Jointly Optimized Modulated-Transmitter and Receiver FIR MIMO Filters

The problem of uplink communications is considered where multiple mobile terminals equipped with multiple antennas are communicating with one base station also having multiple antennas. A theory for jointly optimizing the transmitter and receiver finite impulse response (FIR) multiple-input multiple-output (MIMO) filters is developed. The signals from the individual users are assumed to be uncorrelated with each other and the additive channel noise is uncorrelated with the original signals. The FIR MIMO channel filters are assumed to be known for both the mobile terminals and the base station. All the input signals to the FIR MIMO channels are assumed to be power-constrained. For given FIR MIMO channels with maximum allowable average input powers, the transmitter and receiver FIR MIMO filters are jointly optimized such that the mean square error (MSE) between the desired and reconstructed signals is minimized. An iterative numerical optimization algorithm is proposed. Numerical simulation results show that the proposed method has substantially better performance than a code division multiple access (CDMA) based system using minimum MSE receiver filters.

In this paper, we investigate coordinated multiple-input multiple-output (MIMO) transmission in an interference-limited cellular downlink. Different from previous work, we consider a cellular system serving more than one user using non-orthogonal channels per cell. We propose a novel coordinated transmission scheme based on the minimum mean square error (MMSE) criterion. The proposed scheme is applicable to multiple user cells. Also, efficient user selection methods along with coordinated transmission are investigated to further enhance the sum rate. Computer simulations demonstrate the effectiveness of the proposed coordination scheme and user selection methods.

Multiple-input multiple-output (MIMO) systems can achieve high data-rate and high capacity transmission. In MIMO systems, the scheme that weight substreams based on minimum mean square error (MMSE) criterion at the transmitter using feedback channel state information (CSI) achieves good performance (denoted hereafter as MMSE precoder). However, if the optimum number of substreams is not selected based on CSI and methods for reducing the performance degradation due to feedback delay is not used, MMSE precoder cannot achieve the full performance possible. In this paper, we propose an MMSE precoder with mode selection for MIMO systems, which selects both the number of substreams and the modulation scheme for each substream to minimize the average BER at a fixed rate. We evaluate the BER of the proposed MMSE precoder with two methods for reducing performance degradation due to feedback delay, channel prediction and receive weight robust to feedback delay. We also evaluate the BER of the proposed MMSE precoder with the method that combines channel prediction with receive weight robust to feedback delay. Simulation results show that the BER of the proposed MMSE precoder is improved compared to that of the conventional MMSE precoder using the fixed number of substreams. We also show that the method that combines channel prediction with receive weight robust to feedback delay can achieve good BER even when the large feedback delay exists.

This paper investigates the issue of high complexity of digital predistortion for the nonlinear distortion introduced due to crosstalk in addition to the nonlinear distortion generated by a power amplifier (PA) in 2 × 2 MIMO transmitters. This paper proposes a less complex, novel model for digital predistortion (DPD) for linearizing multiple-input multiple-output (MIMO) transmitters. This model is constructed by taking account of both linear and nonlinear crosstalks, along with the fact that the nonlinearity generated due to crosstalk would be lesser than the nonlinearity already available due to PA. For proof-of-concept, it is shown for two different scenarios that proposed model provides similar linearization performance as compared to 2 × 2 PH model with less number of coefficients.

For the code division multiple access (CDMA) downlink channel, the chip-level equalization has been considered in this paper. There is no interference after despreading if all spreading codes are orthogonal, as in IS-95. However, it cannot be true for a frequency-selective fading channel. In this case, the chip-level equalization can be applied to restore the orthogonality. We investigate the chip-level equalization using finite impulse response (FIR) equalizers for the mobile station with multiple receive antennas. A blind approach and the minimum mean square error (MMSE) approach with code-multiplexed pilot are considered. A generalized MMSE equalization, which combines the MMSE and blind approaches together, is also investigated. It is shown that the generalized MMSE equalizer can effectively increase the number of samples to track the variation of channel and thereby performs better when the coherence time is small. In addition, we derive closed-form solutions of the blind, MMSE, and generalized MMSE equalizers for given channels.

A channel state information (CSI) feedback algorithm based on scalar quantization is proposed for a multiple-input multiple-output (MIMO) transmission. The performance of the proposed algorithm is evaluated using the effective transmission rate, which incorporates the effect of the CSI feedback overhead on transmission time. Besides that, the power consumed due to the computational complexity of the CSI feedback algorithm is taken into account together with the transmit power when evaluating the energy efficiency. We compare our proposed algorithm to other typical CSI feedback algorithms under correlated channel conditions. Simulation results show that the proposed algorithm enables practical MIMO transmission to achieve an relative transmission rate at 95% of the ideal rate.

