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This study explores the performance of multiple-input multiple-output (MIMO) systems with one-bit analog-to-digital converters (ADCs) over Rayleigh fading channels. We particularly aim to characterize the pairwise error probability (PEP) achieved by maximum likelihood detection (MLD), which provides the optimal detection performance of the considered systems. First, the upper bound of the PEP is derived by leveraging Jensen’s inequality and the Chernoff bound. The asymptotic bounds of the PEP are then characterized to clarify the impact of the one-bit ADCs on the diversity order of the MIMO systems. Notably, the diversity order of the MIMO systems with one-bit ADCs is the same as the number of receive antennas only when transmitting two symbol vectors with the opposite sign. Except for this special case, the asymptotic bound of the PEP is saturated at a high signal-to-noise ratio due to the use of the one-bit ADCs. Using simulations, we verify that the analytical results coincide with the asymptotic behavior of the PEP of the MLD for MIMO systems with one-bit ADCs over Rayleigh fading channels. [ABSTRACT FROM AUTHOR]

This paper develops three low-complexity detection schemes for the spatial modulation (SM) Multiple Input Multiple Output (MIMO) systems. We first propose a reduced complexity maximum likelihood (RC-ML) detection scheme. For the practical values of the modulation index, the proposed RC-ML method is simpler than the existing hard-limiting-based ML schemes. The two other proposals are based on a suboptimal Maximum Ratio Combining (MRC) detection method. We present a new analysis of the MRC detector in the uncorrelated Rayleigh fading channel and identify the system operational scenarios for which the MRC performance is nearly identical to the ML performance. Our proposals — a hybrid MRC-ML method and an MRC scheme with rank reduction — are inspired by this analysis. The analytical and simulation results show that the proposed MRC-based schemes can attain a near-optimal performance while reducing the complexity of the ML-based SM receiver. [ABSTRACT FROM AUTHOR]

Low-complexity improved-rate generalised spatial modulation (LCIR-GSM) is proposed to mitigate the high complexity of the mapping book design and demodulation of variable- ${N_a}$ GSM. Specifically, first of all, we propose two efficient schemes for mapping the information bits to the transmit antenna activation patterns, which can be readily scaled to massive MIMO setups. Secondly, we derive a pair of low-complexity near-optimal detectors, one of which has a reduced search scope, while the other benefits from a decoupled single-stream based signal detection algorithm. Finally, the performance of the proposed LCIR-GSM system is characterised by the improved error probability upper bound. Our simulation results confirm the improved error performance of our proposed scheme, despite its reduced signal detection complexity. [ABSTRACT FROM AUTHOR]

A novel index modulation with spherical code and its constellation mapping are proposed. We derive the closed form of the approximation bound of the bit error rate (BER) of the OFDM-IM system based on four-dimensional spherical code. Our derived BER is very close to the simulation results. And different constellation mapping method have different BER performance and the gap is less than 0.2 dB. To reduce the detection complexity which is caused by the high-dimensional modulation, a DNN-based receiver with partial-connected layer is proposed. Simulation results show that our proposed DNN-based receiver can greatly reduce the complexity while its BER performance is close to the classical maximum likelihood detection method. [ABSTRACT FROM AUTHOR]

Analysis on the exact error rate of jointly optimal (JO) maximum likelihood (ML) multiuser detection is limited in the existing literature owing to its high computational complexity. In this paper, the JO ML detection of two quadrature phase-shift keying (QPSK) signals with an arbitrary relative phase offset is investigated. Exact, analytical symbol error rate (SER) and bit error rate (BER) formulas are derived for two users with no less than 3 dB power difference between them. Closed-form union bounds on the user SER and BER with an arbitrary phase offset and an arbitrary user power ratio are also given as a simpler approach to acquire the asymptotic error rate performance. Furthermore, insights on the potentials and properties of the JO ML detector regarding its error rate behaviors for each user are revealed through comparisons with the successive interference cancellation receiver. The accuracies of the obtained formulas are demonstrated through simulation. The results show the error rates for the two-user QPSK case no longer follow the classic knowledge on the error rate behaviors in the single signal detection. In addition, the performance and dB penalty employing different modulation types are also compared and discussed. [ABSTRACT FROM AUTHOR]

