Recently, multi-user multiple-input multiple-output (MU-MIMO) systems are being widely studied. For interference cancellation, MU-MIMO commonly uses spatial precoding techniques. These techniques, however, require the transmitters to have perfect knowledge of the downlink channel state information (CSI), which is hard to achieve in high mobility environments. Instead of spatial precoding, a collaborative interference cancellation (CIC) technique can be implemented for these environments. In CIC, mobile stations (MSs) collaborate and share their received signals to increase the demultiplexing capabilities. To obtain efficient signal-exchange between collaborating users, signal selection can be implemented. In this paper, a signal selection scheme suitable for a QRM-MLD algorithm is proposed. The proposed scheme uses the minimum Euclidean distance criterion to obtain an optimum bit error rate (BER) performance. Numerical results obtained through computer simulations show that the proposed scheme is able to provide BER performance near to that of MLD even when the number of candidates in QRM-MLD is relatively small. In addition, the proposed scheme is feasible to implement owing to its low computational complexity.

This paper investigates the performance of an overloaded multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system with a repetition code. It has been demonstrated that diversity with block coding prevents the performance degradation induced by signal multiplexing. However, the computational complexity of a joint decoding scheme increases exponentially with the number of multiplexed signal streams. Thus, this paper proposes the use of a repetition code in the overloaded MIMO-OFDM system. In addition, QR decomposition with M-algorithm (QRM) maximum likelihood decoding (MLD) is applied to the decoding of the repetition code. QRM-MLD significantly reduces the amount of joint decoding complexity. In addition, virtual antennas are employed in order to increase the throughput that is reduced by the repetition code. It is shown that the proposed scheme reduces the complexity by about 1/48 for 6 signal streams with QPSK modulation while the BER degradation is less than 0.1dB at the BER of 10-3.

Multi-user multi-input multi-output (MIMO) system has been attracting much attention due to its high spectrum efficiency. Non-linear MIMO signal detection methods with less computational complexity have been widely studied for single-user MIMO systems. In this paper, we investigate how a lattice reduction (LR)-aided detection and a maximum likelihood detection (MLD) employing the QR decomposition and M-algorithm (QRM-MLD), which are commonly known as non-linear MIMO signal detection methods, improve the uplink capacity of a multi-user MIMO-OFDM cellular system, compared to simple linear detection methods such as zero-forcing detection (ZFD) and minimum mean square error detection (MMSED). We show that both LR-aided linear detection and QRM-MLD can achieve higher uplink capacity than simple linear detection at the cost of moderate increase of computational complexity. Furthermore, QRM-MLD can obtain the same uplink capacity as MLD.

Recently, assuming ideal brick-wall transmit filtering, we proposed a frequency-domain block signal detection (FDBD) with maximum likelihood detection employing QR decomposition and M-algorithm (called QRM-MLD) for the reception of single-carrier (SC) signals transmitted over a frequency-selective fading channel. QR decomposition (QRD) is applied to a concatenation of the propagation channel and discrete Fourier transform (DFT). However, a large number of surviving paths is required in the M-algorithm to achieve sufficiently improved bit error rate (BER) performance. The introduction of filtering can achieve improved BER performance due to larger frequency diversity gain while keeping a lower peak-to-average power ratio (PAPR) than orthogonal frequency division multiplexing (OFDM). In this paper, we develop FDBD with QRM-MLD for filtered SC signal reception. QRD is applied to a concatenation of transmit filter, propagation channel, and DFT. We evaluate BER and throughput performances by computer simulation. From performance evaluation, we discuss how the filter roll-off factor affects the achievable BER and throughput performances and show that as the filter roll-off factor increases, the required number of surviving paths in the M-algorithm can be reduced.

This paper presents experimental results in real propagation channel environments of real-time 1-Gbps packet transmission using antenna-dependent adaptive modulation and channel coding (AMC) with 4-by-4 MIMO multiplexing in the downlink Orthogonal Frequency Division Multiplexing (OFDM) radio access. In the experiment, Maximum Likelihood Detection employing QR decomposition and the M-algorithm (QRM-MLD) with adaptive selection of the surviving symbol replica candidates (ASESS) is employed to achieve such a high data rate at a lower received signal-to-interference plus background noise power ratio (SINR). The field experiments, which are conducted at the average moving speed of 30 km/h, show that real-time packet transmission of greater than 1 Gbps in a 100-MHz channel bandwidth (i.e., 10 bits/second/Hz) is achieved at the average received SINR of approximately 13.5 dB using 16QAM modulation and turbo coding with the coding rate of 8/9. Furthermore, we show that the measured throughput of greater than 1 Gbps is achieved at the probability of approximately 98% in a measurement course, where the maximum distance from the cell site was approximately 300 m with the respective transmitter and receiver antenna separation of 1.5 m and 40 cm with the total transmission power of 10 W. The results also clarify that the minimum required receiver antenna spacing is approximately 10 cm (1.5 carrier wave length) to suppress the loss in the required received SINR at 1-Gbps throughput to within 1 dB compared to that assuming the fading correlation between antennas of zero both under non-line-of-sight (NLOS) and line-of-sight (LOS) conditions.

In this letter, we propose a novel signal detection method, reduced complexity QRM-MLD, which achieves almost identical error performance to that of the conventional QRM-MLD while significantly reducing the computational complexity.

In this letter, we propose a computationally efficient search space for QRM-MLD that is used for spatially multiplexed multiple antenna systems. We perform a set of computer simulations to show that the proposed method achieves a performance that is near to that of the original QRM-MLD, while its computational complexity is near to that of rank-QRM-MLD.

Multiple-input multiple-output (MIMO) multiplexing has recently been attracting considerable attention for increasing the transmission rate in a limited bandwidth. In MIMO multiplexing, the signals transmitted simultaneously from different transmit antennas must be separated and detected at a receiver. Maximum likelihood detection with QR-decomposition and M-algorithm (QRM-MLD) can achieve good performance while keeping computational complexity low. However, when the number of surviving symbol replica candidates in the M-algorithm is set to be small, the performance of QRM-MLD degrades compared to that of MLD because of wrong selection of surviving symbol replica candidates. Furthermore, when channel estimation is inaccurate, accurate signal ranking and QR-decomposition cannot be carried out. In this paper, we propose an iterative QRM-MLD with decision directed channel estimation to improve the packet error rate (PER) performance. In the proposed QRM-MLD, decision feedback data symbols are also used for channel estimation in addition to pilot symbols in order to improve the channel estimation accuracy. Signal detection/channel estimation are then carried out in an iterative fashion. Computer simulation results show that the proposed QRM-MLD reduces the required average received Eb/N0 for PER of 10-2 by about 1.2 dB compared to the conventional method using orthogonal pilot symbols only.

This letter describes unequal-power transmission for multiple-input and multiple-output (MIMO) systems with a parallel interference canceller (PIC) applied to a maximum likelihood detector (MLD) or complexity-reduced MLD at the receiver. Unequal-power transmission reduces the possibility that all substreams are incorrectly decoded. Canceling the correctly decoded substreams enables more reliable detection in the next stage. The simulation results demonstrated that unequal-power transmission improves the transmission performance of the PIC applied to MLDs or complexity-reduced MLDs, compared with equal-power transmission cases.