Abstract

In this paper, we consider the problem of hybrid multi-input multi-output (MIMO) transceiver design for a non regenerative hybrid two-way amplify-forward (AF) relay based millimeter wave (mmWave) communication system. We propose two low complexity mmWave system designs based on the quality of available channel state information (CSI). We first propose the design of transceivers and a two- way AF relay, by minimizing sum-mean square error (SMSE) under the constraint of total relay transmit power while assuming the perfect channel knowledge. We later extend it to a robust design under the assumption that the transceivers posses only imperfect information about the channel state, where the CSI error is assumed to follow the Gaussian distribution. In both the designs, reduced hardware complexity (introduced due to large number of antenna elements in mmWave system) is achieved by analog-digital hybrid processing by using orthogonal matching pursuit (OMP)-based sparse signal processing. We present numerical results on the performance of both the designs over various dictionaries. The comparison results show that robust design is resilient to the presence of CSI errors. Furthermore, we also demonstrate the convergence of both the proposed algorithms to a limit even though global convergence is hard to prove due to non convex nature of overall optimization problem.

Abstract

In this paper, we present the design of optimal precoders and receive filters for a full-duplex (FD) two-way amplify-and-forward (AF) multiple-input multiple-output (MIMO) relaying system in a cognitive radio network. The secondary user (SU) or cognitive nodes share the spectrum with the licensed primary user (PU) nodes while keeping the interference to PU nodes below a threshold. The cognitive transceivers communicate with each other with the assistance of a cognitive AF relay. The precoders for the cognitive transceivers are designed so as to maximize the signal to noise ratio (SNR) at the relay while limiting the interference to the PU node below a specified threshold. Due to FD mode of operation, all the nodes suffer from self-interference (SI). We assume the available channel state information (CSI) of loopback self-interference channels at relay and transceivers to be imperfect. We design the optimal relay precoder and transceiver receive filter, for suppressing the residual SI, by minimizing the sum of mean square error (SMSE) at the cognitive transceivers with constraint on transmit power at relay. The precoders and receive filters are updated at each time slot, taking into account the cumulative interference effect from all previous time slots, which enhances the performance of the system over time. The simulation results illustrate the effectiveness of the proposed design in terms of the achievable sum-rate.

Abstract

In this paper, we consider optimal transceiver design and relay selection for simultaneous transfer of data and energy in a cooperative network consisting of amplify-and-forward (AF) relays. In this context, we address two different problems and propose optimal relay selection and transceiver processing. Furthermore, the problems are formulated for both time switching (TS) and power splitting (PS) schemes. The first problem is the maximization of overall rate while ensuring a minimum harvested energy at the receiver. For this problem, we perform computations of optimal fractions to distribute the received signal corresponding to TS and PS schemes, the relay weighing coefficients, and optimal relay selection. In the second problem, optimal resource allocation for maximizing the overall harvested energy at the user under constraints on the minimum achievable rate has been formulated. For this problem, we propose a suitable solution to meet the requirements for both TS and PS. For both the problems, we obtain a closed form solution. Finally, the performance of proposed design under various operating conditions and parameter values are illustrated with a comparison between TS and PS schemes.

Abstract

Noise power uncertainty is a major issue in detectors for spectrum sensing. Any uncertainty in the noise power leads to significant reduction in the detection performance of the energy detector and also results in a performance limitation in the form of SNR walls. In this paper, we propose an evidence theory (also called Dempster-Shafer theory (DST)) based cooperative energy detection (CED) for spectrum sensing. The noise variance is modeled as a random variable with a known distribution. The analyzed system model is similar to a distributed parallel detection network where each secondary user (SU) evaluates the energy from its received signal samples and sends it to a fusion center (FC), which makes the final decision. However, in the proposed DST-based CED scheme, the SUs sends computed belief-values instead of actual energy value to the FC. Any uncertainty in the noise variance is accounted for by discounting the belief values based on the amount of uncertainty associated with each SU. Finally, the discounted belief values are combined using Dempster rule to reach at a global decision. Simulation results indicate that the proposed DST scheme significantly improves the detection probability at low average signal-to-noise ratio (ASNR) in comparison to the traditional sum fusion rule in the presence of noise uncertainty.

Abstract

In this paper, we consider the design of low-complexity analog-digital hybrid transceivers for a multi-input multi- output (MIMO) millimeter wave (mmWave) communication system operating in a K-user interference channel. Our objective is to achieve the energy efficiency by minimizing overall transmit power required for achieving a target mean- square error (MSE) at the receivers. We propose two transceiver designs based on the quality of the available channel state information (CSI). We first present a design that minimizes total transmit power assuming the availability of perfect channel knowledge. Later, we extend it to a robust transceiver design by considering imperfections in CSI. The proposed designs achieve reduced hardware and computational complexity by forming hybrid architecture using sparse signal processing. Hence, achieving similar MSE with lower energy consumption. We evaluate the performance of both the proposed schemes based on various parameters. Furthermore, we demonstrate the resilience of the robust design in presence of errors in CSI and performance of both the designs with various dictionaries.