This paper focuses on the issue of achieving transmit diversity for the multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system working with quadrature index modulation (QIM). Inspired by the ideas of quadrature spatial modulation (QSM) and quadrature space-frequency index modulation (QSF-IM), parts of the space-frequency resource units in each resource block (RB) of the MIMO-OFDM system are activated twice independently to send the in-phase and quadrature components of a space-frequency code, respectively, to achieve the second order transmit diversity. Thus the proposed scheme is called space-frequency coded QIM (SFC-QIM). The SFC-QIM scheme allows for a linear-complexity maximum likelihood (ML) receiver, which benefits from the orthogonality between the real and imaginary parts of the symbols in the SFC codewords. Owing to obtaining higher diversity order, simulation results of bit error rate (BER) performance demonstrate that the new SFC-QIM scheme outperforms some existing IM schemes in both independent and identically distributed (i.i.d.) and correlated Rayleigh fading channels. [ABSTRACT FROM AUTHOR]

In this paper, the uplink sparse code multiple access over universal filtered multicarrier (SCMA-UFMC) is studied. In SCMA-UFMC, each sub-band of UFMC is occupied by multiple users through SCMA. Note that the even-component of frequency domain (FD) received signal suffers from neither inter-sub-band interference nor inter-sub-carrier interference while the odd-component suffers from both. The message passing algorithm (MPA) is first employed to perform multiuser detection by utilizing only the even-component. Next, to improve the performance, the odd-component is further utilized. In this improvement, reliable estimates obtained by MPA over even-component are reconstructed and cancelled from odd-component, and then only a very small number of most-unreliable user data are refined by maximum likelihood method. Moreover, the union bound of the average symbol error probability (ASEP) of maximum likelihood detection using only even-component is derived, from which it is shown that ASEP is sub-band-independent. Finally, simulation results are given to demonstrate the performance of the proposed scheme and the effectiveness of the analytical ASEP result. [ABSTRACT FROM AUTHOR]

This paper proposes a low-complexity reinforcement learning detection (RLD) algorithm for multi-input multi-output systems with one-bit analog-to-digital converters. The proposed algorithm exploits pairs of quantized received signals and detected symbols as training examples to train the likelihood function (LF) of the system. A major challenge in optimizing the RLD algorithm is to determine the optimal policy that decides whether to exploit the training examples based on their reliabilities. Determining the optimal policy inherently involves huge complexities in reflecting all possible transitions among candidate symbols. Thus, we simplify the optimal policy by considering only the most probable candidates among all possible decisions to reduce this complexity. Another major challenge in applying the RLD algorithm is that it requires high computational complexity to produce soft information for detection. Thus, we define new branch and path metrics derived from the LF and then remove the candidate symbols whose path metrics are smaller than a pre-defined value to alleviate the complexity. Moreover, we analyze the complexity of the proposed algorithm by deriving the expected number of surviving candidates. Simulation results show that the proposed algorithm provides a better performance-complexity tradeoff than the conventional RLD algorithm. [ABSTRACT FROM AUTHOR]

Detection of cyclostationary (CS) signals has been addressed by means of generalized likelihood ratio test criteria. However, an accurate maximum likelihood estimator requires the estimation of cycle period (CP) as a priori information, which has not yet been correctly addressed in the literature. In this correspondence, an estimator of CP is devised under the information theoretic criterion(ITC) framework for long observation regime. In particular, we formulate asymptotic log-likelihood function in discrete frequency domain. From the evidence that direct implementation of ITC leads to a high probability of CP overestimation, we reformulate ITC by Bayesian information criterion (BIC), and derive an accurate penalty function. The proposed BIC variant appears to be consistent as signal-to-noise ratio increases. Numerical simulations corroborate the feasibility of the proposed estimator and show its superiority over state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

Sphere decoding (SD) based detection schemes for sparse code multiple access (SCMA) systems have recently received attention due to their promising features. However, the existing SD-based schemes can only be applied to SCMA systems with constellations that possess a certain structure. In this paper, we propose a novel SD-based detection scheme, namely improved SD (ISD), for SCMA that achieves the optimal maximum likelihood detector for any arbitrary regular or irregular constellations. To overcome the rank deficiency problem of the SCMA channel matrix, we fix a portion of the transmitted symbols and obtain an optimal detection problem that is equivalent to the original SCMA detection problem for all types of constellations. Moreover, due to the sparse nature of SCMA, the partial metric at each layer is evaluated in such a way that is independent of users assigned to each resource element. This, in turn, reduces the average complexity of ISD. [ABSTRACT FROM AUTHOR]

