This paper investigates the application of inter-cell interference coordination (ICIC) in heterogeneous networks for the LTE-Advanced downlink where picocells are overlaid onto macrocells. In LTE-Advanced, in order to perform ICIC, almost blank subframes (ABSs) are employed, where only the cell-specific reference signal (CRS) is transmitted to protect the subframes in the picocells from severe interference from the macrocells. Furthermore, multicast/broadcast over single-frequency network (MBSFN) subframes are employed to reduce the interference of the CRS on the data channel, although the control channel still suffers from interference from the CRS. When the cell range expansion (CRE), which offload the UEs from macrocells to picocells, is used to improve the system performance, the influence from the CRS increases. In order to assess the influence, the required CRE bias to improve the data channel is investigated based on a system-level simulation under various conditions such as the number of picocells, the protected subframe ratio, and the user distribution. The simulation results show that the cell-edge user throughput is improved with the CRE bias of more than 8 dB, employing ABSs. Furthermore, simulation results show that one dominant source of interference is observed for the sets of user equipment (UEs) connected to the picocells via CRE with such a bias value. Based on observation, the influence that the CRS has on the control channel, i.e., physical control format indicator channel (PCFICH), and physical downlink control channel (PDCCH) is investigated based on a link-level simulation combined with a system-level simulation. The simulation results show that protecting the PCFICH is very important compared to protecting the PDCCH, since the block error rate (BLER) performance of the PCFICH becomes worse than the required BLER of 10-3 to support various conditions, although the BLER performance of the PDCCH can exceed the required BLER of 10-2 by spanning the PDCCH over three OFDM symbols.

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.

In Long-Term Evolution (LTE)-Advanced, an important goal in addition to achieving high-speed, high-capacity communications is throughput enhancement for cell-edge users. One solution is to relay radio transmissions between an eNode B and user equipment (UE). Relays are expected to extend the coverage to the cell boundary and coverage hole areas, and are expected to reduce network costs. It was agreed that in Release 10 LTE, a Layer-3 (L3) relay, which achieves self-backhauling of radio signals between an eNode B and a UE in Layer 3 should be standardized. Meanwhile, a Layer-1 (L1) relay, which amplifies and forwards received radio frequency signals, has already found widespread use in second-generation and third-generation mobile communication systems. This paper investigates the downlink system level performance for L3 and L1 relays with orthogonal frequency division multiple access (OFDMA) in LTE-Advanced. Various practical factors are taken into account in the evaluations such as the processing delay and upper bound of the amplifier gain of the L1 relay, capacity limitation of the backhaul channels, and empty buffer status at the L3 relay. We also propose and investigate a downlink backhaul link (radio link between the eNode B and L3 relay node) scheduling method for the in-band half-duplex L3 relay. In the proposed scheduling method, radio resources from an eNode B to an L3 relay node and macro UE are multiplexed in the same backhaul subframe considering the number of relay UEs and macro UEs, and the channel quality of the backhaul link to the L3 relay and the access link to the macro UE. Based on system-level simulations, we clarify the system impact of several conditions for the relay such as the number of relay nodes and the number of backhaul (radio link between eNode B and L3 relay) subframes, the distance between the eNode B and relay, and show the throughput performance gain of the L3 relay compared to the L1 relay. We also clarify that the cell-edge UE throughput performance is increased by approximately 10% by applying the proposed scheduling method due to more efficient and fair resource allocation to the L3 relay and macro UEs.

In Long-Term Evolution (LTE)-Advanced, a heterogeneous network in which femtocells and picocells overlay macrocells is being extensively discussed in addition to traditional well-planned macrocell deployment to improve further the system throughput. In heterogeneous network deployment, cell selection as well as inter-cell interference coordination (ICIC) is very important to improve the system and cell-edge throughput. Therefore, this paper investigates three cell selection methods associated with ICIC in heterogeneous networks in the LTE-Advanced downlink: Signal-to-interference plus noise power ratio (SINR)-based cell selection, reference signal received power (RSRP)-based cell selection, and reference signal received quality (RSRQ)-based cell selection. The results of simulations (4 picocells and 25 sets of user equipment are uniformly located within 1 macrocell) that assume a full buffer model show that the downlink cell and cell-edge user throughput levels of RSRP-based cell selection are degraded by approximately 2% and 11% compared to those for SINR-based cell selection under the condition of maximizing the cell-edge user throughput due to the impairment of the interference level. Furthermore, it is shown that the downlink cell-edge user throughput of RSRQ-based cell selection is improved by approximately 5%, although overall cell throughput is degraded by approximately 6% compared to that for SINR-based cell selection under the condition of maximizing the cell-edge user throughput.

This paper presents an overview of radio interface technologies for cooperative transmission in 3GPP LTE-Advanced, i.e., coordinated multi-point (CoMP) transmission, enhanced inter-cell interference coordination (eICIC) for heterogeneous deployments, and relay transmission techniques. This paper covers not only the technical components in the 3GPP specifications that have already been released, but also those that were discussed in the Study Item phase of LTE-Advanced, and those that are currently being discussed in 3GPP for potential specification in future LTE releases.

