Yusuke Ohwatari

Performance of Advanced Receiver Employing Interference Rejection Combining to Suppress Inter-Cell Interference in LTE-Advanced Downlink

The interference rejection combining (IRC) receiver is effective in improving the cell-edge user throughput because it suppresses inter-cell interference. The IRC receiver is typically based on the minimum mean square error (MMSE) criteria, which requires channel estimation and covariance matrix estimation including the inter-cell interference with high accuracy. The paper investigates the gain from the IRC receiver taking into account the estimation of the interference signal, i.e., the covariance matrix, in terms of the downlink user throughput performance in a multi-cell environment. For the estimation of the covariance matrix, two estimation schemes are considered one based on data signals and the other based on the demodulation reference signal (DM-RS). In the evaluation, to assess the actual gains of the two schemes, the inter-cell interference signals from the surrounding 56 cells are actually generated in the same way as the desired signals including reference signals, and the channel propagation from all of the cells is explicitly taken into account considering pathloss, shadowing, and multipath fading. The simulation results when the inter-site distance is 500 m and the numbers of transmitter and receiver antennas are 2 and 2, respectively, show that the IRC receiver employing the covariance matrix comprising the interference and noise component estimation improves the cell-edge user throughput (defined as the 5% value in the cumulative distribution function) by approximately 22% compared to the simplified MMSE receiver that approximates the inter-cell interference as AWGN, while the IRC receiver employing the full covariance matrix estimation degrades the average user throughput due to less accurate channel and covariance matrices.

Evaluation of user throughput for MU-MIMO coordinated wireless networks

Interference management is essential toward improving spectral efficiency in wireless networks. During the last decade inter-antenna interference management via multiple-input multiple output (MIMO) transmission has attracted attention for its capability to enhance link spectral efficiency. In a cellular environment, however, inter-cell interference imposes another limit on link spectral efficiency and for MIMO transmission in particular only a marginal portion of the expected gains is obtained. In this paper, as a candidate solution to reduce inter-cell interference and consequently enhance the gains achieved by MIMO, we investigate a coordinated wireless network where multiple base stations are connected to a central station that multiuser (MU)-MIMO precodes ongoing simultaneous transmissions from all coordinated base stations. Specifically, our main goal is to clarify the impact of coordination on spectral efficiency and evaluate user throughput with and without transmit power optimization, for both a hotspot scenario where all base stations can be coordinated (full coordination) and a cellular scenario where only the base stations grouped under the same cluster are coordinated (partial coordination).

Low-Complexity Detection Based on Belief Propagation in a Massive MIMO System

A very large MIMO system has a potential to achieve extremely-high system throughput. In general, however, algorithms detecting spatially-multiplexed signals require the complexity proportional to the cubed number of antenna elements in the least case. Thus, the implementation of an antenna array with an order of 100 elements becomes very difficult. In this paper, we focus on the algorithm which is based on belief propagation and implementable with the second-order calculations. The simulation results show that the algorithm provides very good BER performance in MIMO spatial multiplexing when the number of antenna elements is 100 and reasonably low complexity in comparison to the MMSE spatial filtering.

Investigation on Interference Rejection Combining Receiver for Space–Frequency Block Code Transmit Diversity in LTE-Advanced Downlink

The interference rejection combining (IRC) receiver, which can strictly suppress intercell interference based on the minimum mean square error (MMSE) criteria, is effective in improving cell-edge user throughput. When assuming the Long Term Evolution (LTE) or LTE-Advanced downlink and open-loop transmit diversity employing the space-frequency block code (SFBC) using Alamouti coding, the IRC receiver must detect the Alamouti coded signals and suppress the interference signals using a couple of received signals in the frequency domain at the same time. To achieve this, the IRC receiver weight matrix, which consists of the channel matrix of the serving cell and the statistics of the covariance matrix, including the interference and thermal noise components, must be extended in the frequency domain, i.e., due to the effect of Alamouti coding, in addition to the spatial domain. These extended matrices can be estimated using the downlink reference signals (RSs) from the serving cell. However, some elements, including the effect of Alamouti coding in the extended covariance matrix, cannot be estimated using a practical estimation scheme that subtracts the replica symbols of the serving cell generated by the estimated channel matrix and the known RS sequence from the received RSs of the serving cell. This is because the RSs in LTE/LTE-Advanced are not transmitted using two adjacent subcarriers. This paper investigates the statistics of these unknown elements and proposes appropriate values, specifically inserting zero values, for these elements assuming the LTE/LTE-Advanced downlink. The results of simulations show that the IRC receiver using the proposed scheme, which has two receiver antenna branches, suppresses the intercell interference and improves the throughput by more than 10% compared with that for the conventional maximal ratio combining (MRC) receiver when a cell-edge environment is assumed.