Underwater acoustic (UWA) channels exhibit double selectivity in both time and frequency domains, posing significant challenges to reliable UWA communications. This correspondence paper presents a novel spatial block coding scheme integrated with complementary code keying (CCK) modulation to exploit both spatial diversity and code diversity against doubly selective fading channels. The proposed spatial-CCK modulation utilizes multiple transmit transducers and extends the traditional CCK code set to improve receiver performance. We introduce novel code design criteria by considering maximum likelihood detection receivers under fast Rayleigh fading channel condition. Simulation and lake experiment results demonstrate substantial performance gain by the proposed spatial-CCK scheme over the conventional space–time codes without incurring additional high complexity cost for UWA channels. [ABSTRACT FROM AUTHOR]

In this paper, we consider a signal-level maximum likelihood detection for multiple-input multiple-output filter-bank multicarrier-quadrature amplitude modulation (MIMO FBMC-QAM) system with two prototype filters. Under high-frequency selective channels, the conventional symbol-level maximum likelihood detection suffers from degraded bit error rate performances because it cannot utilize the oversampling characteristics of the signal-level. However, due to intrinsic interference and high computational complexity, a maximum likelihood detection cannot be applied directly to the signal-level. To solve this problem, we propose a signal-level maximum likelihood detection based on partial candidates. Utilizing the diagonal dominant characteristics of effective channels, the proposed signal-level maximum likelihood detection can reduce the effect of intrinsic interference with practical computational complexity. Moreover, a region ordering algorithm based on Euclidean distance can improve the efficiency of the proposed signal-level maximum likelihood detection. Simulation results show that the proposed signal-level maximum likelihood detection can outperform the bit error rate performance of the conventional symbol-level maximum likelihood detection. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient pruning algorithm for MIMO detector, which not only achieves the same performance of the maximum likelihood (ML) decoder, but also massively reduces the number of visiting nodes. The proposed algorithm applies correct sorting order so that it achieves the same performance of the ML decoder. Thanks to the use of the correct ordering, both child and sibling nodes can be pruned efficiently. As a result, the number of visiting nodes is significantly reduced. To acquire properly sorted order, we propose fast sorting algorithms that generate the exact sorted sequence. Furthermore, the proposed schemes can be applied in SISO MIMO detector. The advantages of the proposed sphere decoder become more pronounced in high-order modulation schemes. [ABSTRACT FROM AUTHOR]

This correspondence paper proposes a low-complexity adaptive spatial modulation (ASM) scheme, which is based on sphere search (SS). To find the optimal ASM mode, the existing ASM schemes examine each error vector in the search space. By contrast, in the proposed SS-aided strategy, the search space is reduced to the error vectors inside a sphere, which results in significant complexity reduction. By exploiting a similar structure between the error vectors in ASM and symbol vectors in generalized spatial modulation (GSM), we modify the sphere decoder for GSM to develop an efficient two-step SS scheme for ASM. In addition, an early termination scheme is employed to further reduce the computational load of the SS process for each ASM mode. Simulation results show that SS-aided ASM provides a significant reduction in computational complexity compared to the existing ASM schemes. [ABSTRACT FROM AUTHOR]

In order to improve on existing radio communications for railways, cognitive radio (CR) is a promising concept, allowing the combination of artificial intelligence and software-defined radios. To ensure the best environmental awareness, as required by CR receivers, automatic modulation identification is a key feature for promoting efficient and secure communications in the CR context. This paper deals with blind modulation identification in the railway transmission environment and specifically considers its two major constraints: the high-speed and the impulsive nature of the noise. To achieve this goal, we propose a feature-based process of blind identification, which is made up of three subsystems: impulsive noise mitigation (which is the main contribution of this paper), feature extraction, and classification. For the purpose of mitigating the impulsive noise, we introduce a blind filtering myriad-based approach, which, in turn, requires the estimation of the noise parameters. Simulation results prove that the developed filtering approach provides a good filtering performance, and consequently, high identification performances of the overall identification system. [ABSTRACT FROM AUTHOR]

