Ambient OFDM Pilot-Aided Backscatter Communications: Concept and Design

This paper addresses the design of optimal and near-optimal detectors for a practical interference channel scenario where the transmitters employ discrete modulation schemes. The conventional detectors, which either ignore the interference or successively detect then cancel the interference, typically assume that the desired signal and/or the interference are Gaussian. This paper proposes detectors that explicitly take into account the modulation formats of both the desired signal and the interference. The optimal maximum-likelihood (ML) detector that minimizes the probability of detection error for a given set of modulation schemes is derived first. A joint minimum-distance detector (MD) is then presented as a low-complexity approximation of the optimal ML detector. It is demonstrated by analysis and by simulation that the proposed detectors can significantly outperform their conventional counterparts. In particular, while the interference-ignorant and the successive interference cancellation detectors are both prone to error floors, the proposed optimal ML and joint MD detectors are not.

In full-duplex orthogonal frequency-division multiplexing systems with IQ imbalances, a frequency-domain least-squares (FD-LS) channel estimator is proposed to estimate both source-to-destination (intended) and destination-to-destination (self-interference) channels. Subsequently, an optimal closed-form pilot matrix is derived to minimize the sum of mean square errors (sum-MSE) of the proposed FD-LS channel estimator. Then, an improved FD-LS estimator is presented and proved to further improve the performance of the FD-LS by exploiting the time-domain property of the channel. In the presence of channel estimation error, an optimal low-complexity maximum likelihood (ML) detector is developed by using eigenvalue and singular value decompositions and whitening the residual self-interference plus noise. Simulation results show that given the proposed FD-LS estimator, the optimal pilot matrix performs much better than those nonsingular pilot matrices with larger conditional numbers (CN). To be specific, the former achieves about 10-dB signal-to-noise ratio (SNR) gain over the latter with CN = 10, the improved FD-LS channel estimator provides about 6-dB SNR gain over the FD-LS estimator at a fixed bit error rate (BER), and the proposed whitening-filter ML detector performs at least 0.6 dB better than the conventional ML detector at a given BER of $10^{-3}$ in the medium-and high-SNR regions.

In this paper, we design an implementation of a kind of reduced-complexity maximum likelihood (ML) detector for spatial modulation (SM) deployed in a multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. Based on National Instruments Universal Software Radio Peripheral (NI USRP) platform, two USRP Reconfigurable Input / Output (USRP-RIO) devices are used as the transmitter and the receiver. Error performance comparisons between the reduced-complexity ML detector and conventional ML detector are made in an indoor environment, as well as the comparison between SM scheme and space-frequency block code (SFBC) scheme. 6 different pictures are exploited as transmitted data, and are reconstructed in the receiver side, so the performance of each scheme is taken on the reconstructed pictures. Both of the calculated bit error ratio (BER) and the reconstruction result of each transmitted pictures, validate the highly consistent error performance of HL_ML detector and conventional ML detector, as well as the error performance superiority of SM over SFBC.

A novel adaptive beamforming (BF) receiver is proposed for a multiple-input–multiple-output communication system over multipath fading channels. By dividing a large number of receive antennas into many adaptive beamformers (ABFs), the proposed system reduces the array dimension in order to simplify the signal detection process and enjoys the benefit of BF techniques to improve the symbol-error-rate (SER) performance. The effectiveness of the proposed system depends on the number of ABFs and the number of antennas per ABF. The statistical properties of complex Wishart matrices are applied to analyse the SER performance of the proposed system with both maximum-likelihood (ML) detection and zero-forcing detection. Furthermore, the authors have derived an upper bound for SER of the ML detection based on the smallest eigenvalue distribution. Through the authors analysis, it has been shown that the proposed system using ML detection provides comparable SER performance, but with a lower complexity as compared with that of a conventional ML receiver because of reduced array dimensions.

