A Maximum Likelihood Combining Algorithm for Spatial Multiplexing MIMO Amplify-and-Forward Relaying Systems

In this paper, a common framework for maximum likelihood (ML) detection of spatial multiplexed (SM) and space time coded multiple-input multiple-output (MIMO) signals is proposed. It facilitates a common field programmable gate array (FPGA) based hardware design for the detection of both SM and space time block coded (STBC) MIMO signals with reduced computational complexity. We reduce the number of multipliers required for the ML detection by utilizing a set of precomputed combinations of the constellation symbols from lookup tables (LUT) without any degradation in the packet error rate (PER) performance. The reduction in the computational complexity is achieved by using the additional memory that is available in the FPGA. To evaluate the performance of the proposed method, we perform simulations for the WLAN system based on IEEE 802.11 standard using SM-MIMO and STBC-MIMO.

In this paper, we focus on downlink zero forcing (ZF) beamforming design scheme for multiuser (MU) spatial multiplexing (SM) multiple-input multiple-output (MIMO) systems. Based on the minimum average probability of symbol error (PSE), we give the optimal design method of the beamforming weight matrices. Furthermore, we derive the upper bound PSEs to evaluate the impact of channel feedback errors on the system performance. Comparison of the upper bounds of the average PSE for several schemes shows that the downlink ZF beamforming for multiuser spatial multiplexing MIMO schemes provide almost the same performance as the SU beamforming scheme.

In this paper, we address the ordering of transmit antennas according to reliability for unequal error protection (UEP) in spatially multiplexed (SM) multiple-input multiple-output (MIMO) systems with joint detection at the receiver. When zero-forcing (ZF) detection is adopted, the reliabilities of transmit antennas are explicitly expressed as postequalization signal-to-noise ratios (SNRs). Thus, multiantenna UEP can be implemented by assigning data of high priority to transmit antennas with a high postequalization SNR. Unfortunately, the overall error performance is generally unsatisfactory. Various joint signal detection techniques that achieve maximum likelihood (ML) or near-ML performance have been developed as alternatives to ZF, but it is not obvious how to discriminate the reliabilities of the transmit antennas or the jointly detected symbols. Recently, an ordering technique for antenna reliabilities was proposed that exploits the structure of the previous near-optimal QR-decomposition-based least-reliable-layer joint detection. In this paper, we divide the log-likelihood ratio of each symbol into collaborative and individual components, assuming joint ML detection. We derive a statistical connection between the magnitude order of each component of the multiple symbols (or the corresponding transmit antennas) and the post-ZF-equalization SNRs. Based on the statistical connections, we propose the use of post-ZF-equalization SNR as a criterion for antenna reliability ordering of SM MIMO with various near-optimal, as well as optimal, joint detections. The differentiated error performance of transmit antennas is also shown to be mainly attributed to the difference of individual components, and the tendency becomes stronger as the constellation size increases. Simulations demonstrate that the proposed ordering technique better meets the UEP requirement with lower computational complexity than the conventional ordering. Assuming $N_t \times N_t$ MIMO systems, the previous ordering and the proposed ordering require $\mathcal{O}(N_t^3)+\sum_{N=2}^{N_t-1}\mathcal{O}(NN_t^2+N^3)$ and $\mathcal{O}(N_t^3)$ , respectively.

In this letter, we propose a transmit antenna selection and unitary precoding strategy for maximum-likelihood (ML) detector in interference-aligned multiple input multiple output (MIMO) networks. The proposed transmit antenna selection for ML receiver is to maximize the minimum among all receivers' minimum distances. In order to achieve further performance enhancement, we also propose an unitary precoding strategy for ML detector associated with the antenna selection. Numerical results show that the proposed scheme provides enhanced performance compared with the conventional algorithms.

