Efficient Algorithmic and Architectural Optimization of QR-based Detector for V-BLAST

The use of multiple antennas at both transmitting and receiving sides of a rich scattering communication channel improves the spectral efficiency and capacity of digital transmission systems compared with the single antenna communication systems. However algorithmic complexity in the realization of the receiver is a major problem for its implementation in hardware. This paper investigates a near optimal algorithm for V-BLAST detection in MIMO wireless communication systems based on the QR factorization technique, offering remarkable reduction in the hardware complexity. Specifically, we analyze some hardware implementation aspects of the selected algorithm through MATLAB simulations and demonstrate its robustness. This technique can be used in an efficient fixed point VLSI implementation of the algorithm. We also provide the VLSI architecture that implements the algorithm

Mobile-PolypNet: Lightweight Colon Polyp Segmentation Network for Low-Resource Settings

Colon polyps, small clump of cells on the lining of the colon, can lead to colorectal cancer (CRC), one of the leading types of cancer globally. Hence, early detection of these polyps automatically is crucial in the prevention of CRC. The deep learning models proposed for the detection and segmentation of colorectal polyps are resource-consuming. This paper proposes a lightweight deep learning model for colorectal polyp segmentation that achieved state-of-the-art accuracy while significantly reducing the model size and complexity. The proposed deep learning autoencoder model employs a set of state-of-the-art architectural blocks and optimization objective functions to achieve the desired efficiency. The model is trained and tested on five publicly available colorectal polyp segmentation datasets (CVC-ClinicDB, CVC-ColonDB, EndoScene, Kvasir, and ETIS). We also performed ablation testing on the model to test various aspects of the autoencoder architecture. We performed the model evaluation by using most of the common image-segmentation metrics. The backbone model achieved a DICE score of 0.935 on the Kvasir dataset and 0.945 on the CVC-ClinicDB dataset, improving the accuracy by 4.12% and 5.12%, respectively, over the current state-of-the-art network, while using 88 times fewer parameters, 40 times less storage space, and being computationally 17 times more efficient. Our ablation study showed that the addition of ConvSkip in the autoencoder slightly improves the model\u27s performance but it was not significant (-value = 0.815)

Adaptive Turbo-Coded Hybrid-ARQ in OFDM Systems over Gaussian and Fading Channels

In this paper, an analytical approach for spectral efficiency maximization of coded wideband transmissions is presented based on OFDM. The approach exploits Type-III Hybrid-ARQ, enabling all sub-carriers to be employed in codeword transmission regardless of the sub-carrier conditions. The effects of imperfect sub-channel estimation are characterized and compensated for during code rate and signal constellation optimization. The results of the paper highlight that by independently adapting the code rate and signal constellation to individual OFDM sub-carriers based on an estimated sub-carrier CSI, the overall spectral efficiency of the system is maximized

A Robust QR based detector for V Blast and its efficient hardware implementation

The use of multiple antennas at both transmitting and receiving sides of a communication channel has increased the spectral efficiency to near the Shannon bound. However algorithmic complexity in the realization of the receiver is a major problem for its hardware implementation. In this paper we investigate a near optimal algorithm for V-BLAST detection in MIMO wireless communication systems based on QR factorization, offering remarkable reduction in the hardware complexity. Specifically, we analyze some hardware implementation aspects of the selected algorithm through MATLAB simulations and demonstrate its robustness. This technique can be used in an efficient fixed point VLSI implementation of the algorith

Circular Sphere Decoding: A Low Complexity Detection for MIMO Systems with General Two-dimensional Signal Constellations

We propose a low complexity complex valued Sphere Decoding (CV-SD) algorithm, referred to as Circular Sphere Decoding (CSD) which is applicable to multiple-input multiple-output (MIMO) systems with arbitrary two dimensional (2D) constellations. CSD provides a new constraint test. This constraint test is carefully designed so that the element-wise dependency is removed in the metric computation for the test. As a result, the constraint test becomes simple to perform without restriction on its constellation structure. By additionally employing this simple test as a prescreening test, CSD reduces the complexity of the CV-SD search. We show that the complexity reduction is significant while its maximum-likelihood (ML) performance is not compromised. We also provide a powerful tool to estimate the pruning capacity of any particular search tree. Using this tool, we propose the Predict-And-Change strategy which leads to a further complexity reduction in CSD. Extension of the proposed methods to soft output SD is also presented.Comment: Published in IEEE Trans. Vehicular Technolog

Exploiting Block Structures of KKT Matrices for Efficient Solution of Convex Optimization Problems

Convex optimization solvers are widely used in the embedded systems that require sophisticated optimization algorithms including model predictive control (MPC). In this paper, we aim to reduce the online solve time of such convex optimization solvers so as to reduce the total runtime of the algorithm and make it suitable for real-time convex optimization.We exploit the property of the Karush–Kuhn–Tucker (KKT) matrix involved in the solution of the problem that only some parts of the matrix change during the solution iterations of the algorithm. Our results show that the proposed method can effectively reduce the runtime of the solvers

Power-performance versus algorithmic trade-offs in the implementation of wireless multimedia terminals

Circuit design for wireless applications generally involves achieving a certain level of processing speed, dictated by the data transmission rate and algorithmic performance, while minimizing the energy dissipation. This paper discusses some of the circuit techniques that help to achieve this goal. We show that power reduction in a multimedia system involves trade-offs at the algorithmic, algebraic, architectural, and circuit levels of abstraction. © 2010 IEEE