惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

G
Google Developers Blog
小众软件
小众软件
The Cloudflare Blog
S
SegmentFault 最新的问题
美团技术团队
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
阮一峰的网络日志
阮一峰的网络日志
博客园 - 聂微东
V
Visual Studio Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
雷峰网
雷峰网
WordPress大学
WordPress大学
T
Tailwind CSS Blog
腾讯CDC
人人都是产品经理
人人都是产品经理
月光博客
月光博客
Microsoft Azure Blog
Microsoft Azure Blog
M
MIT News - Artificial intelligence
D
DataBreaches.Net
Apple Machine Learning Research
Apple Machine Learning Research
P
Proofpoint News Feed
J
Java Code Geeks
宝玉的分享
宝玉的分享

cs.IT updates on arXiv.org

Theoretical Limits of Language Model Alignment $f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models When Can Voting Help, Hurt, or Change Course? Exact Structure of Binary Test-Time Aggregation When Semantic Communication Meets Queueing: Cross-Layer Latency and Task Fidelity Optimization Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation Conditional Diffusion Under Linear Constraints: Langevin Mixing and Information-Theoretic Guarantees Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval Expert Routing for Communication-Efficient MoE via Finite Expert Banks Contextual Memory-Enhanced Source Coding for Low-SNR Communications Realizable Bayes-Consistency for General Metric Losses Leveraging Code Automorphisms for Improved Syndrome-Based Neural Decoding A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy Optimization of CV-QKD Under Practical Constraints Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation Evolving Token Communication with Parametric Memory Network Remote Action Generation: Remote Control with Minimal Communication The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation Linear-Readout Floors and Threshold Recovery in Computation in Superposition Soft Graph Diffusion Transformer for MIMO Detection Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design Exponential families from a single KL identity MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness Diffusion-OAMP for Joint Image Compression and Wireless Transmission Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
Performance Estimation of 2*3 MIMO-MC-CDMA using Convolut...
Atul Singh Kushwah, Sachin Manglasheril · 2014-03-12 · via cs.IT updates on arXiv.org

In this paper we estimate the performance of 2by3 MIMOMCCDMA system using convolution code in MATLAB which highly reduces BER by increasing the efficiency of system. MIMO and MCCDMA system combination is used to reduce bit error rate and also for forming a new system called MCCDMA which is multi user and multiple access schemes used to increase the performance of the system. MCCDMA system is a narrowband flat fading in nature which converts frequency selective to numerous narrowband flat fading multiple parallel sub-carriers to increase the efficiency of the system. Now this MCCDMA system can also be enhanced by grouping with 2by3 MIMO system which utilizes ZF decoder at the receiver to decrease BER in which half rate convolutionally encoded Alamouti STBC block code is used for channel encoding scheme as transmit diversity of MIMO with multiple transmit antenna. And convolution encoder is also used as source encoder or FEC encoder in MIMOMCCDMA. Advantage of using MIMO-MC-CDMA using convolution code is due to reduce complexity of system and also for reducing BER and finally to increase gain of system. Now after this we examine system in various modulation techniques like, 8PSK, 16QAM, QPSK, 32QAM, 8QAM and 64QAM using MATLAB in Rayleigh fading channel.