High-throughput Quadrature Amplitude Modulation Research Articles

Space-Time Blind Equalization of Dispersive MIMO Systems Driven by QAM Signals

This paper investigates space-time blind equalization (BE) of dispersive multiple-input multiple-output communication systems driven by high throughput quadrature amplitude modulation signals. Multistage processing is adopted to overcome the severe local convergence problem in BE. First, a good initial value for the equalizer is obtained by forcing one of the system inputs with desired delay to be recovered. Then, the fast multimodulus algorithm (MMA) is used to roughly equalize the communication system. After that, an improved MMA (IMMA) is developed to effectively search for a fine equalizer for the system. Moreover, the novel modified Newton method (MNM) proposed in our previous work is employed to fast optimize the MMA and IMMA cost functions, which significantly reduces the computational load. Furthermore, the proposed algorithm has an additional benefit that once a signal is recovered, its corresponding single-input multiple-output channel impulse response is estimated by the classical least squares methods. Then, the influence of the recovered signal to the original received signals is removed to avoid extracting this recovered signal repeatedly. The quadratic rate of convergence of the MNM is theoretically analyzed, and the good equalization performance of the IMMA is explained. Finally, simulation results are provided to illustrate the effectiveness of the proposed algorithm.

Space-Time Semi-Blind Equalizer for Dispersive QAM MIMO System Based on Modified Newton Method

This paper proposes a space-time semi-blind equalizer (ST-SBE) for dispersive multiple-input multiple-output (MIMO) communication systems that employ high throughput quadrature amplitude modulation (QAM) signals. A novel cost function (CF) that integrates multimodulus algorithm (MMA) with soft decision-directed (SDD) scheme is established to efficiently obtain the weight vector associated with the ST-SBE. In the ST-SBE, a very short training sequence is used to provide a rough initial least squares estimate of the weight vector. An efficient modified Newton method (MNM) for minimizing the established cost function is proposed to fast search the optimal weight vector. Very interestingly, we prove that the proposed MNM has the same quadratic order of convergence as Newton methods. In addition, the proposed MNM has much lower computational complexity than Newton methods. Simulation results are provided to demonstrate that the ST-SBE has better performances than the gradient-Newton (GN)-based concurrent constant modulus algorithm (CMA) with SDD scheme (GN-CMA+SDD).

Fading performance evaluation of a semi-blind adaptive space–time equaliser for frequency selective MIMO systems

A semi-blind adaptive space–time equaliser (STE) has recently been proposed based on a concurrent gradient-Newton (GN) constant modulus algorithm (CMA) and soft decision-directed (SDD) scheme for dispersive multiple-input multiple-output (MIMO) systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal to the dimension of the STE, is used to provide a rough initial estimate of the STE's weight vector. The concurrent GN based CMA and SDD blind adaptive scheme is then adopted to adapt the STE. This semi-blind STE has a complexity similar to that of the training-based recursive least squares (RLS) algorithm. For stationary MIMO channels, it has been demonstrated that this semi-blind adaptive STE is capable of converging fast to the optimal minimum mean square error STE solution. In this contribution, we investigate the performance of this semi-blind adaptive STE operating in Rayleigh fading MIMO systems. Our results obtained show that the tracking performance of this semi-blind adaptive algorithm is close to that of the training-based RLS algorithm. Thus, this semi-blind adaptive STE offers an effective and practical means to successfully operate under the highly dispersive and fading MIMO environment.

Semi-blind adaptive beamforming for high-throughput quadrature amplitude modulation systems

A semi-blind adaptive beamforming scheme is proposed for wireless systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, equal to the number of receiver antenna array's elements, are first utilised to provide a rough initial least squares estimate of the beamformer's weight vector. A concurrent constant modulus algorithm and soft decision-directed scheme is then applied to adapt the beamformer. This semi-blind adaptive beamforming scheme is capable of converging fast to the minimum mean-square-error beamforming solution, as demonstrated in our simulation study.

Fast Converging Semi-Blind Space-Time Equalisation for Dispersive QAM MIMO Systems

A novel semi-blind space-time equaliser (STE) is proposed for dispersive multiple-input multiple-output systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal to the dimension of the STE, are first utilised to provide a rough initial least squares estimate of the STE's weight vector. A concurrent gradient-Newton constant modulus algorithm and soft decision-directed scheme is then applied to adapt the STE. The proposed semi-blind adaptive STE is capable of converging fast to the minimum mean square error STE solution. Simulation results confirms that the convergence speed of this semi-blind adaptive algorithm is very close to that of the training-based recursive least squares algorithm.

Semi-Blind Adaptive Spatial Equalization for MIMO Systems with High-Order QAM Signalling

This contribution investigates semi-blind adaptive spatial filtering or equalisation for multiple-input multiple-output (MIMO) systems that employ high-throughput quadrature amplitude modulation (QAM) signalling. A minimum number of training symbols, equal to the number of receivers (we assume that the number of transmitters is no more than that of receivers), are first utilized to provide a rough least squares channel estimate of the system is MIMO channel matrix for the initialization of the spatial equalizer is weight vectors. A constant modulus algorithm aided soft decision-directed blind algorithm, originally derived for blind equalization of single-input single-output and single-input multiple-output systems employing high-order QAM signalling, is then extended to adapt the spatial equalizers for MIMO systems. This semi-blind scheme has a low computational complexity, and our simulation results demonstrate that it converges fast to the minimum mean-square-error spatial equalization solution.

Iterative Multiuser Minimum Symbol Error Rate Beamforming Aided QAM Receiver

A novel iterative soft interference cancellation (SIC) aided beamforming receiver is developed for high-throughput quadrature amplitude modulation systems. The proposed SIC-based minimum symbol error rate (MSER) multiuser detection scheme guarantees the direct and explicit minimization of the symbol error rate at the output of the detector. Adopting the extrinsic information transfer (EXIT) chart technique, we compare the EXIT characteristics of an iterative MSER multiuser detector (MUD) with those of the conventional minimum mean-squared error (MMSE) detector. As expected, the proposed SIC-MSER MUD outperforms the SIC-MMSE MUD.

Constant modulus algorithm aided soft decision directed scheme for blind space–time equalisation of SIMO channels

This paper investigates a blind space–time equaliser (STE) designed for single-input multiple-output (SIMO) systems that employ high-throughput quadrature amplitude modulation schemes. A constant modulus algorithm (CMA) aided soft decision-directed (SDD) scheme, originally derived for low-complexity blind equalisation of single-input single-output channels, is extended to the SIMO scenario. Simulations are conducted to compare the performance of this blind adaptive scheme with another low-complexity blind STE referred to as the CMA aided decision directed (DD) scheme. The results obtained demonstrate that for SIMO systems the CMA aided SDD scheme exhibits advantages over the CMA aided DD arrangement, in terms of its faster convergence speed and lower computational complexity.