This paper deals with a state-space approach for adaptive second-order IIR notch digital filters with constrained poles and zeros. A simplified iterative algorithm is derived from the gradient-descent method to minimize the mean-squared output of an adaptive notch digital filter. Then, stability and parameter-estimation bias are analyzed for the simplified iterative algorithm. A numerical example is presented to demonstrate the validity and effectiveness of the proposed adaptive state-space notch digital filter and parameter-estimation bias analysis.

This paper investigates an adaptive notch digital filter that employs normal state-space realization of a single-frequency second-order IIR notch digital filter. An adaptive algorithm is developed to minimize the mean-squared output error of the filter iteratively. This algorithm is based on a simplified form of the gradient-decent method. Stability and frequency estimation bias are analyzed for the adaptive iterative algorithm. Finally, a numerical example is presented to demonstrate the validity and effectiveness of the proposed adaptive notch digital filter and the frequency-estimation bias analyzed for the adaptive iterative algorithm.

Using linear programming (LP) decoding based on alternating direction method of multipliers (ADMM) for low-density parity-check (LDPC) codes shows lower complexity than the original LP decoding. However, the development of the ADMM-LP decoding algorithm could still be limited by the computational complexity of Euclidean projections onto parity check polytope. In this paper, we proposed a bisection method iterative algorithm (BMIA) for projection onto parity check polytope avoiding sorting operation and the complexity is linear. In addition, the convergence of the proposed algorithm is more than three times as fast as the existing algorithm, which can even be 10 times in the case of high input dimension.

In this paper, we introduce a promising iterative interference alignment (IA) strategy for multiple-input multiple-output (MIMO) multi-cell downlink networks, which utilizes the channel reciprocity between uplink/downlink channels. We intelligently combine iterative beamforming and downlink IA issues to design an iterative multiuser MIMO IA algorithm. The proposed scheme uses two cascaded beamforming matrices to construct a precoder at each base station (BS), which not only efficiently reduce the effect of inter-cell interference from other-cell BSs, referred to as leakage of interference, but also perfectly eliminate intra-cell interference among spatial streams in the same cell. The transmit and receive beamforming matrices are iteratively updated until convergence. Numerical results indicate that our IA scheme exhibits higher sum-rates than those of the conventional iterative IA schemes. Note that our iterative IA scheme operates with local channel state information, no time/frequency expansion, and even relatively a small number of mobile stations (MSs), unlike opportunistic IA which requires a great number of MSs.

This paper studies an underlay-based cognitive two-way relay network which consists of a primary network (PN) and a secondary network (SN). Two secondary users (SUs) exchange information with the aid of multiple single-antenna amplify-and-forward relays while a primary transmitter communicates with a primary receiver in the same spectrum. Unlike the existing contributions, the transmit powers of the SUs and the distributed beamforming weights of the relays are jointly optimized to minimize the sum interference power from the SN to the PN under the quality-of-service (QoS) constraints of the SUs determined by their output signal-to-interference-plus-noise ratio (SINR) and the transmit power constraints of the SUs and relays. This approach leads to a non-convex optimization problem which is computationally intractable in general. We first investigate two necessary conditions that optimal solutions should satisfy. Then, the non-convex minimization problem is solved analytically based on the obtained conditions for single-relay scenarios. For multi-relay scenarios, an iterative numerical algorithm is proposed to find suboptimal solutions with low computational complexity. It is shown that starting with an arbitrarily initial feasible point, the limit point of the solution sequence derived from the iterative algorithm satisfies the two necessary conditions. To apply this algorithm, two approaches are developed to find an initial feasible point. Finally, simulation results show that on average, the proposed low-complexity solution considerably outperforms the scheme without source power control and performs close to the optimal solution obtained by a grid search technique which has prohibitively high computational complexity.

We propose a novel network traffic matrix decomposition method named Stable Principal Component Pursuit with Frequency-Domain Regularization (SPCP-FDR), which improves the Stable Principal Component Pursuit (SPCP) method by using a frequency-domain noise regularization function. An experiment demonstrates the feasibility of this new decomposition method.

In this paper, we propose a new interference alignment (IA) scheme that jointly designs the linear transmitter and receiver for the 2-user MIMO X channel system, using minimum total mean square error criterion, subject to each transmitter power constraint. We show that transmitters and receivers under such criteria could be realized through a joint iterative algorithm. Considering the imperfection of channel state information (CSI), we also extend the minimum mean square error interference alignment schemes for the MIMO X channel with CSI estimation error. A robust iterative algorithm which is insensitve to CSI estimation error is proposed. Simulation results are also provided to demonstrate the proposed algorithm.