In space-time shift keying (STSK), the information is conveyed by both the spatial and time dimensions, which can be used to strike a tradeoff between the diversity and multiplexing gains. On the other hand, orthogonal frequency-division multiplexing (OFDM) relying on index modulation (IM) conveys information not only by the conventional signal constellations as in classical OFDM, but also by the indices of the subcarriers. In this paper, we combine the benefits of STSK and IM in order to strike a flexible tradeoff between the throughput and bit-error performance by transmitting extra information bits in each subcarrier block, while increasing the diversity order. In order to further improve this tradeoff, as well as to decrease the complexity of the detector, compressed sensing is combined with the proposed STSK-aided IM system. We first present the maximum likelihood (ML) detection, which forms the best-case bound on the proposed system's performance. Then, we propose a pair of reduced-complexity detection algorithms capable of approaching the ML detector's performance. Furthermore, in order to attain a near capacity performance, we propose a soft-input soft-output decoder that is capable of exchanging soft information with a channel decoder through iterative decoding. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel generalized space shift keying (GSSK) detection algorithm by exploiting the inherent sparse property of GSSK signal. In particular, we formulate the GSSK detection into a sparse convex optimization problem. The key contribution of the proposed algorithm lies in the strategical adoption and transformation of the sparse reconstruction (SR) from image processing to GSSK detection. The proposed SR detector achieves better performance than all existing suboptimal solutions with comparable computational complexity. In order to further improve the performance of the SR algorithm, we develop another approach, i.e., the iterative SR algorithm, which utilizes the result of the SR algorithm as the start point and enhances the detection performance gradually in each iteration. The simulation results confirm the efficiency of both of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Space shift keying (SSK) modulation is an emerging transmission technique for multiple-input multiple-output (MIMO) wireless channels, which exploits the spatial domain to convey information. In this paper, we present a layered space shift keying (LSSK) modulation scheme to fully exploit the spatial domain to transmit information bits, where a layered architecture is developed to achieve spatial multiplexing transmission in an SSK system. Specifically, LSSK leverages the rotated signals predetermined at the transceiver to identify different layers and improve the bit-error-rate (BER) performance. The layered signals are directly generated by the proposed LSSK modulation method with a low computational overhead. Furthermore, we propose a layered-and-joint (LJ) near-optimal detection algorithm based on the layered architecture of LSSK to reduce the detection complexity. In LJ detection, layered detection is performed to find a set of detection candidates for each layer, and then, joint detection is performed with these candidates. We show that the performance of LJ detection is quite close to that of optimal maximum-likelihood detection with significantly reduced detection complexity for high-spectrum-efficiency scenarios. Results demonstrate that the proposed LSSK scheme substantially improves the spectrum efficiency of an SSK system and outperforms other existing MIMO schemes. [ABSTRACT FROM PUBLISHER]

In this paper, constellation collaborated nonlinear orthogonal space–time block codes (OSTBCs) for wireless communication systems are considered. Using the recently developed unique factorization of signals, several uniquely factorable constellation pairs (UFCPs) generated from cross quadrature amplitude modulation (QAM) constellations are chosen for transmission through all the transmitter antennas, with one random symbol acting as a coordinator to control all the symbols embedded in each coding matrix. The coding gains of collaborated orthogonal codes are calculated, and some optimal constellation pairs with maximum coding gains are presented, including orthogonal codes with different antennas and UFCPs with different groups. Despite the fact that the proposed code is nonlinear, a fast maximum likelihood (ML) decoding algorithm is developed, and its complexity is analyzed in detail. By comparing the decoding complexity of conventional Alamouti code, the ML algorithm, and the fast ML decoding algorithm of collaborative Alamouti code, it can be observed that the complexity of fast ML algorithm is still linear in terms of the square root of the cardinality of the cross QAM constellations with no performance loss. Computer simulations are performed to verify the performance of collaborative OSTBCs and the fast ML Algorithm under different conditions, and the results demonstrate that the average error rate of the collaborative nonlinear orthogonal codes outperforms that of the conventional OSTBCs. [ABSTRACT FROM PUBLISHER]

We propose a new differential maximum-likelihood (DML) combiner for noncoherent detection of the differential amplify-and-forward (D-AF) relaying system in the time-selective channel. The weights are computed based on both the average channel quality and the correlation coefficient of the direct and relay channels. Moreover, we derive a closed-form approximate expression for the average bit error rate (BER), which is applicable to any single-relay D-AF system with fixed weights. Both theoretical and simulated results are presented to show that the time-selective nature of the underlying channels tends to reduce the diversity gains at the low-signal-to-noise-ratio (SNR) region, resulting in an asymptotic BER floor at the high-SNR region. Moreover, the proposed DML combiner is capable of providing significant BER improvements compared with the conventional differential detection (CDD) and selection-combining (SC) schemes. [ABSTRACT FROM PUBLISHER]