This paper addresses the design of optimal and near-optimal detectors in an interference channel with fading and with additive white Gaussian noise (AWGN), where the transmitters employ discrete modulation schemes as in practical communication scenarios. The conventional detectors typically either ignore the interference or successively detect and then cancel the interference, assuming that the desired signal and/or the interference are Gaussian. This paper quantifies the significant performance gain that can be obtained if the detectors explicitly take into account the modulation formats of the desired and the interference signals. This paper first describes the optimal maximum-likelihood (ML) detector that minimizes the probability of detection error for a given modulation scheme, and the joint minimum-distance (MD) detector, which is a lower-complexity approximation of the ML detector. It is then demonstrated by analysis and by simulation that in an AWGN channel, while interference-ignorant and successive interference cancellation detectors are both prone to error floors, the optimal ML and joint MD detectors are not. This paper further analyzes the performance of joint detection in a Rayleigh fading environment. It is demonstrated that the joint detector can achieve symbol error rates that have the same dependence on the received signal-to-noise ratio (SNR) as if the channel were interference free. Thus, the performance of joint detection is fundamentally limited by the SNR rather than the signal-to-interference ratio (SIR). Moreover, the joint detector enables the use of transmit diversity schemes to achieve the same diversity order as in the absence of interference. These results show that the use of interference-aware detectors can significantly alleviate the effect of interference thereby improving the achievable rates and the reliability of future wireless systems.

Cooperative PSK constellation design and power allocation for massive MIMO uplink communications

A low complexity maximum likelihood (ML) detection method is proposed for the square quadrature amplitude modulation (QAM) constellation. In order to reduce the implementation complexity of ML detection, set-partition, subset-selection, and subset-shift are recursively applied to the square QAM constellation. The estimated square QAM symbol is finally given in a closed form as a function of the received signal and the estimated channel. Complexity analysis and numerical simulation confirm that the proposed detection method reduces the implementation complexity substantially and achieves exactly the same performance as the conventional ML detection irrespective of the channel estimation error.

We propose an efficient transmission scheme for the generalized space shift keying (GSSK) based on the residue number system (RNS). The proposed scheme increases the number of active transmit antenna combinations (TACs), resulting in a higher throughput than that of the conventional GSSK systems. The received signals can be detected by a joint maximum likelihood (ML) detection, whose complexity, however, grows exponentially with the number of active TACs. To solve this problem, we propose a new detection method based on the RNS, whose complexity is much lower than that of the joint ML detection with negligible performance loss.

In this paper, a nonlinear base-band modulation scheme, namely POLar COordinate based Modulation (POLCOM), is proposed for intensity modulation with direct detection (IM/DD) based optical wireless communication (OWC) systems. Two detectors including the optimal maximum likelihood detector (MLD) operated in polar coordinate and the joint detector (JD) operated in rectangular coordinate are investigated. Over additive white Gaussian noise (AWGN) channels, the symbol error rate (SER) performances of POLCOM using these two detectors are derived in high signal-to-noise ratio (SNR) regime. To achieve good performance in terms of SER, a heuristic greedy walk algorithm (GWA) is proposed to design the signal constellations for POLCOM. Comprehensive comparisons are made with existing schemes under the same signal bandwidth and spectral efficiency. Through fair comparisons, it is shown that the proposed POLCOM outperforms most of existing schemes.

This paper investigates the joint maximum likelihood (ML) data detection and channel estimation problem for Alamouti space-time block-coded (STBC) orthogonal frequency-division multiplexing (OFDM) wireless systems. The joint ML estimation and data detection is generally considered a hard combinatorial optimization problem. We propose an efficient low-complexity algorithm based on branch-estimate-bound strategy that renders exact joint ML solution. However, the computational complexity of blind algorithm becomes critical at low signal-to-noise ratio (SNR) as the number of OFDM carriers and constellation size are increased especially in multiple-antenna systems. To overcome this problem, a semi-blind algorithm based on a new framework for reducing the complexity is proposed by relying on subcarrier reordering and decoding the carriers with different levels of confidence using a suitable reliability criterion. In addition, it is shown that by utilizing the inherent structure of Alamouti coding, the estimation performance improvement or the complexity reduction can be achieved. The proposed algorithms can reliably track the wireless Rayleigh fading channel without requiring any channel statistics. Simulation results presented against the perfect coherent detection demonstrate the effectiveness of blind and semi-blind algorithms over frequency-selective channels with different fading characteristics.