3GPP (3rd Generation Partnership Project) LTE (Long Term Evolution) Advanced standards are currently under way, where 4×4 MIMO (Multiple Input Multiple Output) scheme is the minimum structure. One of the best solutions to support the maximum data rate transmission is to adopt a MIMO scheme, especially spatial multiplexing mode, which means that each antenna port can transmit separate data. To realize this algorithm, the main issue is to cancel interferences added to each antenna port, and therefore, the algorithm at the receiver should have good performances. In the aspect of implementation, MMSE (Minimum Mean Square Error) detection algorithm is a reasonable method considering both complexity and performance. Furthermore, an iterative receiver (IR) algorithm can also be applied to this system. An IR algorithm has a tradeoff between complexity and performance. In this paper, we designed a reasonable and implementable MIMO receiver structure and showed performance for 3GPP LTE Advanced system, and verified that hard decoded bits, PIC-MMSE (Parallel Interference Cancellation - MMSE) and 1-iteration PIC are enough to meet the required SNR using the implemented test-bed system.

Video monitoring applications for underground rely on wireless train-to-wayside communication systems which require high data rate as well as high Quality of Service (QoS) level. In order to satisfy both constraints we propose a combined source and channel coding approach in the context of MIMO (Multiple Input Multiple Output) video transmission. In the present case, MIMO transmission is based on the PHY layer of IEEE 802.11n Wi-Fi standard currently deployed in a railway tunnels. Two different strategies are studied: first, the association between Multiple Description Coding (MDC) and a STBC (Space Time Block Code) MIMO scheme is considered when no channel information is available at transmitter side. In the case when perfect channel information is available at transmitter side (CSIT), a Singular Value Decomposition of the MIMO channel is possible. This transmission scheme is then associated with scalable video coding, which consists here in the separation of the scene into different Regions Of Interest (ROI). The creation of the regions of interest is based on the Flexible Macroblock Ordering (FMO) technique introduced in the new H.264/AVC compression standard. The stream associated to the area with the maximal perceptual relevance is transmitted on the eigen-channel with the higher gain. Consequently, this strategy which provides unequal protection against channel errors, allows guaranteeing better robustness and acceptable reconstructed video quality at the control-centre. The two different strategies of transmission have been evaluated thanks to realistic simulations. Two antenna configurations representative of real cases encountered in railway tunnels are considered. The channel model is generated by using the correlation based Kronecker model obtained by computing the channel matrix with a 3D ray tracing tool. Simulation results show that the two proposed solutions allow enhancing the reconstructed video quality compared to conventional transmission schemes with no increase of the transmitted power and of the number of radio access points along the infrastructure, even in tunnels in presence of spatial correlation.Keywordstrain-to-wayside communicationsvideo communicationsMultiple Input Multiple Output (MIMO) systemMultiple Description Coding (MDC)Scalable Video Coding (SVC)Kronecker model

In recent years, multiple-input multiple-output (MIMO) systems, which use several transmit and receive antennas, have attracted much attention for high performance radio systems. In MIMO systems, the channel estimation is important to distinguish transmit signals from multiple transmit antennas. While the space-alternating generalized expectation-maximization (SAGE) algorithm is known to offer good channel estimation and data detection. We proposed earlier the minimum mean square error (MMSE)-based SAGE algorithm for MIMO systems where the MMSE estimation is used for channel estimation. We showed that the proposed MMSE-based SAGE algorithm can achieve the better bit error rate (BER) than the maximum likelihood (ML) detection with training symbols. The MMSE channel estimation needs the knowledge of the maximum Doppler frequency F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sub> for deriving the covariance matrix of the channel and the variance sigma <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of additive white Gaussian noise (AWGN). Additionally, the computation of the MMSE channel estimation requires O(L <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) operations where L is the transmitted frame length. Thus, its computational complexity is high. In this paper, we propose a zero-forcing (ZF)-based SAGE algorithm for channel estimation and data detection in MIMO systems that does not need the knowledge of Fd and sigma <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . Since the computation of the proposed ZF-based SAGE algorithm requires O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) operations where N is the number of transmit antennas, its computational complexity is low. We show that the proposed ZF-based tracking SAGE algorithm with less computational complexity can achieve almost the same BER as that of the MMSE-based tracking SAGE algorithm

In order to decrease system implementation cost of fiber-optic relaying systems for multiple-input multiple output (MIMO) mobile transmissions, we have proposed a novel relaying scheme using spatial modulation (SM) technology. The proposed scheme uses much fewer radio over fiber (RoF) links than the conventional fiber-optic relaying schemes. We studied the performance of the proposed scheme through computer simulations and confirmed that the proposed scheme can achieve much better transmission performance than the conventional ones. Computer simulations show that the optimum number of RoF links of the proposed scheme is around 2 or 3 for 4×4 MIMO transmissions, and around 3 or 4 for 8×8 MIMO transmissions.