Operation of full-duplex systems requires efficient mitigation of the self-interference signal caused by the simultaneous transmission/reception. In this paper, we propose a maximum-likelihood (ML) approach to jointly estimate the self-interference and intended channels by exploiting its own known transmitted symbols and both the known pilot and unknown data symbols from the other intended transceiver. The ML solution is obtained by maximizing the ML function under the assumption of Gaussian received symbols. A closed-form solution is first derived, and subsequently, an iterative procedure is developed to further improve the estimation performance at moderate-to-high signal-to-noise ratios (SNRs). We establish the initial condition to guarantee the convergence of the iterative algorithm to the ML solution. In the presence of considerable phase noise from the oscillators, a phase noise estimation method is proposed and combined with the ML channel estimator to mitigate the effects of the phase noise. Illustrative results show that the proposed methods offer good cancelation performance close to the Cramer–Rao bound (CRB). [ABSTRACT FROM AUTHOR]

In practical applications, an imperfect channel estimate over a noisy channel is inevitable. This paper investigates an interference-aware receiver in which colored-estimation-noise-based maximum-likelihood (CEN-ML) detection is employed to mitigate the impact of imperfect channel estimates. It is shown that the CEN-ML detection, which treats the channel estimation errors as colored noise, has superior performance and is robust to imperfect channel estimation. However, a CEN-ML interference-aware detector usually requires computational efforts that are too complex for multiple-input–multiple-output (MIMO) interference-limited systems. To reduce the complexity, this paper proposes new methods for both the preprocessing and tree-search stages of an interference-aware sphere detector (SD). First, a channel extended matrix is constructed using the information from channel estimation errors in a preprocessing stage. The channel extension model can reduce the complexity without performance loss. Second, two tree pruning (TP) criteria are developed in a tree-search stage to make the implementation of the CEN-ML SD feasible. The first criterion is based on a lower bound of the CEN-ML metric and can achieve the same result as the optimal brute-force method. The second criterion is derived from an approximated metric and can further reduce the complexity with small performance loss. Simulation results for typical Third-Generation Partnership Project Long-Term Evolution (LTE)/LTE-Advanced scenarios show that the new methods provide the ability to deal with the channel estimation errors and to achieve a better tradeoff between complexity and performance (e.g., in terms of throughput or error rate) in interference-limited scenarios. The proposed low-complexity CEN-ML SD can have a gain of more than 10 dB than the other investigated detection for 16-ary quadrature amplitude modulation (QAM) or 64-QAM at a target coded block error rate (BLER) of \mbox10^-2. [ABSTRACT FROM AUTHOR]

Using a spatial multiplexing transmission scheme can improve the data rate in multiple-input–multiple-output (MIMO) relaying systems, while making signal detection more difficult at receivers. Aiming at lowering the computational complexity of the receiver, this paper proposes a maximum likelihood combining (MLC) algorithm for spatial multiplexing MIMO amplify-and-forward (AF) relaying systems in a Rayleigh flat-fading environment, which is implemented before maximum likelihood (ML) detection. The combining signal and equivalent channel are opportunely designed based on the ML rule in the MLC algorithm. We also formulate the diversity gain of the systems that employ the MLC algorithm mathematically, induced by the Chernoff bound of pairwise error probability (PEP). An upper bound on the symbol error probability (SEP) for the MLC algorithm with multiple modulations is also given, based on the derived bound of PEP. Moreover, the complexities of ML receivers adopting the MLC algorithm and the conventional vector combining (VC) algorithm are analyzed. Numerical simulations indicate that systems with the MLC algorithm achieve the same performance while consuming lower computational complexity compared to that with the VC algorithm. [ABSTRACT FROM PUBLISHER]

In this paper, we present an approach to combine measurements from inertial sensors (accelerometers and gyroscopes) with time-of-arrival measurements from an ultrawideband (UWB) system for indoor positioning. Our algorithm uses a tightly coupled sensor fusion approach, where we formulate the problem as a maximum a posteriori (MAP) problem that is solved using an optimization approach. It is shown to lead to accurate 6-D position and orientation estimates when compared to reference data from an independent optical tracking system. To be able to obtain position information from the UWB measurements, it is imperative that accurate estimates of the UWB receivers' positions and their clock offsets are available. Hence, we also present an easy-to-use algorithm to calibrate the UWB system using a maximum-likelihood (ML) formulation. Throughout this work, the UWB measurements are modeled by a tailored heavy-tailed asymmetric distribution to account for measurement outliers. The heavy-tailed asymmetric distribution works well on experimental data, as shown by analyzing the position estimates obtained using the UWB measurements via a novel multilateration approach. [ABSTRACT FROM PUBLISHER]