This work presents a theoretical framework for determining the optimal clipping level for a multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system. We start by modeling of the clipping noise, and propose a maximum likelihood (ML) receiver for the resulting signal. The bit error rate (BER) for this ML receiver is then derived for MIMO spatial multiplexing, space time coding, and cyclic delay diversity schemes. A search through the tradeoff space between the BER performance penalty and power amplifier (PA) power consumption advantage reveals optimum clipping levels of the system. Using an IEEE 802.11n like system, we show that the optimum clipping as predicted by this approach can improve PA power efficiency as much as 70%.

Fast DOA estimation algorithm for MIMO sonar based on ant colony optimization

Multiple-input multiple-output (MIMO) techniques have become an essential part of broadband wireless communications systems. For example, the recently developed IEEE 802.16e specifications for broadband mobile wireless access include three MIMO profiles employing 2times2 space-time codes (STCs) and two of those, namely, Alamouti's STC for transmit diversity, and the 2times2 spatial multiplexing (SM) scheme, are mandatory on the downlink of Mobile WiMAX systems. The first of these has full diversity but it is only half rate, while the second is full rate but suffers from diversity loss. In this paper, we develop a full-diversity STC of size 2times2, which represents an interesting trade-off between these two schemes. More specifically, the presented code is of rate 3/4, it has full diversity, and it leads to simple maximum-likelihood (ML) detection whose complexity grows only linearly with the size of the signal constellation. This makes it a suitable candidate for future evolutions of broadband wireless systems toward higher data rates and performance.

Radio frequency identification (RFID) is a technique that enables autonomous identification of objects using tiny and cheap transponders (tags). Therefore, its use increases, especially in the area of logistics. However, in dense applications scenarios with many tags multiple tags may transmit their data at the same time, leading to collisions. These collisions, especially in case of UHF RFID, significantly reduce the system throughput. The use of multiple input–multiple output (MIMO) is one candidate to achieve a high throughput even in case of tag collisions. Within this paper, we therefore analyze the performance of maximum-likelihood decoding for UHF RFID with multiple reception antennas. We especially take into account the impact of the FM0 channel encoding used by the EPCglobal Class-1 Gen-2 standard, the most common UHF RFID standard in the area of logistics. The channel characteristics of passive RFID systems follow the so-called double or backscatter Rayleigh distribution, which makes the performance analysis a challenging task. We use two methodologies to analyze the performance in this. First, we derive an upper bound symbol error probability (SEP) based on the pairwise error probability (PEP). The second technique depends on the exact evaluation of the SEP by taking into account all probabilities of errors between symbols. We finally compare the accuracy of both methodologies with simulation results. These results show that the PEP analysis converges with increasing number of antennas, and the exact analysis gives accurate results even with only two receive antennas.

In this thesis we investigate the effects of the physical constraints such as antenna aperture size, antenna geometry and non-isotropic scattering distribution parameters (angle of arrival/departure and angular spread) on the performance of coherent and non-coherent space-time coded wireless communication systems. First, we derive analytical expressions for the exact pairwise error probability (PEP) and PEP upper-bound of coherent and non-coherent space-time coded systems operating over spatially correlated fading channels using a moment-generating function-based approach. These analytical expressions account for antenna spacing, antenna geometries and scattering distribution models. Using these new PEP expressions, the degree of the effect of antenna spacing, antenna geometry and angular spread is quantified on the diversity advantage (robustness) given by a space-time code. It is shown that the number of antennas that can be employed in a fixed antenna aperture without diminishing the diversity advantage of a space-time code is determined by the size of the antenna aperture, antenna geometry and the richness of the scattering environment. In realistic channel environments the performance of space-time coded multipleinput multiple output (MIMO) systems is significantly reduced due to non-ideal antenna placement and non-isotropic scattering. In this thesis, by exploiting the spatial dimension of a MIMO channel we introduce the novel use of linear spatial precoding (or power-loading) based on fixed and known parameters of MIMO channels to ameliorate the effects of non-ideal antenna placement on the performance of coherent and non-coherent space-time codes. The spatial precoder virtually arranges the antennas into an optimal configuration so that the spatial correlation between all antenna elements is minimum. With this design, the precoder is fixed for fixed antenna placement and the transmitter does not require any feedback of channel state information (partial or full) from the receiver. We also derive precoding schemes to exploit non-isotropic scattering distribution parameters of the scattering channel to improve the performance of space-time codes applied on MIMO systems in non-isotropic scattering environments. However, these schemes

