Error Rate Improvement in Underwater MIMO Communications Using Sparse Partial Response Equalization

For iterative detection and decoding (IDD) in multiple-input multiple-output (MIMO) systems, the log-likelihood ratio (LLR) of each coded bit can be found by an optimal bit-wise maximum a posteriori probability (MAP) detector. However, since this MAP detector requires a prohibitively high computational complexity, low-complexity suboptimal detectors are desirable. In this paper, lattice reduction (LR)-based MIMO detection is investigated to derive a low-complexity detector that can achieve near MAP performance for IDD. In order to approximate LLR values incorporating the extrinsic information provided by a soft-input soft-output (SISO) decoder, bit-wise LR-based minimum mean square error (MMSE) filters are derived. Furthermore, in order to minimize the performance degradation due to quantization (or rounding) errors in the LR-based detection, a low-complexity integer perturbed list generation method is proposed, where no tree search is used by taking advantage of a near orthogonal channel basis obtained by LR. Through a complexity analysis and simulations, it is shown that the proposed approach achieves near optimal performance, while the complexity is comparable with that of the MMSE soft cancellation method, which is known to be computationally efficient. As a bit-wise detector, a parallel implementation of the proposed method would be straightforward, which lowers the detection delay.

Multiple Input Multiple Output (MIMO) configurations in radar systems provide architectural and performance advantage over conventional monostatic and bistatic systems due to the implicit diversity characteristics of any MIMO system. Various authors are individually addressed either of these diversities. This work aims at parameterizing all the three, spatial, frequency and waveform diversities and hence designing a new MIMO SAR system for high resolution achievement. This system is designed taking into account both target and clutter, as clutter background pollutes the images substantially. The parameterizations and hence the constraints obtained on the system architecture and transmit signal properties ensure high resolution and better performance over conventional SAR imaging systems.

High-Frequency (HF) radars are operated in the 3–30 MHz frequency band. For oceanographic applications low transmit power HF radar systems have been developed, which use surface electromagnetic wave propagation along the salty ocean surface. This paper presents a new approach to use Multiple Input Multiple Output (MIMO) technique for compact HF ocean radar deployments and positive economic benefits without reducing overall system performance. The initial results show that such MIMO HF radar configuration can be used for both oceanographic measurements and ship tracking applications. Ship detection and tracking are tested using real WERA HF radar measurements for a MIMO configuration with collocated receive antennas. The comparison between standard and MIMO mode results is focused on azimuthal angle estimation.

Three dimensional (3D) Multiple Input Multiple Output (MIMO) is considered as one key technology for 5th Generation mobile communication systems. However, can the capacity derived from a 3D channel impulse response (CIR) better approximate the corresponding capacity derived from the measured CIR? Is there a substantial improvement in the capacity of 3D MIMO system in comparison to the classical 2D case? To answer these questions, extensive field measurements were conducted for the outdoor to indoor scenarios in China and New Zealand. Key channel parameters are extracted from the measured channel impulse response via the space-alternating generalized expectation-maximization algorithm, followed by the reconstruction of the 32 × 56 CIR according to 2D and 3D channel model. Then CIRs are used to evaluate the channel capacity and comparative simulation results demonstrate that the 3D MIMO capacity closely approximates the capacity predicted with practical CIRs. Moreover, obvious enhancements in the capacity of 3D channel is observed in comparison to 2D case. In addition, the distribution of eigenvalues and the number of contributing eigenvalues are also investigated.

This paper investigates the optimization of the coded orthogonal frequency division multiplexing (OFDM) transmitted signal in a synthetic aperture radar (SAR) context. We propose to design OFDM signals to achieve range ambiguity mitigation. Indeed, range ambiguities are well known to be a limitation for SAR systems which operates with pulsed transmitted signal. The ambiguous reflected signal corresponding to one pulse is then detected when the radar has already transmitted the next pulse. In this paper, we demonstrate that the range ambiguity mitigation is possible by using orthogonal transmitted wave as OFDM pulses. The coded OFDM signal is optimized through genetic optimization procedures based on radar image quality parameters. Moreover, we propose to design a multiple-input multiple-output (MIMO) configuration to enhance the noise robustness of a radar system and this configuration is mainly efficient in the case of using orthogonal waves as OFDM pulses. The results we obtain show that OFDM signals outperform conventional radar chirps for range ambiguity suppression and for robustness enhancement in 2 ×2 MIMO configuration.

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.