In this paper, the error performance of physical-layer network coding (PNC) is studied in multiple-antenna two-way relay channels (TWRCs), where two users exchange their messages with the help of a relay. We assume that the TWRC system uses binary phase-shift keying (BPSK) modulation and that all channels are Rayleigh faded. In particular, we consider a general system model where two users may have different numbers of antennas and different average signal-to-noise ratios (SNRs) to the relay. Considering a TWRC with multiple antennas at both users and the relay [referred to as multiple-input multiple-output (MIMO)-TWRC], we derive the upper and lower bounds on the uplink error probability of PNC based on maximum-likelihood (ML) detection. In this scheme, a transmit antenna selection (TAS) strategy is applied at two users, where each user selects the strongest transmit antenna for transmission. Furthermore, we also present the upper and lower bounds for two special cases, namely, the single-input multiple-output (SIMO)-TWRC with single-antenna users and the multiple-antenna relay and the multiple-input single-output (MISO) TWRC with multiple-antenna users and the single-antenna relay. Then, the diversity order is investigated for the schemes. We show that the PNC with TAS outperforms the PNC with space–time block codes (STBCs) significantly. The numerical results also demonstrate that our bounds are very tight to the Monte Carlo simulation. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a synchronization and channel estimation method for amplify-and-forward two-way relay networks (AF-TWRNs) based on a low-complexity maximum-likelihood (LCML) algorithm and a joint synchronization and channel estimation (JSCE) algorithm. For synchronous AF-TWRNs, the LCML algorithm blindly estimates general nonreciprocal flat-fading channels. We formulate the channel estimation as a convex optimization problem and obtain a closed-form channel estimator. Based on the mean square error (MSE) analysis of the LCML algorithm, we propose a generalized LCML (GLCML) algorithm to perform channel estimation in the presence of the timing offset. Based on the approximation of the LCML algorithm, the JSCE algorithm is proposed to estimate jointly the timing offset and channel parameters. The theoretical analysis shows that the closed-form LCML channel estimator is consistent and unbiased. The analytical MSE expression shows that the estimation error approaches zero in scenarios with either a high signal-to-noise ratio (SNR) or a large frame length. Monte Carlo simulations are employed to verify the theoretical MSE analysis of the LCML algorithm. In the absence of perfect timing synchronization, the GLCML algorithm selects an estimation sample, which produces the optimal channel estimation, according to the MSE analysis. Simulation results also demonstrate that the JSCE algorithm is able to achieve accurate timing offset estimation. [ABSTRACT FROM PUBLISHER]

This paper analyzes the outage performance of cognitive relay networks operating in the same frequency band of a primary transceiver. Different from previous works, opportunistic decode-and-forward (ODF) and uncoded decode-and-forward (UDF) relaying schemes are considered, in which the relay makes either a hard decision on whether or not to transmit or generates soft information of the received signal by using the maximum-likelihood (ML) detection. To facilitate the coexistence between the cognitive user (CU) and the primary user (PU), the transmit power of both the source and the relay should be optimized to minimize the outage probability of the CU, while satisfying both the outage probability constraint on the PU and their transmit power constraints. The resulting optimization problem for the ODF scheme is generally nonconvex, but the suboptimal solution can be obtained when the decoding rate threshold of the relay is sufficiently small. Whereas for the UDF scheme, the suboptimal solution is obtained by minimizing the upper bound of its outage probability. For comparison, traditional DF relaying with optimal power allocation and direct transmission are also investigated. Simulation results confirm the tightness of suboptimal solutions and the negligible performance gap for both the ODF and the UDF schemes, and demonstrate the performance improvement provided by both schemes, particularly when the relay is far from the primary receiver. [ABSTRACT FROM PUBLISHER]

