Blind Recognition of Linear Space–Time Block Codes: A Likelihood-Based Approach

Abstract

Blind recognition of communication parameters is a research topic of high importance for both military and civilian communication systems. Numerous studies about carrier frequency estimation, modulation recognition as well as channel identification are available in literature. This paper deals with the blind recognition of the space-time block coding (STBC) scheme used in multiple-input-multiple-output (MIMO) communication systems. Assuming there is perfect synchronization at the receiver side, this paper proposes three maximum-likelihood (ML)-based approaches for STBC classification: the optimal classifier, the second-order statistic (SOS) classifier, and the code parameter (CP) classifier. While the optimal and the SOS approaches require ideal conditions, the CP classifier is well suited for the blind context where the communication parameters are unknown at the receiver side. Our simulations show that this blind classifier is more easily implemented and yields better performance than those available in literature. Index Terms-Maximum-likelihood (ML) detection, multiple-input-multiple-output (MIMO) systems, space-time block code (STBC). I. INTRODUCTION B LIND recognition of communication parameters is an intermediate step between signal detection and signal decoding/demodulation. In civilian applications, blind recognition algorithms are used in software-defined radio (SDR) to cope with a large panel of communication systems. In electronic warfare, these algorithms are required for signal interception and processing, two tasks of key importance in tactical operations. Usually, the largest part of the algorithms is devoted to the blind recognition of single-input-single-output (SISO) communication parameters. Other investigations have dealt with the development of new technologies aimed at enhancing the reliability of data transmission in wireless communication systems. Among them, one of the most promising technologies is based on the use of multiple-input-multiple-output (MIMO)

Fast Blind Recognition of Channel Codes

“…Figures 4(a)-4(c) illustrate the ROC curves of the different schemes for the case where the SNR is 0 dB and for two different values of N b for the three convolutional codes, respectively. More precisely, we have provided ROC curves for (i) the statistical test given by (12), (ii) the suboptimal test given by (13), (iii) the suboptimal test where in addition to (13), we also used the approximation given by (11) in computing γ i , (iv) our analysis provided by (20), and (v) the test using the algorithm in [13]. 12 As the results show, the proposed statistical test (i) has better performance compared to the other tests, specially compared to the test in [13].…”

“…To the best of our knowledge, there is very little work in the literature addressing this problem in its generality. For instance in [11], [12], two blind schemes for recognition of space-time block codes and LDPC codes were proposed, respectively. The proposed algorithm therein, after intercepting a number of code blocks, computes the likelihood of each code candidate and picks the most likely one.…”

Improving the Efficiency of Control Signaling in Wireless Multiple Access Systems

“…When it is known that the channel code has been chosen from a set of predefined candidate set, the receiver can use this a priori information for achieving a better blind channel code identification. This problem was addressed in [41][42][43].…”

Joint Space Time Block Code and Modulation Classification for MIMO Systems

“…Feature based (FB) MC algorithms for SM signals can be found in [4], [5] and [6], in which modulation specific features based on higher order cumulants are employed. MIMO Similarly, LB STBC classification methods in the literature assume the presence of perfect knowledge on the employed modulation, the SNR and code block timing [7]. Their FB counterparts usually exploit the cyclostationary behavior of the received signal induced by the coding operation, which has the benefit of not requiring any a-priori information on the modulation type, however, they are sub optimal [8], [9], [10].…”