The combination of space-time block codes (STBC) and spatial multiplexing (SM) schemes has the advantages of diversity gain and high data rate. For such STBC/SM hybrid systems, we propose a new detector based on the block structure of STBC and the sphere decoder (SD). By employing the SD, optimal detection is performed with computational complexity much less than the brute-force maximum likelihood (ML) search. Simulation results show that the new decoder significantly outperforms the previously developed zero-forcing (ZF) group/STBC detector, the minimum mean square error (MMSE) group/STBC detector, and the MMSE and ML detectors for equivalent SM systems.

For multiple-input multiple-output (MIMO) spatial multiplexing systems the complexity of the maximum likelihood detector (MLD) can be prohibitively large when the number of transmitting antennas and constellation points is high. To simplify the MLD many linear and nonlinear techniques have been proposed. In this letter the principle of reduced state sequence detection, based on mapping by set partitioning, is applied to perform detection in spatial multiplexing MIMO systems based on non-binary constellations. Simulation results are presented to show the benefits of our proposal. An upper bound to the symbol error probability is also derived.

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.

Molecular communication (MC) is a promising communication paradigm for realizing nano-networks, where molecules are employed as an information carrier. In this letter, based on diffusive MC we propose a novel modulation scheme, called layered molecular shift keying (LMoSK), where several types of molecule form different layers to encode information bits, which can not only improve the data rate but also reduce the effect of inter-symbol interference (ISI). For detection of LMoSK, we formulate an ideal maximum likelihood (ML) receiver assuming knowledge of the ISI. Considering the limited capability of the receiver, we further propose a practical ML detection, enjoying both reduced computational complexity and memory of the receiver. The error performance of the LMoSK with practical ML receiver is analyzed and compared with that of molecular shift keying modulation and molecular type permutation shift keying modulation. Simulation results demonstrate that the proposed LMoSK outperforms benchmark schemes.

Non-orthogonal multiple access (NOMA) is an effective way to improve the spectrum efficiency of multiple-input multiple-output (MIMO) systems, where this advancement can be fully exploited by employing a proper user selection strategy in the multiuser MIMO system. However, for multiuser scenarios, information-theoretic throughput may not be properly used as the performance indicator since the constraints at the receiver (e.g., suboptimal detectors) are not taken into consideration. In this paper, we adopt the error probability (EP) as the performance metric, which is equivalent to the practical throughput efficiency and can take the critical constraints into consideration. We analyze the pair-wise error probability (PEP) performance of different detectors and propose two kinds of user selection methods to minimize the PEP. To facilitate the detection performance evaluation, we further investigate the multiuser diversity of the proposed selection methods and derive a tight lower PEP bound for the case with randomly selected users. From the analytical and numerical results, we demonstrate that the proposed multiuser selection methods can suppress the inter-user interference effectively and achieve better performance than that of the state-of-the-art method.

This paper proposes a new multiple input multiple output receiver based on the Kalman filtering algorithm. The Kalman filtering algorithm is based on the Gaussian assumption of the input signal. However, the assumption is not appropriate for the digital communication system which has non-Gaussian input signal. The proposed receiver overcomes the problem by using multiple Kalman filters and its output is obtained using the weighted sum of the outputs of the Kalman filters by the Gaussian sum approximation method to make the data signal approximately Gaussian. Simulation results show that the bit error rate (BER) performance of the proposed receiver is better than the previous Kalman-based receivers and its BER performance is close to the maximum likelihood (ML) receiver with lower computational complexity than the ML receiver.