As compared to uncoded unitary space-time modulation (USTM), channel coded USTM has received increased attention for its large coding gain. However, low-density parity-check (LDPC) coded USTM has only received limited attention. This paper proposes a scheme of combining LDPC code with USTM for noncoherent MIMO communication system over Rayleigh flat fading and additive white Gaussian noise (AWGN) channel. At the receiver, considering the soft information required by the belief-propagation (BP) iterative decoder of the LDPC code, we deduce a low complexity maximum a posteriori probability (MAP) demodulating algorithm for a special USTM based on the sine-cosine function, SC-USTM for short. We combine the MAP with the maximum likelihood (ML) demodulating algorithm based on the SC-USTM in order to generate a novel dual-demodulator for further decreasing the computational complexity of the demodulating/decoding system. For improving the performance of the receiver, the iterative feedback scheme between the MAP demodulator and the BP decoder is designed. Comparing with the uncoded USTM, our LDPC-coded USTM can obtain about 15 - 17 dB coding gain at 10-5 BER.

In this paper, a new signal detection scheme for overloaded multiple-input multiple output (MIMO) systems is proposed. In MIMO signal detection with belief propagation (BP), a factor graph consists of many loops that arise high complexity and cause performance degradation due to outliers. Various schemes have been proposed to overcome these issues. In BP with maximal ratio combining (MRC) and minimum mean square error (MMSE) pre-cancellation, a conventional scheme applies MRC on received signals in advance to obtain diversity gain to improve bit error rate (BER) performance as compared with BP using only MMSE pre-cancellation. To achieve further performance improvement, BP using a combined channel matrix is proposed in this paper. In the proposed scheme, the number of observation nodes is increased by combining a part of an original channel matrix to the channel matrix with MRC and MMSE pre-cancellation to enhance diversity gain. Numerical results obtained through computer simulation show that the BER performance of the proposed scheme is superior to that of BP or BP with MRC and MMSE pre-cancellation. The proposed scheme improves BER performance by about 3.1 dB at a BER of 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> as compared with the BP withMRC and MMSE pre-cancellation. The computational complexity of the proposed scheme increases as the number of rows of the additional channel submatrix. It is in the same order of magnitude as that of the original BP based MIMO detection scheme.

Space-time techniques for multiple-input multiple-output (MIMO) systems potentially provide vast increases in capacity. In order to achieve the quoted capacity gains the MIMO channel impulse response (CIR) must be known or estimated. Thus far, existing MIMO channel estimation techniques have been limited to the narrowband case or cater specifically for coded space-time systems. In this paper, we present a novel training-based MIMO channel estimation scheme for an uncoded layered space-time system that operates in the wideband frequency-selective fading environment. The method uses a pilot matrix consisting of pilot symbols derived from the Paley-Hadamard matrix in order to jointly estimate the individual CIR of the MIMO channel. The orthogonal property of the pilot matrix is utilized to resolve both intersymbol interference and intercarrier interference of the multiple transmit and received signals. The Paley Toeplitz structure is also exploited in order to minimise the length of the pilot sequence for a given length of CIR and thus maximise the effective data throughput. Results are presented which demonstrate the accuracy of the proposed channel estimation scheme and its performance in a layered space-time system.

In this paper, we propose space-polarization shift keying (SPSK) modulation scheme for multiple-input multiple-output (MIMO) systems employing dual-polarized antenna array, where the concept of space shift keying (SSK) is extended to include both the space and polarization dimensions. In the SPSK, polarization index also been used to relay the information along with the antenna index. As a result, the proposed transmission scheme reduces the signal processing complexity at the receiver exponentially when compared to the SSK scheme, for a given target transmission rate. In this correspondence, we investigate the performance of $$ 4\times 4 $$4×4 SPSK---MIMO configurations over different wireless channel scenarios for a range of values of the correlation coefficient and the Rician K-factor. We also highlight the effect of random orientation of antennas at the mobile unit on the bit error rate performance of SSK and SPSK transmission scheme. By using analytical results and simulations, we show that the proposed scheme outperforms the SSK scheme under line-of-sight channel conditions and its performance is comparable to SSK under non-line-of-sight channel conditions, for various receive-antenna inclination angle.

