cumulative distribution function of 5% from the IRC receiver exceeding 10% is achieved compared to the conventional minimum mean square error (MMSE) receiver in a heterogeneous network regardless of the usage of ICIC. Furthermore, in heterogeneous networks employing CRE and ICIC, we clarify that an average user throughput gain exceeding 5% is achieved from the IRC receiver and the improvement in the average user throughput is high especially for the UEs connected to picocells compared to UEs connected to macrocells.

The interference rejection combining (IRC) receiver, which can suppress inter-cell interference, is effective in improving the cell-edge user throughput. The IRC receiver is typically based on the minimum mean square error (MMSE) criteria, and requires a covariance matrix including the interference signals, in addition to a channel matrix from the serving cell. Therefore, in order to clarify the gain from the IRC receiver, the actual estimation error of these matrices should be taken into account. In a system performance evaluation, the link performance modeling of the IRC receiver, i.e., the output signal-to-interference-plus-noise power ratio (SINR) after IRC reception including the estimation errors, is very important in evaluating the actual performance of the IRC receiver in system level simulations. This is because these errors affect the suppression of the interference signals for the IRC receiver. Therefore, this paper investigates and proposes IRC receiver modeling schemes for the covariance matrix and channel estimation errors. As the modeling scheme for the covariance matrix, we propose a scheme that averages the conventional approximation using the complex Wishart distribution in the frequency domain to address issues that arise in a frequency selective fading channel. Furthermore, we propose a modeling scheme for the channel estimation error according to the ideal channel response of all cells and a channel estimation filter to address channel fading fluctuations. The results of simulations assuming the LTE/LTE-Advanced downlink with two transmitter and receiver antenna branches show that the proposed modeling scheme for the covariance matrix estimation error accurately approximates the performance of a realistic IRC receiver, which estimates the covariance matrix and channel matrix of the serving cell based on the demodulation reference signal (DM-RS), even in a frequency selective fading channel. The results also show that the proposed modeling scheme for the channel estimation error is a robust scheme in terms of the r.m.s. delay spread of a channel model compared to the scheme using the mean square error (MSE) statistic of the estimated channel coefficients based on a channel estimation filter.