Practical Multiple-input Multiple-output Systems Research Articles

A Space-Time Transmission Scheme for Large MIMO Systems

In this letter, we propose a space-time transmission scheme (STTS) for large multiple-input multiple-output (MIMO) communication systems. These systems are primarily used to transmit a huge amount of data. The existing space-time block codes (STBCs) are not suitable for these systems due to the fact that these STBCs require very large channel coherence time (more than the number of transmit antennas), render poor data rate (less than one), and aim at full spatial diversity. In a practical large MIMO system with one thousand transmit and one thousand receive antennas, the diversity order of ${10}^{{6}}$ can be achieved; however, such a high value of diversity order is not required in practical systems. Therefore, an STTS with good data rate, parsimoniously utilized temporal dimensions, and symbol-wise decoding is essentially required for practical large MIMO systems. In this letter, we emphasize design of a new STTS by relaxing the constraint of achieving full spatial diversity. In the proposed STTS, the data rate of the large MIMO system is increased at the expense of the reduction in spatial diversity order. An approximate expression of symbol error rate of the proposed system is obtained-based on the moment generating function of the instantaneous received signal-to-noise ratio. Further, it is shown that the diversity order of the proposed STTS-based system is one less than the number of receive antennas.

Compact Dual-Band Decoupling Structure for Improving Mutual Coupling of Closely Placed PIFAs

In this letter, a dual-band isolation enhancement technique for two closely located dual-band planar inverted-F antennas (PIFAs) is proposed using a compact planar spiral line (PSL) structure. The decoupling structure has the dimensions of less than 0.15λ × 0.1λ and can be flexibly applied to various practical multiple-input multiple–output systems. By employing this structure, two PIFAs (with port distance of 0.1λ) can achieve high isolation better than 20.3 and 26.7 dB within the lower band (2.4–2.483 GHz) and higher band (5.25–5.9 GHz), respectively. Meanwhile, the decoupling mechanism and design requirement of PSL are discussed. Influences of the proposed PSL to the efficiency, gain, and radiation pattern of PIFAs were also studied. Good agreement between the simulated results and measured results is obtained.

OSTBC Transmission in Large MIMO Systems

We address the problem of orthogonal space-time block code (OSTBC) transmission in a large multiple-input multiple-output (MIMO) system in Rayleigh fading environment. Because there are hundreds of antennas at the transmitter, a very large dimension OSTBC is required in the case of massive MIMO system. Full rate OSTBC is available only for two transmit antenna-based system with complex symbols. Recently, an implementation of OSTBC for 32 transmit and 32 receive antennas is presented for real symbols. In this letter, we present a scheme of OSTBC transmission for practical large MIMO systems by embedding the OSTBCs of small dimensions with good rate. At the receiving end, the decoding of the OSTBCs is performed by utilizing the concept of null space. It is shown by simulation and analysis that the code rate can be improved at the cost of degraded performance; however, the performance of large MIMO system is not an issue because of the availability of very large antennas at the transmitter and receiver. The expression for the moment generating function (MGF) of the received signal-to-noise ratio at the receiver node is derived for the proposed OSTBC-based scheme. Using the MGF expression, we obtain the analytical symbol error rate for the proposed scheme with M-ary phase-shift keying modulation symbols.

Partitioned scheduling for sphere decoding with runtime constraints for practical MIMO communication systems

SummaryThis paper presents an effective scheduling scheme for sphere decoding (SD) with runtime constraints, targeting the practical multiple‐input multiple‐output (MIMO) communication systems where neither the interleaving scheme nor its block size cannot be designed freely. The proposed scheme imposes runtime constraints on SD to distribute the errors due to the early termination of SD. Because the distributed errors may be corrected effectively by forward error correction, the error‐rate performance can be improved; experimental results show that the performance improvement is approximately 2dB in terms of the signal‐to‐noise ratio to achieve a bit‐error rate of 10−4 in 4 × 4 16‐QAM MIMO systems. Copyright © 2015 John Wiley & Sons, Ltd.

Statistical Precoding for MIMO Systems With Channel Estimation Errors

Obtaining accurate instantaneous channel state information (CSI) is challenging for multiple-input–multiple-output (MIMO) systems, particularly if the channel fluctuates rapidly. A more practical assumption is statistical CSI as the channel statistics are likely to remain unchanged for a longer period. In this letter, we propose a precoder design, using only statistical CSI, to minimize error probability for practical MIMO systems with channel estimation errors. Our proposed precoder design is shown to achieve a significant improvement in error performance when compared with other precoding schemes in literature. For example, for a real 4 $\times$ 4 MIMO system with BPSK modulation and at a codeword error rate of $10^{-3}$ , coding gains of up to 12 dB can be achieved.