Recent demand for capacity increase in mobile communications urges the development of both multiple- input multiple-output (MIMO) and small cells. However, overlapping coverage areas between neighboring small cells results in interference-limited networks, where the capacity of the network is severely degraded without superior intercell interference management (IIM) techniques. As one of the superior IIM techniques, the power control intercell interference coordination (ICIC) optimizes downlink transmit powers in the network. This paper proposes an IIM scheme consisting of both neural networks (NNs) power control on the transmitter side and interference cancellation (IC) on the receiver side. Computer simulations examine networks of MIMO systems with the power optimization using some ICIC algorithms: NN, the greedy search, the belief propagation (BP), and the maximum power, combined with IC on the receiver side. In addition, the deep learning, a breakthrough technique for NN with multi-layer structures, is also applied to mobile communications. The results show that the performance of NN is very close to that of the greedy search and superior to that of BP. Complexity of NN is much less than that of BP, and thus NN is suitable for IIM. It is also demonstrated that employing IC provides high capacity gain.

Recently many studies have been done on different issues of using multiple antennas at transmit and receive sides of a radar system in a MIMO (Multiple Input Multiple Output) configuration. In addition, for the electronic warfare‟s purposes, the utilization of available signals of the environment to detect the targets has gained considerable attention in recent years. Such passive radars use the transmitter of other purposes (e.g. the GSM or television stations) as their noncooperative transmitter. Moreover, the idea of using multiple of such illuminators to get the advantages of MIMO technology, besides the advantages of passive illumination, is new and attractive. An excellent candidate of such configuration is a DVB-T SFN (single frequency network). However, various obstacles and considerations appear when working with a MIMO DVB-T based passive radar system. In this paper, we consider two such problems: tracking multiple targets and choosing appropriate positions for the receive antennas in the surveillance region. First, based on the previously developed schemes to associate the receive data to the transmitters and targets, we propose a tracking algorithm to extract the true targets from the candidate targets. Then, we develop a procedure to place the receivers of such MIMO passive systems in such positions that result in better performance of the aforementioned association algorithm.

Multiple-input multiple-output (MIMO) technology is a breakthrough that considerably improves the throughput of wireless networks. The ever-growing technology has improved the smartphones to meet the requirements of current IEEE standards for wireless local area networks (WLANs). However, the benefits of smartphones are always constrained by their battery life. This study investigates the energy consumed by a smartphone during the transmission and reception of data. The effect of the different features of 802.11n (including Modulation and Coding Scheme (MCS) and MIMO) is investigated in terms of throughput and energy consumption using a network simulator (NS3). Additionally, the energy consumption during the process of transmission and reception is compared by using per-bit energy consumption for data transfer with different MIMO configurations and physical data rates. The results show that increasing the system configuration beyond 2×2 MIMO improves the throughput and reduce the energy consumption. In addition, a simple energy consumption model is developed for transmission and reception based on MIMO parameter.

In this article, a planar dual-element frequency reconfigurable multiple-input multiple-output (MIMO) antenna for ultra-wideband (UWB) applications is studied. The frequency band can be switched between UWB operation and single band rejected UWB performance using a pair of PIN diodes in the MIMO configuration. The presented antenna is comprised of two similar slotted circular radiators, having tapered microstrip feedlines and separate partial ground planes. An RT/Duroid 5880 substrate with size 54 × 54 mm2 is used for the design purpose. Rotational symmetry between the radiators and diagonally oriented t-shaped decoupling structure behind the substrate have been utilized for high isolation purpose. The designed MIMO antenna exhibits UWB performance in mode 1. In other mode, the antenna operates in the frequency range 2.46–10.44 GHz with Worldwide Interoperability for Microwave Access (WiMAX) band rejection. Thus, the MIMO antenna exhibits on-demand single band rejection behavior depending on the switching conditions of the diodes. The measured isolation is greater than −20 dB in both the modes. The presented MIMO configuration possesses compact and planar geometry with high gain, good isolation, ultrawideband performance with reconfigurable band elimination, high efficiency and efficient diversity performance parameters. The suggested antenna is a good choice to be utilized for portable UWB MIMO applications.

A improved algorithm to perform channel estimation and equalization for multiple input multiple output(MIMO) systems in frequency and time-selective fading environments is put forward. lt contains two steps: training and tracking. In training phase, improved Kalman filtering, namely robust Kalman filtering(RKF), is exploited to estimate channel impulse response(CIR). After that, in tracking stage,the RKF and minimum mean-square error feedback decision equalizer (MMSE-DFE) cooperate to track the time-varying channel. The RKF recursions is presented and a closed-form solution for baud rate MIMO MMSE-DFE under perfect knowledge of CIR and correct past decisions conditions is derived. In addition, it regards unknown dc-offset due to zero intermediate frequency(IF) at the receiver as the mean of measurement noise, which is estimated as a byproduct through robust Kalman filters. Finally, it is compared with well-known ones,such as least mean-square (LMS), recursive least square (RLS), Kalman filtering (KF). All these show that the proposal exhibits better performance.