On sphere detection for OFDM based MIMO systems

Abstract: The mobile wireless communication systems has been growing fast and continuously over the past two decades. Therefore, in order to fulfill the demand for this rapid growth, the standardization bodies along with wireless researchers and mobile operators around the world have been constantly working on new technical specifications.An important problem in modern communication is known as NP complete problem in the Maximum Likelihood (ML) detection of signals transmitting over Multiple Input Multiple Output channel of the OFDM transceiver system. Development of the Sphere Decoder (SD) as a result of the rapid advancement in signal processing techniques provides ML detection for MIMO channels at polynomial time complexity average case. There are weaknesses in the existing SDs. The sphere decoder performance is very sensitive for the most current proposals in order to choose the search radius parameter. At high spectral efficiencies SNR is low or as the problem dimension is high and the complexity coefficient can become very large too. Digital communications of detecting a vector of symbols has importance as, is encountered in several different applications. These symbols are as the finite alphabet and transmitted over a multiple-input multiple-output (MIMO) channel with Gaussian noise. There are no limitation to the detection of symbols spatially multiplexed over a multiple-antenna channel and the multi user detection problem. Efficient algorithms are considered for the detection problems and have recognized well. The algorithm of sphere decoder, orders has optimal performance considering the error probability and this has proved extremely efficient in terms of computational complexity for moderately sized problems in case of signal to noise ratio. At high SNR the algorithm has a polynomial average complexity and it is understood the algorithm has an exponential worst case complexity. The efficiency of the algorithm is ordered the exponential rate derivation of growth. Complexity is positive for the finite SNR and small in the high SNR. To achieve the sphere decoding solution applying Schnorr-Euchner by Maximum likelihood method , Depth-first Stack-based Sequential decoding is used. This thesis focuses on the receiver part of the transceiver system and takes a good look at the near optimal algorithm for sphere detection of a vector of symbols transmitted over MIMO channel. The analysis and algorithms are general in nature.