Finite-SNR Diversity-Multiplexing Tradeoff for Rayleigh MIMO Channels

In this paper, exact diversity-multiplexing tradeoff (DMT) at finite signal to noise ratio (SNR) for multiple-input multiple-output (MIMO) systems with dual antennas at the transmitter (2 x N_r) and/or at the receiver (N_tx 2) is derived over Rayleigh fading channels. We derive the outage probability of the mutual information between transmitted and received signals versus SNR. It is shown that at realistic SNRs, achievable diversity gains are significantly lower than asymptotic values. While space-time codes (STCs) for MIMO systems are conventionally designed to achieve the asymptotic DMT frontier, this finite-SNR DMT could provide a new insight to design STCs for practical MIMO systems optimized at operational SNRs.

Cross-entropy optimisation of multiple-input multiple-output capacity by transmit antenna selection

Radio channel capacity can be increased dramatically using a multiple-input multiple-output (MIMO) scheme, but at the expense of hardware complexity. An efficient approach for complexity reduction is antenna subset selection at the transmitter and/or receiver. A novel transmit antenna selection algorithm is presented using the cross-entropy optimisation method to maximise channel capacity. In contrast with the existing work, the proposed algorithm guarantees a result to within 99% of the true optimum (i.e. the maximal capacity with selected transmit antennas) with substantially low complexity. The simulation results indicate that the proposed algorithm is independent of the relationship between the selected transmit array size and receive array size. The proposed scheme has the potential to make practical MIMO systems with high performance simpler to implement.

MIMO ISI Channel Estimation Using Uncorrelated Golay Complementary Sets of Polyphase Sequences

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, optimal training sequence design for multiple-input multiple-output (MIMO) intersymbol interference channels is addressed, and several novel low-complexity channel estimators are proposed, using uncorrelated Golay complementary sets of polyphase sequences.<footnoteref refid="fnote1"/><footnote id="fnote1"> <footnotepara>A polyphase sequence is a sequence of complex numbers, each of unit magnitude.</footnotepara> </footnote> The theoretical analysis and simulation show that, when the additive noise is Gaussian, the proposed best linear unbiased estimator achieves the minimum possible classical CramÉr–Rao lower bound (CRLB) if the channel coefficients are regarded as unknown deterministics. On the other hand, the proposed linear minimum mean-square error estimator attains the minimum possible Bayesian CRLB when the underlying channel coefficients are Gaussian and independent of the additive Gaussian noise. The proposed channel estimators not only achieve the best estimation performance but can also be implemented with low complexity via DSP or application-specified integrated circuit/field programmable gate array. This has been possible due to the special structures intrinsic to uncorrelated Golay complementary sets of polyphase sequences, which make the proposed channel estimators ready to use in the practical MIMO systems. </para>

An Enhanced Deterministic Sequential Monte Carlo Method for Near-Optimal MIMO Demodulation With QAM Constellations

We propose a low-complexity, linear minimum mean squared error (MMSE)-based sequential Monte Carlo (SMC) technique as an alternative to the sphere decoder for near-optimal demodulation in multiple-input multiple-output (MIMO) systems. Prior to the SMC procedure, the received signal is passed through a linear MMSE-based preprocessing step, which also determines an optimal channel-dependent order of detection and produces a sequential structure. The algorithm then draws the symbol samples in a deterministic fashion, and the survivor paths are selected based on their importance weights. The proposed algorithm exploits the rectangular structure of the QAM signal constellation by separating the real and imaginary parts of the signal to reduce the complexity associated with the listing and weight update steps, resulting in a complexity (in terms of the constellation size M) of O(radicM) as compared to O(M) complexity of the existing SMC algorithms for an M-QAM constellation. We demonstrate through simulations that the new method achieves the sphere decoder performance for V-BLAST systems. Unlike the sphere decoder whose complexity is channel-dependent, our algorithm has a fixed complexity which is channel independent; thus it is well suited for use in practical MIMO systems. Some other interesting features of the algorithm are that it is able to handle MIMO systems with less receive antennas than transmit antennas; and can also deal with multiuser multirate MIMO systems, utilizing a novel ordering scheme. Finally we extend the proposed algorithm to solve the lattice decoding problem and demonstrate the effect of different preprocessing stages on the performance and complexity of the algorithm through extensive simulation results

