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Rayi, Prasad
- A Novel Low Complexity Algorithm for Analysis, Simulation of Proportional Resource Allocation in MIMO-OFDMA System
Authors
1 Aditya Engineering College, Surampalem, Kakinada, ECE Department, IN
2 Aditya Engineering College, Surampalem, Kakinada, IN
Source
Networking and Communication Engineering, Vol 5, No 9 (2013), Pagination: 441-447Abstract
Multiple Input Multiple Output-Orthogonal Frequency Division Multiple Access (MIMO-OFDMA) system is most sophisticated technology for multiple users to transmit multiple symbols simultaneously on different orthogonal subcarriers with same symbol period. This paper mainly focuses allocation of subcarriers by base station and power to each user to maximize the user data rates, subject to total power, bit error rate, and proportionality constraints across user data rates. Recent allocation methods have been iterative nonlinear methods applicable for offline optimization. In the special high subchannel SNR case, an iterative ischolar_main-finding method has linear-time complexity in the number of users .We proposed a new well-behaved method to solve the rate-adaptive resource allocation problem with proportional rate constraints for MIMO-OFDMA systems. It improves spectral efficiency and flexibility by achieving approximate rate proportionality while maximizing the total capacity. This scheme allowing the optimal power allocation to be performed using a direct algorithm with a much lower complexity versus an iterative algorithm. Hence it performs better than the previous work in terms of significantly decreasing the computational complexity, and yet achieving higher total capacities. The simulation results were presented with MATLAB 2013a@R.Keywords
MIMO-OFDM, SC, QAM, FFT, IFFT, FDM, BER.
- Modeling, Simulation and Capacity Analysis of Spatially Correlated Channels in MIMO Systems
Authors
1 Vignan’s Institute of Information and Technology, Duvvada, Vishakhapatnam, IN
Source
Networking and Communication Engineering, Vol 4, No 5 (2012), Pagination: 270-275Abstract
In this paper we mainly focus on capacity evaluation of Multi Input Multi Output (MIMO) systems with Spatially correlated Channel Modeling (SCM) technique. This technology promises significant improvements in spectral efficiency and throughput can be accomplished by deploying multiple antennas at both the transmitter and receiver. The proposed channel model implemented based on the knowledge of channel parameters that describe the characteristics of the channel over large areas of several Wavelength with link level design presented by shadow fading, angle spread and delay spread. Here we investigate the spatial-temporal correlation characteristics of the 3GPP-3GPP2 SCM in terms of Spatial Autocorrelation and Channel Capacity for different channel environments such as suburban macro-cell, urban macro-cell and urban micro-cell. The results show that the simulated channels provides channel capacity can be greatly increased by the more number antenna's and also optimized with spatially auto correlation for 3-sector case and 6-sector case are demonstrated by simulation results. We also compare the simulation results with prior measurement results. The comparison provides insight into the accuracy of MIMO capacity predictions using SCM model.
Keywords
AOA, AOD, MIMO, SISO, SCM, 3GPP.- Truncated and Optimized Pilot-to-Data Power Ratio for MIMO-OFDM Systems
Authors
1 Vignan‟s Institute of Information and Technology, Duvvada, Vishakhapatnam, IN
2 Sri Vaishnavi Engineering College, Srikakulam, IN
Source
Networking and Communication Engineering, Vol 4, No 5 (2012), Pagination: 276-282Abstract
This paper evaluates optimal pilot-to-data power ratio (PDPR) for capacity scaling in multi carrier systems. Orthogonal frequency division multiplexing (OFDM) is a popular method for high data rate wireless transmission. OFDM must be combined with antenna arrays at the transmitter and receiver to increase the diversity gain and also to reduce fading effects and to enhance the system capacity on time-variant and frequency-selective channels, resulting in a multiple-input multiple-output (MIMO)-OFDM configuration. Pilot-symbol-aided or decision-directed channel estimation are used to track the channel variations in MIMO-OFDM systems. While pilot symbols facilitate channel estimation, they reduce the energy to be transmitted for data symbols over a fixed total transmit power constraint. We compute a lower bound on the capacity of a channel that is learned by training, and maximize the bound as a function of the received signal-to-noise ratio, and derive the optimal PDPR in MIMO-OFDM systems with three different types of pilot patterns: independent, scattered, and orthogonal. The result tells us that implementing the optimal PDPR in an actual MIMO-OFDM system surprisingly have broad range of PDPR values over which near optimal capacity is achieved. Performance of simulation results are demonstrated in terms of information theoretic capacity and signal to noise ratio (SNR).