Block Data Transmission Systems (BDTS) are used in high-speed wireless communication systems with time dispersive channel characteristics. In such systems, blocks of data are separated by zeros to mitigate the effect of Inter-Symbol-Interference (ISI) between the blocks. An optimal detection process employs the Maximum Likelihood Block Detection (MLBD) technique on each block individually in the presence of ISI and Gaussian noise based on the Euclidean distance as an objective function. The detection process is computationally expensive therefore Genetic Algorithms have been used to reduce the overall design complexity. In this work, three types of Genetic Algorithms have been incorporated in the detection process i.e. the conventional GA, Micro GA(μGA), and Hybrid μGA to reduce computational load. In particular, a novel training method for Hybrid μGA has been proposed. Simulation results at 10 dB channel SNR for the BDTS with Hybrid μGA executes as low as 3,750 number of objective functions evaluation for a block size of 20. The Bit Error Rate (BER) performance of this system is relatively good i.e. around 1 dB inferior to the BDTS using the Exhaustive Search method that requires as many as 2 20 number of objective functions evaluation. Keywords: Block Transmission, Inter Symbol Interference, dispersive channels, genetic algorithms, additive white gaussian noise Classification: Science and engineering for electronics IEEE Trans. Veh. Technol., vol. 41, no. 3, pp. 255-263, Aug. 1992

The recent wireless communication networks rely on the new technology named Long Term Evolution (LTE) to offer high data rate real-time (RT) traffic with better Quality of Service (QoS) for the increasing demand of customer requirement. LTE provide low latency for real-time services with high throughput, with the help of two-level packet retransmission. Hybrid Automatic Repeat Request (HARQ) retransmission at the Medium Access Control (MAC) layer of LTE networks achieves error-free data transmission. The performance of the LTE networks mainly depends on how effectively this HARQ adopted in the latest communication standard, Universal Mobile Telecommunication System (UMTS). The major challenge in LTE is to balance QoS and fairness among the users. Hence, it is very essential to design a down link scheduling scheme to get the expected service quality to the customers and to utilize the system resources efficiently. This paper provides a comprehensive literature review of LTE MAC layer and six types of QoS/Channel-aware downlink scheduling algorithms designed for this purpose. The contributions of this paper are to identify the gap of knowledge in the downlink scheduling procedure and to point out the future research direction. Based on the comparative study of algorithms taken for the review, this paper is concluded that the EXP Rule scheduler is most suited for LTE networks due to its characteristics of less Packet Loss Ratio (PLR), less Packet Delay (PD), high throughput, fairness and spectral efficiency.

The complexity of the exhaustive search decoding technique such as Maximum Likelihood Block Detection (MLBD) grows exponentially with the size of transmitted data. In this paper, a Lattice Sphere Decoding (LSD) technique is proposed for detection in block data transmission systems (BDTS). Simulation results at 10 dB channel SNR of BDTS with LSD using block size of 20 performs are near Hybrid Micro Genetic Algorithm (HMGA) and slightly inferior than the exhaustive search technique using the channels with spectral nulls. In term of complexity, the proposed LSD technique requires only 460 and 126 objective functions evaluation using radius selection based on Babai Estimation (BE) and off-line observation respectively, while the HMGA and exhaustive search requires 3750 and 2 20 objective functions evaluation respectively.

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