Precoded FIR and Redundant V-BLAST Systems for Frequency-Selective MIMO Channels

The vertical Bell labs layered space-time (V-BLAST) system is a multi-input multioutput (MIMO) system designed to achieve good multiplexing gain. In recent literature, a precoder, which exploits channel information, has been added in the V-BLAST transmitter. This precoder forces each symbol stream to have an identical mean square error (MSE). It can be viewed as an alternative to the bit-loading method. In this paper, this precoded V-BLAST system is extended to the case of frequency-selective MIMO channels. Both the FIR and redundant types of transceivers, which use cyclic-prefixing and zero-padding, are considered. A fast algorithm for computing a cyclic-prefixing-based precoded V-BLAST transceiver is developed. Experiments show that the proposed methods with redundancy have better performance than the SVD-based system with optimal powerloading and bit loading for frequency-selective MIMO channels. The gain comes from the fact that the MSE-equalizing precoder has better bit-error rate performance than the optimal bitloading method

Comparison of precoding methods for broadband MIMO systems

In this paper we investigate non-linear precoding solutions for the problem of broadband multiple-input multipleoutput (MIMO) systems. Based on a broadband singular value decomposition (BSVD) we can decouple a broadband MIMO channel into independent dispersive spectrally majorised singleinput single-output (SISO) subchannels. Bit loading is proposed to optimally utilise these SISO subchannels after mitigating their individual inter-symbol-interference (ISI) using Tomlinson- Harashima precoding (THP). This method is benchmarked against recent results of both MMSE linear and THP designed for frequency-selective MIMO channels. Simulation results show that better bit-error-ratio (BER) can be achieved especially for higher throughput targets when compared to the benchmar

Maximum-Likelihood Sequence Detection of Multiple Antenna Systems over Dispersive Channels via Sphere Decoding

Multiple antenna systems are capable of providing high data rate transmissions over wireless channels. When the channels are dispersive, the signal at each receive antenna is a combination of both the current and past symbols sent from all transmit antennas corrupted by noise. The optimal receiver is a maximum-likelihood sequence detector and is often considered to be practically infeasible due to high computational complexity (exponential in number of antennas and channel memory). Therefore, in practice, one often settles for a less complex suboptimal receiver structure, typically with an equalizer meant to suppress both the intersymbol and interuser interference, followed by the decoder. We propose a sphere decoding for the sequence detection in multiple antenna communication systems over dispersive channels. The sphere decoding provides the maximum-likelihood estimate with computational complexity comparable to the standard space-time decision-feedback equalizing (DFE) algorithms. The performance and complexity of the sphere decoding are compared with the DFE algorithm by means of simulations

Trade-off between complexity and BER performance of a polynomial SVD-based broadband MIMO transceiver

In this paper we investigate non-linear precoding solutions for the problem of broadband multiple-input multiple output(MIMO) systems. Based on a polynomial singular value decomposition (PSVD) we can decouple a broadband MIMO channel into independent dispersive spectrally majorised single-input single-output (SISO) subchannels. In this contribution, the focus of our work is to explore the influence of approximations on the PSVD, and the performance degradation that can be expected as a result

Block diagonal GMD for zero-padded MIMO frequency selective channels with zero-forcing DFE

In the class of systems with linear precoder and zero-forcing (ZF) DFE for zero-padded MIMO frequency selective channels, existing optimal transceiver designs present two major drawbacks. First, the optimal system requires a large number of bits to encode the full precoding matrix. Second, the full precoding matrix leads to complex computations. These disadvantages become more severe as bandwidth (BW) efficiency increases. In this article, we propose using the block diagonal geometric mean decomposition (BD-GMD) technique to design an alternative transceiver. The proposed ZF-BD-GMD system uses a block diagonal orthogonal precoder matrix structure to reduce the required number of encoding bits and simplifies the computation. While solving the current optimal system's drawbacks, the ZF-BD-GMD system also produces a similar bit error rate (BER) performance when the block size is large. In other words, the ZF-BD-GMD system is asymptotically optimal in the class of communication systems with linear precoder and ZF-DFE receiver

Sparsity Enhanced Decision Feedback Equalization

For single-carrier systems with frequency domain equalization, decision feedback equalization (DFE) performs better than linear equalization and has much lower computational complexity than sequence maximum likelihood detection. The main challenge in DFE is the feedback symbol selection rule. In this paper, we give a theoretical framework for a simple, sparsity based thresholding algorithm. We feed back multiple symbols in each iteration, so the algorithm converges fast and has a low computational cost. We show how the initial solution can be obtained via convex relaxation instead of linear equalization, and illustrate the impact that the choice of the initial solution has on the bit error rate performance of our algorithm. The algorithm is applicable in several existing wireless communication systems (SC-FDMA, MC-CDMA, MIMO-OFDM). Numerical results illustrate significant performance improvement in terms of bit error rate compared to the MMSE solution