Abstract

In this paper, we consider the problem of relay selection in a cognitive full-duplex two-way multiple-input multiple-output relaying network. The cognitive nodes operate on the same frequency as the licensed primary user (PU). The end-to-end communication between the secondary users (SU) via a secondary relay (SR) takes two time slots. The SR operates on amplify-and-forward (AF) protocol. In the first time slot, the SR relay with the highest receive signal-to-noise ratio is selected as the optimal relay. At the same time, the precoders at the SU are designed to limit the interference to the PU below a certain threshold. All the nodes in the network are assumed to have imperfect knowledge of channel state information of their loopback self-interference channels and hence experience residual self-interference (RSI). After selecting the optimal SR, in the next time slot, we design the SR precoder and SU receive filters, to mitigate the RSI. We do so by minimizing the sum of mean square error of the end-to-end communication with a transmit power constraint at SR. To curb the effect of cumulative RSI caused by the AF operation of the SR, we update the SR precoder and SU receive filters at each time slot. The efficacy of our proposed designs is illustrated in the simulation results.

Abstract

In this paper, we consider the design of optimal transceiver and relay processing algorithms for a full-duplex (FD) two-way amplify-and-forward (AF) multiple-input multiple-output (MIMO) relaying system. We assume the channel state information of loopback self-interference (SI) channels to be imperfect. The nodes employ pre-coders and receive filters for suppressing the residual SI. The optimal precoders at transceivers are designed by equalising the signal-to-interference-plus-noise ratio at the relay and transceiver. Using the transceiver precoders thus designed, we then design the optimal relay precoder and transceiver receive filters by minimizing the sum of mean square error at the transceivers. The optimal precoders and receive filters are continuously updated to account for the cumulative interference effect caused by AF operation of the FD relay. The secrecy performance of this system in the presence of a passive eavesdropper is analyzed by considering the relay signal to be artificial noise for the eavesdropper. The effectiveness of the proposed design is demonstrated in our simulation results.

Abstract

Millimeter wave (mmWave) communication is envisioned as a potential technology for next generation mobile communication as it can offer multi-gigabit-per-second data rate and a huge unlicensed spectrum. In this paper, we present a signal leakage-based low-complexity hybrid analog-digital transceiver design for a mmWave communication system operating in a K-user MIMO interference channel. Owing to higher cost and power consumption of components at mmWave frequencies, optimal system design with reduced hardware and computational complexity is critical to make the commercial use of mmWave communication viable. We achieve reduced hardware complexity of the proposed design by employing sparse approximation techniques for large antenna array. The proposed design is based on the maximization of signal- to-leakage-plus-noise ratio (SLNR) for all users. This leads to the reduced computational complexity of the overall system. Numerical results comparing the proposed design with existing iterative solution demonstrate that it can achieve comparable performance with reduced hardware and computational complexity. Performance of the proposed design with various dictionaries considered for beamforming has also been compared and illustrated in the simulation results.

Abstract

The existence of perceptually distinct numerosity ranges has been proposed for small (i.e., subitizing range) and larger numbers based on differences in precision, Weber fractions, and reaction times. This raises the question of whether such dissociations reflect distinct mechanisms operating across the two numerosity ranges. In the present work, we explore the predictions of a single-layer recurrent on-center, off-surround network model of attentional priority that has been applied to object individuation and enumeration. Activity from the network can be used to model various phenomena in the domain of visual number perception based on a single parameter: the strength of inhibition between nodes. Specifically, higher inhibition allows for precise representation of small numerosities, while low inhibition is preferred for high numerosities. The model makes novel predictions, including that enumeration of …

Abstract

Perception of time is an active process that takes place continually. However, we are yet to learn its exact mechanisms conclusively. The temporal bisection task is ideal to investigate the circuitry underlying time perception. Caffeine, a commonly used stimulant, has been known to play a role in modulation of time perception. The objective of this article is to explore the role of caffeine, a neuromodulator, in the perception of time in human beings by conducting suitable experiments. The experiment shows that an expansion of time is perceived by subjects after caffeine ingestion and that caffeine has an accelerating effect on our time perception system. Additionally, we present a preliminary 2-step decision model that fits the results of the experiment and potentially gives insights into the mechanisms of caffeine. We conclude by pointing out future directions towards a more biologically realistic computational model.