This paper investigates iterative frequency domain techniques for the reception of spatially multiplexed single carrier signals transmitted over frequency-selective multiple input multiple output (MIMO) channels. The investigated equalizers are based on the soft-cancellation (SC) and minimum mean square error (MMSE) altering technique for turbo-coded single carrier point-to-point MIMO systems. We consider two different transmit antenna separation techniques in the frequency domain: (1) antenna-by-antenna (AA) and (2) joint over antenna techniques (JA). (1) aims to separate signals in different layers by MMSE filtering antenna-by-antenna, whereas (2) aims to detect the composite signal comprised of the signals transmitted from the multiple antennas. In (2) the composite received signal is decomposed by using the spatial maximum a posteriori probability (MAP) algorithm. We evaluate performances in terms of frame error rate (FER) and throughput in point-to-point MIMO frequency-selective fading channels. Impacts of spatial correlation on performance of the two detectors are also investigated in this paper.

In the field of multiple input multiple output (MIMO) decoder, K-best has been well investigated because it guarantees an SNR-independent fixed-throughput with a performance close to the optimal maximum likelihood detection (MLD). However, the complexity of its expansion and sorting tasks is significantly affected by the constellation size W. In this paper, we propose an algorithm and hardware design of a 2D sorter-based K-best MIMO decoder whose complexity is negligibly affected by W. The main novelties of the algorithm are the following: (1) Direct expansion and parent node grouping ideas are proposed for reducing the expansion task’s complexity. (2) Two-dimensional (2D) sorter is proposed for simplifying the sorting task. The hardware design of the decoder supports up to 256-QAM modulation, which aims to apply into 4 × 4 MIMO 802.11n and 11ac systems. The paper shows that the proposed decoder outperforms the Bell Labs layered space-time (BLAST) minimum mean square error (MMSE) and lattice-reduction aided (LRA) MMSE, and is close to the full K-best in terms of bit error rate (BER) performance. The hardware design of the decoder is synthesized in application specific integrated circuit (ASIC) and compared with the previous works. As a result, it achieves the highest throughput (up to 2.7 Gbps), consumes the least power (56 mW), obtains the best hardware efficiency (15.2 Mbps/Kgate), and has the shortest latency (0.07 µs).

An adaptive digital predistortion (PD) technique is proposed for linearization of power amplifiers (PAs) in multiple-input multiple-output (MIMO) transmitters. Instead of constructing a separate feedback path at each PA, we propose a PD technique based on a combined feedback, which adds all the PAs' outputs to form a single feedback. We develop an algorithm for finding the multiple PA characteristics jointly from the combined feedback. The PD parameters are calculated from the identified PA characteristics. Although the proposed method requires more computations for PA identification than the conventional method, its hardware implementation is much simpler and can overcome the crosstalk problem of a radio frequency (RF) selector, which is necessary for multiple feedback selection. The simulation results show that, despite its simple structure, the linearization performance of the proposed method is almost the same as the separate multiple feedback method.

Chapter 2 - Design and Implementation of Digital FIR Filters

In this paper, we propose a new channel reciprocity calibration method based on minimum mean square error (MMSE) in network multiple-input and multiple-output (MIMO) system. Network MIMO system can mitigate the inter-cell interference by joint precoding techniques. The system is assumed to operate in time division duplex (TDD). However, the generalized channeles do not only consist of free-space electromagnetic channel, but also include transceiver modules, the mismatches between the transceiver modules of the antennas destroy the channel reciprocity. Therefore the mismatches should be calibrated before channel reciprocity can be utilized. An effective method for calculating the calibration coefficients in the network MIMO system whose BSs are equipped with multiple antennas is proposed. The network MIMO system is divided into M independent centralized MIMO systems and one distributed MIMO system, then the calibration coefficients of the two systems can be combined to calculate the calibration coefficients of the network MIMO system. The validity of the method is proved by the simulation results.