A training-based vector channel estimation method has been proposed for single-user code-division multiple access (CDMA) systems in fast-varying correlated multipath fading channels. In this paper, we extend it in an iterative way to multiuser multiple-input multiple-output (MIMO) CDMA systems where both the transmitter and receiver have multiple antennas. In the training period, we propose to add the minimum mean square error (MMSE) front end before channel estimation to suppress multiuser interference (MUI) from substreams with difference spreading codes, so then we can get good initial vector channel estimation for each user. In the data transmission period, we proposed to add MMSE/parallel interference cancellation (PIC) front end to suppress MUI, interference suppression, and vector channel estimation in an iterative way. The perfect channel estimation is assumed in Liu et al., and the inter-play between channel estimation and multiuser detection is not discussed either. On the contrary, the novelty of the proposed method is that we add MMSE/PIC front end (in addition to matched filter) before channel estimation and we repeatedly switch between MMSE/PIC front end and channel estimation.

The size-dependent array problem is a problem with systolic arrays such that the size of systolic arrays limits the size of calculations, which in a do-loop structure controls how many times it is repeated and how deep the nesting loops are. A systolic array cannot deal with larger calculations. For the size-dependent array problem, a spiral systolic array has been studied so far. It has non-adjacent connections between PEs, such as loop paths for sending data back so that data flows over the array independently of its own size. This paper takes an approach to the problem without non-adjacent connections. This paper discusses systolic messy arrays for infinite iterative algorithms so that they are independent from the size of calculations. First a systolic messy array called two-square shape is introduced then the properties of two-square shape are summarized: memory function, cyclic addition, and cyclic multiplication. Finally a way of building systolic messy arrays that calculate infinite iterative algorithms is illustrated with concrete examples such as an arithmetic progression, a geometric progression, N factorial, and Fibonacci numbers.

In orthogonal frequency-division multiplex access (OFDMA) uplink, the carrier-frequency offsets (CFOs) between the multiple transmitters and the receiver introduce inter-carrier interference (ICI) and severely degrade the performance. In this paper, based on the perfect estimation of each user's CFO, we propose two low-complexity iterative algorithms to cancel ICI due to CFOs, which are denoted as the basic algorithm and the improved algorithm with decision-feedback equalization (DFE), respectively. For the basic one, two theorems are proposed that yield a sufficient condition for the convergence of iterations. Moreover, the interference-power-evolution (IPE) charts are proposed to evaluate the convergence behavior of this interference cancellation algorithm. Motivated by the IPE chart, the procedure of DFE is introduced into the iterations, which is the basic idea of the improved algorithm. For this improved algorithm, the error-propagation effect are analyzed and suppressed by an efficient stopping criterion. From IPE charts and simulation results, it can be easily observed that the basic algorithm has the same capability of ICI cancellation as the linear optimal minimum mean square error (MMSE) method, but offers lower complexity, while the improved algorithm with DFE outperforms the MMSE method in terms of the bit-error rate (BER) performance.

One of the system greatly affecting the performance of a database server is the size-division of buffer pools. This letter proposes an adaptive control method of the buffer pool sizes. This method obtains the nearly optimal division using only observed response times in a comparatively short duration.

This paper presents a linear constrained minimum variance multiuser detection (MUD) scheme for DS-CDMA systems, which makes full use of the available spreading sequences of the users as well as the relevant channel information of the incoming rays in the construction of the constraint matrix. To further enhance the performance, a statistical optimum filter bank in combination with the developed minimum variance MUD with the partitioned linear interference canceller (PLIC) as the underlying structure is also addressed. The determination of the filter bank coefficients, however, calls for computationally demanding nonlinear programming. To alleviate the computational overhead, an iterative procedure is also proposed, which solves the Rayleigh quotient in each iteration. Furthermore, the expressions of the output signal to interference plus noise ratio (SINR) are also determined to provide further insights into the proposed approach. Conducted simulations validate the new scheme.

This paper is concerned with synthesizing VLSI array processors from iterative algorithms. Our primary objective is to obtain the highest processor efficiency but not the shortest completion time. Unlike most of the previous work that assumes the index space of the given iterative algorithm to be boundless, the proposed method takes into account the effects of the boundaries of the index space. Due to this consideration, the pseudo-dependence relations are excluded, and most of the independent computations can therefore be uniformly grouped. With the method described in this paper, the index space is partitioned into equal-size blocks and the corresponding computations are systematically and uniformly mapped into processing elements. The synthesized VLSI array processors possess the attractive feature of very high processor efficiency, which, in general, is superior to what is derived from the conventional linear transformation methods.

We present a novel algorithm to reconstruct the refractive-index profile of a circularly symmetric object from measurements of the electromagnetic field scattered when the object is illuminated by a plane wave. The reconstruction algorithm is besed on an iterative procedure of matching the scattered field calculated from a certain refractive-index distribution with the measured scattered field on the boundary of the object. In order to estimate the convergence of the reconstruction, the mean square error between the calculated and measured scattered fields is introduced. It is shown through reconstructing several examples of lossy dielectric cylinders that the algorithm is quite stable and is applicable to high-contrasty models in situations where the Born approximation is not valid.