Low-Latency Compressive Active User Identification over Frequency-Selective Fading Channels

Abstract

This paper proposes a compressive sensing (CS) based active user identification scheme over frequency-selective fading channels. Unlike the conventional cyclic prefix (CP) based preamble transmission, our approach does not utilize CP in order to conserve signaling overhead, in turn reducing the system-wide processing latency. Our approach first estimates the multi-user channel impulse response vectors by solving a mixed l(2 )/ l(1) - norm optimization problem; then, the active users are identified via a sorting of the norms of the estimated channel vectors. By exploiting the Toeplitz channel matrix structure resulting from CP-free preamble transmission, analytic performance guarantee in term of the block restricted isometry property of the preamble matrix is given. Computer simulations are used to illustrate the performance of the proposed method.