Generalized feedback detection for spatial multiplexing multi-antenna systems

We present a unified detection framework for spatial multiplexing multiple-input multiple-output (MIMO) systems by generalizing Heller’s classical feedback decoding algorithm for convolutional codes. The resulting generalized feedback detector (GFD) is characterized by three parameters: window size, step size and branch factor. Many existing MIMO detectors are turned out to be special cases of the GFD. Moreover, different parameter choices can provide various performance-complexity tradeoffs. The connection between MIMO detectors and tree search algorithms is also established. To reduce redundant computations in the GFD, a shared computation technique is proposed by using a tree data structure. Using a union bound based analysis of the symbol error rates, the diversity order and signal-to-noise ratio (SNR) gain are derived analytically as functions of the three parameters; for example, the diversity order of the GFD varies between 1 and N. The complexity of the GFD varies between those of the maximum-likelihood (ML) detector and the zero-forcing decision feedback detector (ZFDFD). Extensive computer simulation results are also provided

I/Q imbalance mitigation for space-time block coded communication systems

Multiple-input multiple-output (MIMO) space-time block coded (STBC) wireless communication systems provide reliable data transmissions by exploiting the spatial diversity in fading channels. However, due to component imperfections, the in-phase/quadrature (I/Q) imbalance caused by the non-ideal matching between the relative amplitudes and phases of the I and Q branches always exists in the practical implementation of MIMO STBC communication systems. Such distortion results in a complex conjugate term of the intended signal in the time domain, hence a mirror-image term in the frequency domain, in the data structure. Consequently, I/Q imbalance increases the symbol error rate (SER) drastically in MIMO STBC or STBC MIMO orthogonal frequency division multiplexing (OFDM) communication systems, where both the signal and its complex conjugate are utilized for the information transmission, hence should be mitigated effectively. In this dissertation, the impact of I/Q imbalance in MIMO STBC systems over flat fading channels, the impact of I/Q imbalance in STBC MIMO-OFDM systems and in time- reversal STBC (TR-STBC) systems over frequency-selective fading channels are studied systematically. With regard to the MIMO STBC and the STBC MIMO-OFDM systems with I/Q imbalance, orthogonal space-time block codes (OSTBCs), quasi-orthogonal STBCs (QOSTBCs) and rotated QOSTBCs (RQOSTBCs) are studied, respectively. By exploiting the special structure of the received signal, low-complexity solutions are provided to mitigate the distortion induced by I/Q imbalance successfully. In addition, to mitigate I/Q imbalance while at the same time to exploit the multipath diversity for STBC OFDM systems over frequency-selective fading channels, a new encoding/decoing scheme for the grouped linear constellation precoded (GLCP) OFDM systems with I/Q imbalance is studied. In Chapter 1, the objectives of the research are elaborated. In Chapter 2, the various I/Q imbalance models are introduced, and the model used in this dissertation is established. In Chapter 3, the performance degradation caused by I/Q imbalance of the transceivers in MIMO STBC wireless communication systems over flat fading channels and the solutions are studied. A 2 Tx Alamouti system, a 4 Tx quasi-orthogonal STBC (QOSTBC) system, and a 4 Tx rotated QOSTBC (RQOSTBC) system with I/Q imbalance are studied in detail. By exploiting the special structure of the received signal, low-complexity solutions are proposed to mitigate I/Q imbalance successfully. Since STBCs are developed for frequency-flat fading channels, to achieve the spatial diversity in frequency-selective fading channels, MIMO-OFDM arrangements have been suggested, where STBCs are used across different antennas in conjunction with OFDM. In Chapter 4, the performance degradation caused by I/Q imbalance in STBC MIMO-OFDM wireless systems over frequency-selective fading channels and the solutions are studied. Similarly, a 2 Tx Alamouti system, a 4 Tx quasi-orthogonal STBC (QOSTBC) system, and a 4 Tx rotated QOSTBC (RQOSTBC) system with I/Q imbalance are studied in detail, and low-complexity solutions are proposed to mitigate the distortion effectively. However, OFDM systems suffer from the loss of the multipath diversity by converting frequency-selective fading channels into parallel frequency-flat fading subchannels. To exploit the multipath diversity and reduce the decoding complexity, GLCP OFDM systems with I/Q imbalance are studied. By judiciously assigning the mirror-subcarrier pair into one group, a new encoding/decoding scheme with a low-complexity is proposed to mitigate I/Q imbalance for GLCP OFDM systems in Chapter 5. Since OFDM communication systems have high peak-to-average power ratio (PAPR) problem and are sensitive to carrier frequency offset (CFO), to achieve both the spatial and multipath diversity, time-reversal STBC (TR-STBC) communication systems are introduced. In Chapter 6, the I/Q imbalance mitigating solutions in TR-STBC systems, both in the time domain and in the frequency domain, are studied