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In this paper, we present a novel distributed affine projection algorithm (APA) to solve distributed estimation problem within dynamic diffusion networks. In addition, mean-square stability of the proposed algorithm is also studied through exploitation of the energy conservation approach due to Sayed. Simulations confirm that the novel algorithm achieves a greatly improved performance as compared...
A novel multimodal approach is proposed to solve the problem of blind source separation (BSS) of moving sources. The challenge of BSS for moving sources is that the mixing filters are time varying, thus the unmixing filters should also be time varying, which are difficult to track in real time. In the proposed approach, the visual modality is utilized to facilitate the separation for both stationary...
The problem of multiuser multiplexing with a MIMO sub system for each individual user is considered. We demonstrate that the capacity performance of the null space based spatial multiplexing schemes can be improved with iterative power allocation within the iterative design process. We considered water-filling based local and global power allocation and demonstrate that both schemes outperform the...
In this work we propose a power control algorithm for a multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) multi-hop collaborative relaying network. Using orthogonal and quasi-orthogonal block codes with three stage processing our algorithm optimally distributes available transmission power based on the architecture and the channel condition at each stage so as to minimize...
Using the convolutive nonnegative matrix factorization (NMF) model due to Smaragdis, we develop a novel algorithm for matrix decomposition based on the squared Euclidean distance criterion. The algorithm features new formally derived learning rules and an efficient update for the reconstructed nonnegative matrix. Performance comparisons in terms of computational load and audio onset detection accuracy...
In order to obtain a good balance of bit error rate (BER) across channels, the geometric mean decomposition (GMD) is introduced to replace the singular value decomposition (SVD) for precoding in the downlink of a multiuser multistream multiple-input multiple-output (MIMO) system. By combining GMD with a block diagonalization method, we obtain two kinds of precoding schemes: iterative nullspace-directed...
In this paper we propose the use of variable length adaptive filtering within the context of incremental learning for distributed networks. Algorithms for such incremental learning strategies must have low computational complexity and require minimal communication between nodes as compared to centralized networks. To match the dynamics of the data across the network we optimize the length of the adaptive...
In this work we consider OFDM transmission, due to its potential for meeting the stringent quality of service (QoS) targets of next-generation broadband distributed wireless networks, over three-stage relay networks. In particular, we examine distributed adaptive space-frequency coding for generally asynchronous links composed of four transmit and/or receive antennas, i.e. exploiting quasi-orthogonal...
A new variable tap-length adaptive algorithm which exploits both second and fourth order statistics is proposed in this paper. In this algorithm, the tap-length of the adaptive filter is varying rather than fixed, and controlled by fourth order statistics, whereas the coefficient update retains a conventional least mean square (LMS) form. As will be seen in the simulation results, the proposed algorithm...
In this paper, the steady-state performance of the distributed least mean-squares (dLMS) algorithm within an incremental network is evaluated without the restriction of Gaussian distributed inputs. Computer simulations are presented to verify the derived performance expressions.
A generalized blind lag-hopping adaptive channel shortening (GLHSAM) algorithm based upon squared auto-correlation minimization is proposed. This algorithm provides the ability to select a level of complexity at each iteration between the sum-squared auto-correlation minimization (SAM) algorithm due to Martin and Johnson and the single lag auto-correlation minimization (SLAM) algorithm proposed by...
A simple extended orthogonal space-frequency coded multiple input single output (MISO) orthogonal frequency division multiplexing (OFDM) transmitter diversity technique for wireless communications over frequency selective fading channels is presented. The proposed technique utilizes OFDM to transform frequency selective fading channels into multiple flat fading sub-channels on which space-frequency...
This paper presents a comparative study of three of the emerging frequency domain convolutive blind source separation (FDCBSS) techniques i.e. convolutive blind separation of non-stationary sources due to Parra and Spence, penalty function-based joint diagonalization approach for convolutive blind separation of nonstationary sources due to Wang et al. and a geometrically constrained multimodal approach...
A full-rate and full-diversity closed-loop quasi-orthogonal space time block coding scheme pioneered by Toker, Lambotharan and Chambers is proposed for application in virtual antenna arrays. The theoretical capacity and throughput gains are evaluated as a function of signal-to-noise ratio. It is shown that the scheme has particular benefits in both ergodic and non-ergodic channel environments, and...
A full rate and full diversity closed-loop quasi-orthogonal space time block coding scheme due to Toker, Lambotharan and Chambers is proposed for application in virtual antenna arrays. The performance gain is achieved through closed-loop operation involving feedback of phase rotation angle(s) calculated from channel state information (CSI) to the transmitter array. Throughput performance of the proposed...
A simple extended orthogonal space-frequency coded multiple input single output (MISO) orthogonal frequency division multiplexing (OFDM) transmitter diversity technique for wireless communications over frequency selective fading channels is presented. The proposed technique utilizes OFDM to transform frequency selective fading channels into multiple flat fading sub-channels on which space-frequency...
In this paper a new adaptive leakage factor variable tap-length learning algorithm is proposed. Through analysis the converged difference between the segmented mean square error (MSE) of a filter formed from a number of the initial coefficients of an adaptive filter, and the MSE of the full adaptive filter, is confirmed as a function of the tap-length of the adaptive filter to be monotonically non-increasing...
A study of a peak-to-average power ratio (PAPR) reduction scheme for quasi-orthogonal space- time block coded multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems based on selective mapping (SLM) is presented. The reduction technique is based upon combining the PAPRs of the transmission blocks from four antennas and exploits the associated antenna diversity gain...
Recent analytical results due to Walsh, Martin and Johnson showed that optimizing the single lag autocorrelation minimization (SLAM) cost does not guarantee convergence to high signal to interference ratio (SIR), an important metric in channel shortening applications. We submit that we can overcome this potential limitation of the SLAM algorithm and retain its computational complexity advantage by...
Partial updating is an effective method for reducing computational complexity in adaptive filter implementations. In this work, a novel random partial update sum-squared auto-correlation minimization (RPUSAM) algorithm is proposed. This algorithm has low computational complexity whilst achieving improved convergence performance, in terms of achievable bit rate, over a partial update sum-squared auto-correlation...
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