Compressive coded random access for massive MTC traffic in 5G systems

Massive MTC support is an important future market segment, but not yet efficiently supported in cellular systems. In this paper we follow-up on recent concepts combining advanced MAC protocols with Compressed Sensing (CS) based multiuser detection. Specifically, we introduce a concept for sparse joint activity, channel and data detection in the context of the Coded ALOHA (FDMA) protocol. We will argue that a simple sparse activity and data detection is not sufficient (as many papers do) because control resources are in the order of the data. In addition, we will improve on the performance of such protocols in terms of the reduction of resources required for the user activity, channel estimation and data detection. We will mathematically analyze the system accordingly and provide expressions for the capture probabilities of the underlying sparse multiuser detector. Finally, we will provide CS algorithms for the joint estimation scheme and evaluate its performance.

[1]  Petar Popovski,et al.  Coded random access: applying codes on graphs to design random access protocols , 2014, IEEE Communications Magazine.

[2]  S. Foucart.  Sparse Recovery Algorithms: Sufficient Conditions in Terms of RestrictedIsometry Constants , 2012 .

[3]  M. Rudelson,et al.  On sparse reconstruction from Fourier and Gaussian measurements , 2008 .

[4]  Chen Wang,et al.  Compressive random access for post-LTE systems , 2014, 2014 IEEE International Conference on Communications Workshops (ICC).

[5]  Carsten Bockelmann,et al.  Characterization of coded random access with compressive sensing based multi-user detection , 2014, 2014 IEEE Global Communications Conference.

[6]  Petar Popovski,et al.  Exploiting capture effect in frameless ALOHA for massive wireless random access , 2014, 2014 IEEE Wireless Communications and Networking Conference (WCNC).

[7]  Holger Boche,et al.  Sparse Signal Processing Concepts for Efficient 5G System Design , 2014, IEEE Access.

[8]  Petar Popovski,et al.  Coded Random Access: How Coding Theory Helps to Build Random Access Protocols , 2014, ArXiv.

[9]  Michael Mitzenmacher,et al.  Analysis of random processes via And-Or tree evaluation , 1998, SODA '98.

[10]  Gerhard Wunder,et al.  Compressive Random Access Using a Common Overloaded Control Channel , 2015, 2015 IEEE Globecom Workshops (GC Wkshps).

[11]  Frank Schaich,et al.  5GNOW: non-orthogonal, asynchronous waveforms for future mobile applications , 2014, IEEE Communications Magazine.