Spatial modulation (SM) is a transmission scheme that uses multiple transmit antennas but only one transmit RF chain. At each time instant, only one among the transmit antennas will be active and the others remain silent. The index of the active transmit antenna will also convey information bits in addition to the information bits conveyed through modulation symbols. Pseudo-random phase precoding (PRPP) is a technique that can achieve high diversity orders even in single antenna systems without the need for channel state information at the transmitter and transmit power control. In this paper, we exploit the advantages of both SM and PRPP simultaneously. We propose a pseudo-random phase precoded SM (PRPP-SM) scheme, where both the modulation bits and the antenna index bits are precoded by pseudo-random phases. The proposed PRPP-SM system gives significant performance gains over SM system without PRPP and PRPP system without SM. Since maximum likelihood (ML) detection becomes exponentially complex in large dimensions, we propose a low complexity local search based detection (LSD) algorithm suited for PRPP-SM systems with large precoder sizes. Our simulation results show that with 4 transmit antennas, 1 receive antenna, 5 × 20 pseudo-random phase precoder matrix and BPSK modulation, the performance of PRPP-SM using ML detection is better than SM without PRPP with ML detection by about 9 dB at 102 BER. This performance advantage gets even better for large precoding sizes. We also propose a precoder index modulation (PIM) scheme, which conveys additional information bits through the choice of a precoding matrix among a set of pre-determined PRPP matrices. Finally, combining the PIM and PRPP-SM schemes, we propose a PIM-SM scheme which conveys bits through both antenna index as well as precoder index.

The blind maximum-likelihood (ML) detection of orthogonal space-time block codes (OSTBCs) is a computationally challenging optimization problem. Fortunately, for BPSK and QPSK OSTBCs, it has been shown that the blind ML detection problem can be efficiently and accurately approximated by a semideflnite relaxation (SDR) approach [1]. This paper considers the situation where the 16-QAM signals are employed. Due to the nonconstant modulus nature of 16-QAM signals, the associated blind ML OSTBC detection problem has its objective function exhibiting a Rayleigh quotient structure, which makes the SDR approach not directly applicable. In the paper, a linear fractional SDR (LF-SDR) approach is proposed for efficient approximation of the optimum blind ML solution. In this approach, the blind ML 16-QAM OSTBC detection problem is first approximated by a quasi-convex relaxation problem. Generally quasi-convex problems may be computationally more complex to handle than convex problems, but we show that the optimum solution of our quasi-convex problem can be efficiently obtained by solving a convex problem, namely a semideflnite program. Simulation results demonstrate that the proposed LF-SDR based blind ML detector outperforms the norm relaxed blind ML detector and the blind subspace channel estimator [2], especially in the one- receive-antenna scenario.

In the wireless communication systems, the classic Multi-User Detection (MUD) techniques such as the Minimum Mean Square Error (MMSE) detector have some limitations and imperfections due to Multi-Access Interference (MAI) especially in overloaded scenarios when the number of users is more than the number of receiving antennas. The optimal Maximum Likelihood (ML) detector gives an excellent result to estimate the transmitted data but suffers from a computational complexity that grows exponentially with the number of users. In this paper, we propose a new metaheuristic approach for multiuser detection based on Honey Bees Mating Optimisation (HBMO) hybridised with Tabu Search (TS) for an uplink Space Division Multiple Access-Orthogonal Frequency Division Multiplexing (SDMA-OFDM) system in a flat Rayleigh fading channel. Indeed, the HBMO algorithm provides a good estimation for TS while exploring the largest regions, while the TS algorithm uses this estimation to find the best solution of the problem. The simulation results show that the proposed algorithm HBMO-TS-MUD provides the best trade-off between performance and computational complexity comparing to the conventional detector and the other MUD detectors proposed as Genetic Algorithm hybridised with the Tabu Search (GA-TS).

Efficient jamming attack against MIMO transceiver

Maximum likelihood (ML) detection algorithm is the best method for multi-user detection, but it has high computational complexity. This paper presents a view of this issue to its rapid and effective method, that is, complex spherical decoding algorithm. This algorithm not only maintains good performance of the ML detection, but also has a low computational complexity. On the other hand, the multi-carrier modulation with wavelet packet doesn't give rise to high side lode caused by OFDM technique, so that it avoids the loss of orthogonality duing to multi-path effect which leads to severe inter-channel interference. This modulation scheme also avoids the loss of SNR on account of cyclic prefix's application. We combine these two techniques to propose the complex spherical decoding algorithm in MC-CDMA modulated by wavelet packet (WPT-CDMA) system, the performance of multi-user detection has great improved from the results of simulation.