Low-Complexity Optimal Estimation of MIMO ISI Channels With Binary Training Sequences

In this letter, a novel low-complexity optimal channel estimator using uncorrelated periodic complementary sets of binary sequences is proposed for multiple-input multiple-output (MIMO) intersymbol interference (ISI) channels. The estimator is optimal since it attains the minimum possible Crameacuter-Rao lower bound (CRLB). Moreover, it can be implemented with very low complexity via ASIC/FPGA, which makes it suitable and ready for practical MIMO systems

Prediction of variation in MIMO channel capacity for the populated indoor environment using a Radar cross-section-based pedestrian model

Multipath propagation is a fundamental requirement for the operation of multiple-input multiple-output (MIMO) wireless systems. However, at ultrahigh frequency (UHF) and above, pedestrian movement may significantly affect the multipath propagation conditions in indoor environments. For the first time, a systematic analysis of the effect of pedestrian movement on channel capacity for an otherwise line-of-sight MIMO link in a single room is presented. A novel channel model for the populated indoor environment is also introduced, based on geometrical optics and a detailed radar cross-section representation of the human body. The new model generates a temporal profile for the complex transfer function of each antenna combination in the MIMO system in the presence of specified pedestrian movement. Channel capacity values derived from this data are important in terms of understanding the limitations and possibilities for MIMO systems. Capacity results are presented for a 42-m/sup 2/ single room environment, using a 2.45-GHz narrowband 8/spl times/8 MIMO array with 0.4/spl lambda/ element spacing. Although the model predicts significant increases in the peak channel capacity due to pedestrian movement, the improvement in mean capacity values was more modest. For the static empty room case, the channel capacity was 10.9 b/s/Hz, while the mean capacity under dynamic conditions was 12.3 b/s/Hz for four pedestrians, each moving at the same speed (0.5 m/s). The results presented suggest that practical MIMO systems must be sufficiently adaptive if they are to benefit from the capacity enhancement caused by pedestrian movement.

Semi-blind estimation of channels and symbols for asynchronous MIMO systems

Semi-blind channel estimation and equalisation algorithms for asynchronous multiple input multiple output (MIMO) systems are proposed. MIMO channels are estimated from the second-order statistics of the received signals subject to an ambiguity matrix and unknown time delays. Then some pilot symbols are used to resolve the ambiguity matrix and the time delays. Two methods are presented for equalisation: the direct method and the two-step method. The direct method equalises the symbols directly without explicitly estimating the channels, while the two-step method needs to estimate the channels before recovering the symbols. Only upper bounds for the channel orders and the time delays are needed for implementing the algorithms. Neither the knowledge of real channel orders nor precise synchronisation of different users is required, which makes the algorithm applicable to practical multiuser MIMO systems.

Near-Optimum Soft Decision Equalization for Frequency Selective MIMO Channels

In this paper, we develop soft decision equalization (SDE) techniques for frequency selective multiple-input multiple-output (MIMO) channels in the quest for low-complexity equalizers with error performance competitive to that of maximum likelihood (ML) sequence detection. We demonstrate that decision feedback equalization (DFE) based on soft-decisions, expressed via the posterior probabilities associated with feedback symbols, is able to outperform hard-decision DFE, with a low computational cost that is polynomial in the number of symbols to be recovered and linear in the signal constellation size. Building on the probabilistic data association (PDA) multiuser detector, we present two new MIMO equalization solutions to handle the distinctive channel memory. The first SDE algorithm adopts a zero-padded transmission structure to convert the challenging sequence detection problem into a block-by-block least-square formulation. It introduces key enhancement to the original PDA to enable applications in rank-deficient channels and for higher level modulations. The second SDE algorithm takes advantage of the Toeplitz channel matrix structure embodied in an equalization problem. It processes the data samples through a series of overlapping sliding windows to reduce complexity and, at the same time, performs implicit noise tracking to maintain near-optimum performance. With their low complexity, simple implementations, and impressive near-optimum performance offered by iterative soft-decision processing, the proposed SDE methods are attractive candidates to deliver efficient reception solutions to practical high-capacity MIMO systems. Simulation comparisons of our SDE methods with minimum-mean-square error (MMSE)-based MIMO DFE and sphere decoded quasi-ML detection are presented.