Simultaneous reception and sensing using multiple antennas in cognitive cellular networks

Abstract

We consider the problem of sensing in the presence of a desired signal in the context of future 3GPP LTE-A based cognitive cellular systems employing multiple-input multipleoutput (MIMO) transmission. Energy detection (ED) based on equal gain combining and beamforming are investigated. Receive beamformers for energy detection (ED) are designed according to the Neyman-Pearson criterion to maximize the probability of detection for a given probability of false alarm. Suitable suboptimum solutions to the maximization problem with a good tradeoff between performance and complexity are identified. Furthermore, we also formulate the likelihood ratio test (LRT) for this scenario. Performance simulations indicate that a significant performance gain is achieved in ED if the receive beamformer is chosen properly. This work has been performed in the framework of the Cognitive Mobile Radio (CoMoRa) project, which is partly funded by the Federal Ministry of Education and Research (BMBF) of Germany.

On simultaneous sensing and reception for cognitive LTE-A systems

“…In [8], we studied beamformers for maximizing the probability of detection for a constant target probability of false alarm in a frequency-nonselective fading channel. It was shown that the best of the considered suboptimal beamformers is the solution to a maximum Rayleigh quotient problem.…”

“…Hence, we compute t BF from link level simulations. As in [8][9], we adopt the following form for the threshold.…”

“…The majority of prior studies addresses the problem of sensing before transmission where the objective is to determine whether a primary signal is present or not [13], which we refer to as Type 1 sensing in this work. Recent studies have been considering a new type of sensing where the sensing is performed while the transmission of the secondary user takes place [8][14] [15], which we refer to as Type 2 sensing. Traditional cognitive radio protocols consist of a sensing phase with Type 1 sensing followed by the data transmission phase.…”

“…Nevertheless, energy detection is still attractive for practical implementations due to its simplicity. In [8], we have developed beamforming based energy detection (ED-BF) algorithms for Type 2 sensing in cognitive LTE-A systems, and the performance of the proposed schemes have been studied for a frequency-nonselective Rayleigh fading channel. Here, we consider a reference signal cancellation based energy detector, and its performance is compared to that of the ED-BF scheme under practical channel conditions and with realistic channel estimation.…”

Simultaneous Spectrum Sensing and Data Reception for Cognitive Spatial Multiplexing Distributed Systems

“…In addition, the concept of simultaneous data reception and spectrum sensing for singleantenna nodes was studied in [17], [18], while for multiple-antenna nodes in [19]. However, these works used the central limit theorem to approximate the total received signal as a Gaussian input (invoking the constraint of sufficiently large amount of received samples), whereas they provided only semi-analytical and/or simulation results with respect to the system performance.…”