Efficient Multimedia Data Transmission Model for Future Generation Wireless Network

Abstract

To meet the resource demands of future wireless communications due to the increased usage of smart phones, smart devices and video-streaming platforms have led the future wireless communications to deploy dense heterogeneous Cloud Radio Access Network Systems (C-RANs). The heterogeneous communication environment offers fine-grained uniform experience to its subscribers and low-cost deployment irrespective of user location in the communication environment. The C-RANs have emerged as one of the promising solution to meet the operational cost, Quality of Service (QoS), and compression of baseband data requisite. This work, considers implementation of C-RAN model where baseband unit (BBU) and Remote Radio Heads (RRH) are connected through Common Public Radio Interface (CPRI) Fronthaul links. For such networks, reducing the data rate compression is very essential as the Fronthaul links capacity is limited and costly as they transport complex baseband samples. Fronthaul compression exploits the spatial and temporal behavior of time domain LTE signals for reducing the data rates has been considered by the existing models nonetheless it remains a challenge. To overcome the research challenge in building better transmission model, this work considers jointly exploiting both spatial and temporal correlations of the transmitted baseband signals to obtain efficient Fronthaul compression performance for LTE cellular networks using Refined Huffman. This work, assumes a case similar to massive Multiple-Input Multiple-Output (MIMO) communication mobile environment, where number of receiving antennas will outnumber the active user terminals. Our model applies Low-Rank (LR) approximation of complex baseband samples to obtain spatial and temporal correlations construction matrices of signals. The correlated baseband signals are then encoded using proposed refined Huffman encoder technique (RHCT) to achieve better compression. Experiments are carried out for evaluating the performance attained by the proposed method with Standard Huffman. The results obtained displays, that the proposed model attains superior performance enhancement than the existing state-of-the-art Huffman encoder model in terms of Symbol Error Rate (SER), Bit Error Rate (BER), Compression, and Throughput (Sum rate).