Total views : 372
Performance Comparison of Coded and Uncoded MIMO-OFDM with Linear and Non-Linear Detector
Background/Objectives: Orthogonal Frequency Division Multiplexing (OFDM) is a very popular data transmission technique that can be easily applied in wire line or wireless data communication applications. But this OFDM system has several weaknesses; one of them is the complexity of OFDM system. This complexity problem can lead to the decreasing performance of OFDM when it is applied in real hardware. Methods/Statistical Analysis: In this paper, we investigate the performance of one of the most complex OFDM system, Multiple Input Multiple Output (MIMO) OFDM, with channel code and linear detector, and MIMO-OFDM without channel code and non-linear detector, to find which MIMO-OFDM system has lower complexity and decent performance. We calculate its complexity by analyzing how many mathematical operations needed to implement the system. Findings: The analytical and simulation results indicate that MIMO-OFDM with channel coding and linear detector has lower complexity than MIMO-OFDM with non-linear detector. Although the performance is slightly lower than the system with non-linear detector, the system with channel coding and linear detector is more suitable for hardware implementation. Application/Improvements: For future enhancement, this system needs to be applied in the real hardware system to analyze the performance further
Complexity, Channel Estimation, Detector, MIMO, OFDM, Wireless Communication.
- Foschini GJ. Layered space time architecture for wireless communication in fading environment when using multiple antennas. Bell Laboratories Technical Journal. 1996; 1(2):41–9.
- Wolniansky PW, Valenzuela RA.V-BLAST: An architecture for realizing very high data rates over the rich-scattering wireless channel. Holmdel Keyport: Bell Laboratories, Crawford Hill Laboratory; 1988. p. 295–300.
- Damen MO, Gamal HE, Caire G. On maximum likelihood detection and search for the closest lattice point.IEEE Transaction of Information Theory. 2003; 49(10): 2389–402.
- Hassibi B, Vikalo H. On the sphere-decoding algorithm I. Expected complexity. IEEE Transactions on Signal Processing. 2005; 53(8):2806–12.
- Vallavaraj A, Brian GS. Optimizing the rate ½: Convolutional code for OFDM applications in terms of bit-error-rate and peak-to-average power ratio. GCC Conference (GCC); Manama. 2006. p. 1–6.
- Astawa IG, Moegiharto Y, Salim IDA, Anggraeni NA. Performance analysis of MIMO-OFDM using convolution codes with QAM modulation. International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering. 2013; 7(12):1–4.
- Ranjith S, Vishnupriya T. Analysis and design of SDF architecture for MIMO application. Indian Journal of Science and Technology. 2016 Feb; 9(8):1–5.
- Sivakumar R, Deepa P, Sankaran D. A study on BFO algorithm based PID controller design for MIMO process using various cost functions. Indian Journal of Science and Technology. 2016 Mar; 9(12):1–6.
- Paulraj AJ, Gore DA, Nabar RU, Bölcskei H. An overview of MIMO communications- A key to gigabit wireless. Proc IEEE. 2004 Feb; 92(2):198–218.
- Nguyen TT. Performance comparisons of detector algorithms for high data rate MIMO OFDM systems in frequency selective fading channel. 2012 IEEE International Symposium Signal Processing and Information Technology (ISSPIT); Ho Chi Minh City. 2012. p. 1–5.
- Chatzigeorgiou IA, Rodrigues MRD, Wassel IJ, Carassco R. Comparison of convolutional and turbo coding schemes for broadband FWA systems. IEEE Transactions on Broadcasting. 2007; 53:494–503.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.