Reduced-complexity maximum a posteriori probability (MAP) signal detection is a promising technique for multiple-input multiple-output space division multiplexing (MIMO-SDM) transmission. These detectors avoid exhaustive searches for all possible transmitted symbol vectors by generating a set of candidate symbol vectors. One problem with the reduced-complexity MAP detectors when used in conjunction with soft input decoders is the inaccuracy of log likelihood ratio (LLR) values since they are computed from a handful of candidate symbol vectors, which degrades the subsequent decoding process. To rectify this weakness, this paper proposes an LLR computation scheme for reduced complexity MAP detectors. The unique feature of the proposed scheme is that it utilizes the statistical property of the MIMO channel metric to narrow down further the number of candidate symbol vectors. Toward this goal, metric selection is performed to select only a statistically "good" portion of the candidate symbol vectors. Computer simulation results show that the proposed LLR computation scheme is more effective than the existing schemes especially when the number of candidate symbol vectors becomes smaller in reduced-complexity MAP detection.

In multiple-input multiple-output (MIMO) wireless relay networks, simultaneously using multiple relay nodes can improve the capacity of source-to-destination communications. Recent information theories have shown that passing the same message across multiple relay nodes can improve the capacity of source-to-destination communications. We have previously proposed three relay schemes that use jointly QR decomposition and the phase control matrix; computer simulations have confirmed the superiority of these schemes over conventional ones such as amplify-and-forward and zero-forcing schemes. In this paper, we analyze the capacity and achievable gains (distributed array gain, intra-node array gain and spatial multiplexing gain) of the previously proposed relay schemes (QR-P-QR, QR-P-ZF, and ZF-P-QR) and thus provide an insight into what contributes to their superiority over conventional schemes. The analyses show that the location of the relay nodes used has a significant impact on capacity. On the basis of this observation, we further propose a method that enables each relay node to individually select its relay scheme according to its channel conditions so as to maximize the capacity. A computer simulation confirms the capacity improvement achieved by the proposed selection method.

This paper aims to improve the performance of the soft canceller followed by simplified minimum mean-square error (SC/S-MMSE) turbo receiver for multiple-input and multiple-output space-division multiplexing/orthogonal frequency division multiplexing (MIMO-SDM/OFDM) transmission; it performs iterative parallel soft interference cancellation and MMSE filtering, and stream-wise soft-input and soft-output decoding. For this aim, we newly introduce two detection techniques: 1) serial interference cancellation, and 2) cyclic redundancy check (CRC)-assisted interference cancellation and MMSE filter tap computation. Various computer simulations are conducted to evaluate the performance enhancement obtained via the use of the two detection techniques. The computer simulation results show that this paper's proposed serial SC/S-MMSE turbo receiver with CRC achieves frame error rate (FER) performance gain over existing MIMO receivers (MMSE receiver, V-BLAST receiver, parallel SC/MMSE-matched filter (MF) turbo receiver, and parallel SC/S-MMSE turbo receiver) for QPSK, 16QAM and 64QAM modulation while keeping the comparable complexity order.

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.

In closed-loop multiple-input and multiple-output space-division multiplexing (MIMO-SDM) systems, allocating power among multiple transmit data streams improves the channel capacity. However, the optimum power allocation values are not always available in closed-form. For instance, when we use transmission and reception schemes that do not transfer the MIMO channel into parallel orthogonal channels (e.g., eigen-mode SDM), the signal to interference plus noise ratio (SINR) of each data stream at the output of the receiver is not proportional to its corresponding transmit power. This feature makes it difficult to obtain the optimal closed-form power allocation value for each data stream. Thus, in this paper, we propose an iterative power allocation scheme for MIMO-SDM systems where the SINR is not proportional to the transmit power. Furthermore, we incorporate a transmit antenna selection scheme into the proposed power allocation scheme in order to attain further capacity enhancement. Computer simulation results are provided to show the effectiveness of the proposed power allocation schemes.

In the Long-Term Evolution (LTE)-Advanced downlink, a user-specific demodulation reference signal (DM-RS) is used to support channel estimation and data demodulation for user-transparent multi-antenna and/or multi-point (MA/P) transmission techniques. A hybrid code division multiplexing (CDM) and frequency division multiplexing (FDM) scheme is adopted as a DM-RS multiplexing scheme for up to eight data streams per user. A time-domain orthogonal cover code (OCC) is used for CDM since time domain orthogonality among OCCs offers good robustness against channel variation. However, in a medium-to-high mobility environment, orthogonality distortion occurs among OCCs, which results in performance degradation. In this paper, we propose a two-dimensional (2D)-OCC mapping that achieves two-dimensional orthogonality in the time and frequency domains to improve the performance of CDM-based DM-RSs while reducing the peak transmission power of the OFDM symbol which includes the DM-RSs. Simulation results show that the proposed 2D-OCC mapping is effective in improving the block error rate performance especially in medium-to-high mobility environments. Furthermore, it is shown that the 2D-OCC mapping effectively reduces the peak power compared to the time-domain OCC mapping.