Blind adaptive noncoherent multiuser detection for nonlinear modulation

In this paper, we introduce a novel fuzzy adaptive algorithm for blind detection of direct sequence code division multiple access (DS-CDMA) signals in a multiuser communication scenario. We make use of fuzzy control systems to wisely determine the appropriate step size of the adaptive algorithm based on the quality of the received signal. We have used the popular minimum output energy (MOE) blind detector proposed by Honig et al. as our blind adaptive detector whose step size is to be determined by the fuzzy control system. This blind detector requires no more knowledge than does the conventional single-user receiver, i.e. the desired user's signature waveform and its timing. We have proposed to use signal to interference ratio (SIR) and its variations as the key inputs to our fuzzy algorithm. By simulation, we show the competency of our algorithm in terms of the convergence characteristics of the adaptive algorithm. Likewise, by simulation results we show that these convergence improvements yield to a lower bit error rate (BER) for the demodulation process in the receiver.

The decorrelating detector is known to eliminate multiaccess interference given that the signature sequences of the users are linearly independent, at the cost of enhancing the Gaussian receiver noise. In this paper, we present and study the convergence of a blind adaptive decorrelating detector which is based on the observation of the available statistics. The algorithm is iterative and distributed. Only two parameters are needed for the construction of the receiver filter of a user: the user's signature sequence and the variance of the white Gaussian receiver noise. The computational complexity of the proposed algorithm per iteration is linear in the number of users.

We first develop a reduced-rank minimum mean square error (MMSE) detector for direct-sequence (DS) code division multiple access (CDMA) by forcing the linear MMSE detector to lie in a signal subspace of a reduced dimension. While a reduced-rank MMSE detector has lower complexity, it cannot outperform the full-rank MMSE detector. We then concentrate on the blind reduced-rank MMSE detector which is obtained from an estimated covariance matrix. Our analysis and simulation results show that when the desired user's signal is in a low-dimensional subspace, there exists an optimal subspace so that the blind reduced-rank MMSE detector lying in this subspace has the best performance. By properly choosing a subspace, we guarantee that the optimal blind reduced-rank MMSE detector is obtained. An adaptive blind reduced-rank MMSE detector, based on a subspace tracking algorithm, is developed. The adaptive blind reduced-rank MMSE detector exhibits superior steady-state performance and fast convergence speed.

This paper proposes c1 sequential detection multi-user receiver which is constructed over a CDMA system such that a transmitter transmits a symbol made bv spreading the spectmm with an enveloped sequence prorected by guard sequences, and a receiver de-modulates the core-sequence part of the received symbol with a de-correlating detector or an MMSE detector and has an advantage of increasing the number of the active users. This sequential detection uses such a method that the best user signal is estimated out of the soft outputs, which are obtained by solving a de-correlating system of equations, and then detected, followed by removing the detected user component from the received symbol. All the user signals may be sequentially detected by repeating the method stated above. The computer simulution reveals a remarkable improvement in bit error rate performance compared to conventional systems.

Blind detection of a desired user's signal in a code-hopping (CH) direct sequence code-division multiple access (CDMA) system is considered. In CH CDMA systems each user switches between a predetermined set of short-code sequences. A user signal in such systems may be treated as the superposition of several virtual short-code signals. A code-constrained inverse filter criterion (IFC)-based blind detector for short-code CDMA signals in asynchronous multipath channels to detect a desired user's signal was recently presented by Tugnait and Li (2001). A novel approach combining the code-constrained IFC and a penalty function is proposed to simultaneously extract all virtual users associated with a given CH user. Global minima of the proposed cost function are analyzed. An extension of an existing subspace-based approach is also investigated. An illustrative simulation example is provided where the proposed algorithm is compared with a clairvoyant matched filter receiver, two linear minimum mean-square error (MMSE) receivers with channels known, and the subspace-based approach.

In this work, we study the non-time-slotted massive-device multiple access (MaDMA) problem where massive user devices transmit sporadic data to a multi-antenna base station (BS). We develop a structured sparsity learning based multiuser detection (SSL-MUD) scheme. By exploiting the structured sparsity naturally embedded in user signals, our SSL-MUD scheme is able to blindly detect the user packets without any prior knowledge of the user activity state (UAS) and the channel state information (CSI), and hence significantly reduces the transmission overhead. For the blind signal detection at the BS, we put forth the turbo bilinear generalized approximate message passing (Turbo-BiG-AMP) algorithm. Simulation results demonstrate that the Turbo-BiG- AMP algorithm significantly outperforms the existing compressed sensing based approach and achieves a performance comparable to that of the oracle linear minimum mean-square error (Oracle- LMMSE) algorithm (which assumes perfect knowledge of UAS and CSI at the BS).

The paper proposes a new method to blindly detect QPSK signals of MIMO systems by using continuous Hopfield neural network (HNN). The new method successfully constructs a weighted matrix of HNN, which reduces the number of equilibrium points of HNN significantly, so that the speed to blindly detect signals is increased as well as the bit error rate (BER) is lowered. The new method detects multi-user signals with serial processing, in which the method utilizes those user signal vectors having been detected to extend the complementary subspace consisting of received data vectors in order to recover other user signals to be detected. The performance of the proposed HNN-based method is evaluated via computer simulations and compared with the existing approaches. Results are shown that the new method has better performances than others.

Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.

We propose a blind multiuser detector based on a new data precoding technique for direct-sequence code-division multiple-access signals. The modulus of all users' data is block encoded, using a sequence that is unique for each user. This precoding method, together with the analytical constant modulus algorithm for detection, enables a closed-form, one-shot detection of the desired user's signal in a multipath channel using one or more antennas. The detection process does not involve or require a channel estimation step. The proposed detector is shown to be extremely near-far resistant, and can operate properly in the presence of severe carrier frequency offset.

Constrained minimum variance (CMV) detection has been proposed for blind multiuser detection of DS/CDMA signals in multipath channels. We suggest a new approach for implementing the CMV detection when an antenna array is used at the receiver. A simple technique is used for restricting the domain of the CMV detector to a smaller subspace based on signals directions of arrivals (DOAs), in a beamformer-like formulation. The proposed technique requires prior knowledge of only the timing of the desired user's signal. It is seen that the proposed subspace restriction is useful for accurate path DOA estimation followed by efficient data detection in heavily loaded systems and over small block sizes of the input signal. This makes this method suitable for slowly time varying channels.

A new stable blind multiuser detector based on signal subspace orthogonal projection is presented. By carrying out a pseudo-eigendecomposition (PED) analysis, a technique proposed for the first time, the signal of the interested user can be approximated by the orthogonal projection of a received multiuser signal onto the related subspace of the interested user. Simulations show that compared with the previous subspace-based MMSE blind multiuser detector, the new detector offers better performance without leading to an increase in the computational complexity.

Optimization in Simulation is an important problem often encountered in system behavior investigation; however, the existing methods such as response surface methodology and stochastic approximation method are inefficient. This paper presents a modification of a quasi‐Newton method, in which the parameters are determined from some numerical experiments. To demonstrate the validity of the devised method, two examples resembling the M/M/1 queueing problem are solved. The closeness of the converged solutions to the optimal solutions and a comparison with two stochastic approximation methods indicate that the modified quasi‐Newton method as devised in this paper is a robust and efficient method for solving optimization problems in simulation.

This paper presents new transceiver framework for the DS-CDMA systems that use the multiple-input multiple-output (MIMO) antennas, with space-time block code (ST-BC). In the transmitter, new hybrid (prefix/postfix) zero-padding sequences combining with the desired user signature is exploited to form the hybrid augmented user signature sequences, with respect to different transmit-antennas. While in the receiver under the GSC framework a new Capon-like semi-blind MIMO-CDMA filterbank detector based on the linearly constrained constant modulus (LCCM) criterion, is derived. Also, the adaptive GSC-RLS algorithm is developed for adaptively implementing the blind LCCM MIMO-CDMA filterbank of the receiver. With the specific design of the hybrid augmented user signature sequences, we are able to resolve phase ambiguity problem of blind channel estimation. Computer simulations verify the merits of the proposed new transceiver framework; it can be employed to achieve better performance, and is more robust against the discrepancy due to Capon channel estimation.

DS/CDMA cellular systems are plagued with the near-far problem which can result in considerable reduction in capacity. Adaptive antenna arrays are used to increase link capacity, improve coverage and permit less stringent power control. Adaptive beamforming algorithms are crucial to the success of the smart antennas. The existing beamforming methods are found to be far from satisfactory for DS/CDMA in the urban multipath environment where user signals are very dissimilar in strength and perfect power control is hardly possible. This paper proposes a new decision-directed beamforming algorithm for CDMA with noncoherent M-ary orthogonal modulation which performs very well in typical CDMA environments. We introduce a quality measure of a symbol decision and a criterion for picking good weights and rejecting bad weights during the process of adaptation. With incorporating the measure into the least-squares algorithm, we can select weights in a positive manner such that the beamformer is forced to keep track of its optimum weights. The advantages of the proposed algorithm include: (1) an amount of immunity to the near-far effect; (2) the ability of tracking the optimum weight vector in the context of time-variant channels; (3) insensitivity to decision errors; (4) good convergence property; (5) the ability of working in low SNR scenarios; (6) tolerance to timing errors between the antennas; (7) mild synchronization requirement, and (8) computational simplicity. The simulation results are given in this paper to demonstrate the effectiveness of the proposed algorithm.

This paper introduces the problem of noncoherent detection for nonorthogonal multipulse modulation in the context of the synchronous multiuser Gaussian channel. Each user sends an M-ary information symbol by transmitting one of M possibly nonorthogonal waveforms. Furthermore, the M signals of one user are allowed to be correlated with the signals of all other users. A key idea proposed here is that of a noncoherent decorrelative receiver front end. Like its counterpart in single-pulse modulation, this front end eliminates multiuser interference. It therefore reduces the multiuser detection problem into decoupled single-user problems over equivalent noise-enhanced single-user channels. Each equivalent single-user channel is rather general and can be described as one where the waveforms employed are not only correlated, but are also of unequal energies. Several new results pertaining to the design and analysis of optimum and suboptimum noncoherent detectors for this single-user channel are obtained. In the multiuser channel, these detectors constitute the post-decorrelative processing units for each user.