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Louay M. A. Jalloul

Publications and source records attributed to Louay M. A. Jalloul.

6 recordsLinked to original sources

A Reinforcement Learning Based Universal Sequence Design for Polar Codes

To advance Polar code design for 6G applications, we develop a reinforcement learning-based universal sequence design framework that is extensible and adaptable to diverse channel conditions and decoding strategies. Crucially, our method scales to code lengths up to $2048$, making it suitable for use in standardization. Across all $(N,K)$ configurations supported in 5G, our approach achieves competitive performance relative to the NR sequence adopted in 5G and yields up to a 0.2 dB gain over the beta-expansion baseline at $N=2048$. We further highlight the key elements that enabled learning at scale: (i) incorporation of physical law constrained learning grounded in the universal partial order property of Polar codes, (ii) exploitation of the weak long term influence of decisions to limit lookahead evaluation, and (iii) joint multi-configuration optimization to increase learning efficiency.

cs.LG↗

Phase Noise Compensation Using Limited Reference Symbols in 3GPP LTE Downlink

It is known that phase noise (PN) can cause link performance to degrade severely in orthogonal frequency division multiplexing (OFDM) systems, such as IEEE 802.11, 3GPP LTE and 5G. As opposed to prior PN mitigation schemes that assume perfect channel information and/or abundant reference symbols (e.g., in 802.11), the proposed PN compensation technique applies to LTE and 5G downlink with a limited number of reference symbols. Specifically, in this work, we propose an efficient PN mitigation algorithm where the PN statistics are used to obtain more accurate channel estimates. Based on LTE downlink subframe structure, numerical results corroborate the effectiveness of the proposed algorithm.

cs.IT↗

A Low-Complexity Detection Algorithm for the Primary Synchronization Signal in LTE

One of the challenging tasks in LTE baseband receiver design is synchronization, which determines the symbol boundary and transmitted frame start-time, and performs cell identification. Conventional algorithms are based on correlation methods that involve a large number of multiplications and thus lead to high receiver hardware complexity and power consumption. In this paper, a hardware-efficient synchronization algorithm for frame timing based on K-means clustering schemes is proposed. The algorithm reduces the complexity of the primary synchronization signal for LTE from 24 complex-multiplications, currently best known in the literature, to just 8. Simulation results demonstrate that the proposed algorithm has negligible performance degradation with reduced complexity relative to conventional techniques.

cs.IT↗

Optimized Configurable Architectures for Scalable Soft-Input Soft-Output MIMO Detectors with 256-QAM

This paper presents an optimized low-complexity and high-throughput multiple-input multiple-output (MIMO) signal detector core for detecting spatially-multiplexed data streams. The core architecture supports various layer configurations up to 4, while achieving near-optimal performance, as well as configurable modulation constellations up to 256-QAM on each layer. The core is capable of operating as a soft-input soft-output log-likelihood ratio (LLR) MIMO detector which can be used in the context of iterative detection and decoding. High area-efficiency is achieved via algorithmic and architectural optimizations performed at two levels. First, distance computations and slicing operations for an optimal 2-layer maximum a posteriori (MAP) MIMO detector are optimized to eliminate the use of multipliers and reduce the overhead of slicing in the presence of soft-input LLRs. We show that distances can be easily computed using elementary addition operations, while optimal slicing is done via efficient comparisons with soft decision boundaries, resulting in a simple feed-forward pipelined architecture. Second, to support more layers, an efficient channel decomposition scheme is presented that reduces the detection of multiple layers into multiple 2-layer detection subproblems, which map onto the 2-layer core with a slight modification using a distance accumulation stage and a post-LLR processing stage. Various architectures are accordingly developed to achieve a desired detection throughput and run-time reconfigurability by time-multiplexing of one or more component cores. The proposed core is applied as well to design an optimal multi-user MIMO detector for LTE. The core occupies an area of 1.58MGE and achieves a throughput of 733 Mbps for 256-QAM when synthesized in 90 nm CMOS.

cs.IT↗

Multi-User MIMO Receivers With Partial State Information

We consider a multi-user multiple-input multiple-output (MU-MIMO) system that uses orthogonal frequency division multiplexing (OFDM). Several receivers are developed for data detection of MU-MIMO transmissions where two users share the same OFDM time and frequency resources. The receivers have partial state information about the MU-MIMO transmission with each receiver having knowledge of the MU-MIMO channel, however the modulation constellation of the co-scheduled user is unknown. We propose a joint maximum likelihood (ML) modulation classification of the co-scheduled user and data detection receiver using the max-log-MAP approximation. It is shown that the decision metric for the modulation classification is an accumulation over a set of tones of Euclidean distance computations that are also used by the max-log-MAP detector for bit log-likelihood ratio (LLR) soft decision generation. An efficient hardware implementation emerges that exploits this commonality between the classification and detection steps and results in sharing of the hardware resources. Comparisons of the link performance of the proposed receiver to several linear receivers is demonstrated through computer simulations. It is shown that the proposed receiver offers \unit[1.5]{dB} improvement in signal-to-noise ratio (SNR) over the nulling projection receiver at $1\%$ block error rate (BLER) for $64$-QAM with turbo code rate of $1/2$ in the case of zero transmit and receiver antenna correlations. However, in the case of high antenna correlation, the linear receiver approaches suffer significant loss relative to the optimal receiver.

cs.IT↗

Efficient Soft-Input Soft-Output Detection of Dual-Layer MIMO Systems

A dual-layer multiple-input multiple-output (MIMO) system with multi-level modulation is considered. A computationally efficient soft-input soft-output receiver based on the exact max-log maximum a posteriori (max-log-MAP) principle is presented in the context of iterative detection and decoding. We show that the computational complexity of our exact max-log-MAP solution grows linearly with the constellation size and is, furthermore, less than that of the best known methods of Turbo-LORD that only provide approximate solutions. Using decoder feedback to change the decision thresholds of the constellation symbols, we show that the exhaustive search operation boils down to a simple slicing operation. For various simulation parameters, we verify that our solution performs identically to the brute-force exhaustive search max-log MAP solution.

cs.IT↗