Investigation on Advanced Receiver Employing Interference Rejection Combining in Asynchronous Network for LTE-Advanced Downlink

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. To do this, the channel estimation and covariance matrix must be averaged within a subframe, i.e., 1 msec. However, the source of the inter-cell interference is changed within one subframe of the covariance matrix estimation due to the change in the user allocation at the interfering cells if asynchronous networks are employed. This affects the performance gain of the IRC receiver. This paper investigates the impact on asynchronous networks and the gain from the IRC receiver in terms of the downlink user throughput performance. Simulations results based on a 57-cell model environment, i.e., a cellular environment in the LTE-Advanced downlink, show that the IRC receiver which has two antenna branches effectively suppresses the inter-cell interference even when asynchronous networks are employed.

Investigation on interference rejection combining receiver in heterogeneous networks for LTE-Advanced downlink

In Long-Term Evolution (LTE)-Advanced, heterogeneous networks where low power nodes such as picocells are overlaid onto macrocells were extensively investigated to improve further 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 transmitted from the macrocells to the sets of user equipment (UEs) connected to the picocells. In such cases, since the interference statistics are completely different from traditional well-planned macrocell deployments according to the parameters specified for CRE and ICIC, it is important to investigate using the interference rejection combining (IRC) receiver because it effectively improves the cell-edge user throughput by suppressing interference from the surrounding cells. To clarify the improvement in user throughput due to the IRC receiver, this paper investigates the interference statistics and evaluates the user throughput performance of the IRC receiver in heterogeneous networks employing CRE and ICIC. Simulation results show that the throughput gain from the IRC receiver becomes small due to a reduction in the severe inter-cell interference from ICIC. However, we clarify that a cell-edge user throughput gain from the IRC receiver exceeding 10% is achieved compared to the conventional minimum mean square error (MMSE) receiver in a heterogeneous network with four picocells within each macrocell. Furthermore, we show that the same parameters specified for CRE and ICIC can be set regardless of the IRC or conventional MMSE receiver.

Complexity reduction for signal detection based on belief propagation in a massive MIMO system

The easiest way to improve the throughput performance of multiple-input multiple-output (MIMO) systems is to increase the number of both transmit and receive antennas. Thus, a massive MIMO concept has been proposed recently. In general, however, algorithms detecting spatially-multiplexed signals require the complexity to be proportional to the cubed power of the number of antenna elements at least. Several studies have shown that a detection based on belief propagation with a parallel interference canceller is implementable in the order of the second power of the number of elements and achieves very good BER performance. For further reduction of complexity, we apply layered belief propagation, forced convergence, and node selection methods to the belief propagation based detection. The results show that the layered belief propagation can halve the complexity without performance degradation.

Investigation on advanced receiver employing interference rejection combining for space-frequency block code transmit diversity in LTE-Advanced downlink

The interference rejection combining (IRC) receiver, which can suppress inter-cell interference, is effective in improving the cell edge user throughput, and is required to function effectively in various development scenarios, e.g., in both closed-loop and open-loop multiple input multiple output (MIMO) multiplexing. 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 inter-cell interference. We investigated a covariance matrix estimation scheme that employs received signals and the known sequence of downlink reference signals (RSs), and evaluated the performance gain of the scheme assuming closed-loop MIMO multiplexing. However, for open-loop MIMO multiplexing assuming one-stream transmission, i.e., open-loop transmit diversity employing the space-frequency block code (SFBC), the IRC receiver must detect the SFBC signals and suppress the interference signals at the same time. Although it is required for the extended covariance matrix estimation, some elements cannot be estimated using the RS-based estimation scheme. Therefore, this paper proposes inserting zero values in the unknown elements, and investigates the performance gains. The results of simulations assuming the LTE/LTE-Advanced downlink show that the IRC receiver using the proposed scheme, which has two receiver antenna branches, suppresses the inter-cell interference and improves the throughput by approximately 12% to 15% compared to that for the conventional maximal ratio combining (MRC) receiver when a cell edge environment is assumed.

Investigation on improvement in channel estimation accuracy using data signal muting in downlink coordinated multiple-point transmission and reception in LTE-Advanced

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. Particularly, the performance of data signal muting, i.e., muting data signals that collide with the channel state information reference signal (CSI-RS) of the 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 and consequently the throughput performance, especially for sets of user equipment at the cell boundary. Furthermore, the tradeoff relation between accurate channel estimation by muting larger numbers of data signals and a high peak data rate, i.e., low overhead, is also investigated. It is shown that when the number of coordinated cells is set to three, the improvement in performance is almost saturated when the data signals that collide with the CSI-RSs of the other two coordinated cells are muted in a synchronized network.

Reduced-complexity transmit power optimization techniques for multiuser MIMO with per-antenna power constraint

For a multiuser (MU)-MIMO precoded transmission with individual constraints on the maximum power of each transmit antenna, the transmit power optimization problem is a non-linear convex optimization problem with a high level of computational complexity. In this paper, we propose three methods in order to reduce the computational complexity associated with this problem. The reductions in computational complexity achieved with the proposed methods are evaluated under the sum-rate maximization criterion assuming i.i.d Rayleigh fading MIMO channels and block diagonalization zero-forcing as a precoder.