Compressive sensing and reception for MIMO-OFDM based cognitive radio

Abstract

This paper explores a novel receiver architecture for multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) that utilizes compressive sensing (CS) technique. Assuming that a limited number of subcarriers are used simultaneously in one MIMO-OFDM channel, we show that the conventional MIMO receiver can be replaced with the proposed receiver to compressively sample signals. In the proposed reception architecture, signals from multiple antennas are mixed and sampled with less hardware by exploiting the sparsity in the OFDM channel usage. Applying the CS technology to the receiver directly reduces the power consumption in mixed signal circuit which is attributable to less number of analog-to-digital converters (ADCs). A new streamlined algorithm for digital signal processing (DSP) to recover the compressively sensed data is also devised. Besides the simplification of the signal sensing, the simulation results also show that the reception fidelity of the proposed architecture outperforms that of the conventional maximum likelihood (ML) MIMO detector when the channel is lightly loaded.

Optimal reception of sub-sampled time-domain sparse signals in wired/wireless OFDM transceivers

“…The dimensions of the image used, are 280 × 280 = 78400 pixels, with 3509 of them being nonsparse (or equivalently S = 4.4 %). In [15], a 4 × 4 MIMO system with 256 subcarriers is simulated and the BER is examined for a different number of active subcarriers (between 4 and 32).…”

“…Information reconstruction in MIMO-OFDM cognitive radio (CR) is described in [15] using compressive sensing techniques. However, this approach is different compared to the one presented here: CR radios target to the efficient spectrum utilization when several subcarriers are unused by the licensed users.…”

“…FFTs implemented with fewer than O(N ·logN) operations can be found in [12][13][14]. A MIMO-OFDM cognitive radio is described in [15]. Compressively sensed data are recovered, using fewer hardware resources: a single analogue/digital converter (ADC) and smaller buffer memory.…”

Sub-nyquist sampling techniques for cognitive radio applications

“…Due to its high robustness to noise, the modulated wideband converter (MWC) [63] has become the favorite design for CS based CR receivers [64,65] to alleviate both the analog and digital processing requirements. As demonstrated in [86,87], incorporating the CS framework into MIMO-OFDM based CR's reception can produce a simpler hardware circuitry and reduce MIMO scale in CR receiver design. As shown in Figure 2.15, the number of receiver's sampling circuits can be reduced such that only one ADC is required.…”

“…However, for the MWC circuit used in the OFDM based CS-CR receiver, the issue of mutual coherence has always been neglected in existing designs [3,86,112]. An important reason is due to the fact that Φ and Ψ are pre-determined such that the…”