This paper describes a sensor fault-tolerant control (FTC) for electric-vehicle (EV) powertrains. The proposed strategy deals with speed sensor failure detection and isolation within a reconfigurable induction-motor direct torque control (DTC) scheme. To increase the vehicle powertrain reliability regarding speed sensor failures, a maximum-likelihood voting (MLV) algorithm is adopted. It uses two virtual sensors [extended Kalman filter (EKF) and a Luenberger observer (LO)] and a speed sensor. Experiments on an induction-motor drive and simulations on an EV are carried out using a European urban and extraurban driving cycle to show that the proposed sensor FTC approach is effective and provides a simple configuration with high performance in terms of speed and torque responses. [ABSTRACT FROM PUBLISHER]

The order of a communications channel is the length of its impulse response. Recently, several works have tackled the problem of estimating the order of a frequency-selective multiple-input–multiple-output (MIMO) channel. However, all of them consider a single order, despite the fact that a MIMO channel comprises several subchannels (specifically, as many as the number of inputs times the number of outputs), each one possibly with its own order. In this paper, we introduce an algorithm for maximum-likelihood sequence detection (MLSD) in frequency- and time-selective MIMO channels that incorporates full estimation of the MIMO channel impulse response (CIR) coefficients, including one channel order per output. Simulation results following the analytical derivation of the algorithm suggest that the proposed receiver can achieve significant improvements in performance when transmitting through a MIMO channel that effectively comprises subchannels of different lengths. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a precoder selection criterion for the maximum-likelihood (ML) detector in limited-feedback spatial multiplexing systems. The exhaustive search for the optimal ML precoder selection requires very high computational complexity. As a good compromise, we propose a simple precoder selection scheme for the ML detector. Numerical results show that the proposed scheme achieves both the diversity order of the ML detector and the performance enhancement of the limited-feedback spatial multiplexing. [ABSTRACT FROM PUBLISHER]

Multicarrier code-division multiple-access (MC-CDMA) system performance can severely be degraded by multiaccess interference (MAI) due to the carrier frequency offset (CFO). We argue that MAI can more easily be reduced by employing complex carrier interferometry (CI) codes. We consider the scenario with spread gain N, multipath length L, and N users, i.e., a fully loaded system. It is proved that, when CI codes are used, each user only needs to combat 2(L - 1) (rather than N - 1) interferers, even in the presence of CFO. It is shown that this property of MC-CDMA with CI codes in a CFO channel can be exploited to simplify three multiuser detectors, namely, parallel interference cancellation (PIC), maximum-likelihood, and decorrelating multiuser detectors. The bit-error probability (BEP) for MC-CDMA with binary phase-shift keying (BPSK) modulation and single-stage PIC and an upper bound for the minimum error probability are derived. Finally, simulation results are given to corroborate theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, a precoded and iteratively detected downlink muItiuser system is proposed, which is capable of operating in rank- deficient scenarios, when the number of transmitters exceeds the number of receivers. The literature of uplink space division multiple access (SDMA) systems is rich, but at the time of writing there is a paucity of information on the employment of SDMA techniques in the downlink. Hence, we propose a novel precoded downlink SDMA (DL-SDMA) muItiuser communication system, which invokes a low-complexity near-maximum-likelihood sphere decoder and is particularly suitable for the aforementioned rank-deficient scenario. Powerful iterative decoding is carried out by exchanging extrinsic information between the precoder's decoder and the outer channel decoder. Furthermore, we demonstrate with the aid of extrinsic information transfer charts that our proposed precoded DL-SDMA system has a better convergence behavior than its nonprecoded DL-SDMA counterpart. Quantitatively, the proposed system having a normalized system load of L8 = 1.333, i.e., 1.333 times higher effective throughput facilitated by having 1.333 times more DL-SDMA transmitters than receivers, exhibits a "turbo cliff" at an Eb/No of 5 dB and hence results in an infinitesimally low bit error rate (BER). By cciitrast, at Eb/No = 5 dB, the equivalent system dispensing with precoding exhibits a BER in excess of 10%. [ABSTRACT FROM AUTHOR]

Several digital cellular systems employ coherent Rake reception, wherein channel estimates are used to combine despread values. In this paper, a maximum likelihood (ML) approach to Rake combining that accounts for channel estimation error, including error correlation across despread values, is examined. Fading and noise correlation are also considered. The performance of the ML approach is compared to traditional Rake combining as well as approximate ML-based approaches. Results show that when the channel estimation error and noise are of the same order, ML-based approaches can provide gains on the order of 1 dB over traditional Rake reception. [ABSTRACT FROM AUTHOR]