Tharm Ratnarajah

Outage Analysis of Decode-and-Forward Cognitive Dual-Hop Systems With the Interference Constraint in Nakagami-

This paper studies the outage probability performance of decode-and-forward (DF) cognitive dual-hop systems for Nakagami-m fading channels, with consideration of an interference temperature limit. An exact outage probability expression is derived, and the impact of various key system parameters, such as interference temperature and fading severity, is investigated. Our results show that the interference temperature constraint causes the outage saturation phenomenon, but the outage performance gets better when the channel quality of the secondary transmission links improves. However, how the channel quality of the interfering links affects the outage performance depends on the channel quality of the secondary transmission links, as well as the interference temperature constraint and maximum transmit power.

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Abstract-In this paper, the emerging interference alignment technique is applied into the prevailing cognitive radio system. Dynamic spectrum access enables the secondary users to coexist with the licensed primary user in a cognitive radio system. However, to mitigate the intrinsic network interference of secondary users is becoming a challenge, even for the secondary network itself. Moreover, the primary user offers limited resource to share with secondary users. Here, a novel interference-oriented and alignment-based scheme is proposed, which explores the impact of propagation delay on the degrees of freedom of cognitive radio and is called interference draining scheme. On one hand, the secondary users network try to share the same interference draining space at the primary user; on the other hand, the secondary users network aligns its own internal interference. Delicate cooperation between primary user and secondary users network is implemented. A temporal paradigm illustrates a successful interference draining procedure. The interference draining efficiency manifests a surprising increase with the number of secondary users.

Fading Channels

We consider a peer-to-peer cognitive radio (CR) network with single primary user and multiple secondary users. We propose an interference alignment technique for this network, and show that desired secondary user performances can be archived without degrading the primary user performance for both single and multiple antenna networks. For the multiple antenna networks, we optimize both the precoding vectors and power allocation to enhance the secondary user rates using a gradient method. Numerical results are given for primary and secondary users rates, which show that the proposed precoding vectors and power allocation algorithm enhance the performance of the CR network. Hence the proposed interference alignment scheme significantly enhances the spectrum efficiency.

A Novel Interference Draining Scheme for Cognitive Radio Based on Interference Alignment

In this paper, the distribution of the ratio of extreme eigenvalues of complex Wishart matrix is studied in order to calculate the exact decision threshold as a function of the desired probability of false alarm for maximum-minimum eigenvalue (MME) detection method for multiple receiver collaborative spectrum sensing. Furthermore, the proposed exact formulation is simplified for the case of two receiver based collaborative spectrum sensing and with finite number of samples. In addition, an approximate closed form formula of the exact threshold is derived in terms of a desired probability of false alarm for a special case having equal number of receive antennas and signal samples. Finally, using Monte-Carlo simulations, we verify the estimated values of exact decision threshold and their approximated closed-form values. The probability of detection performance has been verified using the proposed exact decision thresholds achieving significant performance gains compared to the performance of the asymptotic decision threshold.

On secondary network interference alignment in cognitive radio

This article presents an analytical investigation on the performance of interference-limited fixed-gain amplify-and-forward dual-hop relaying systems over Nakagami-m fading channels. Assuming the fading parameter m of the two hop channels being integer, we derive a closed-form expression of the cumulative distribution function of a new type of random variables involving a number of independent gamma random variables, based on which, the outage performance and symbol error rate of the system are examined, and two important performance metrics at the high signal-to-noise ratio regime, namely, diversity order and coding gain, are characterized. Moreover, expressions of the general moments of the end-to-end signal-to-interference-and-noise ratio are derived and then applied in the analysis of the ergodic capacity of the system. In addition, the impact of interference power distribution on the ergodic capacity of the system is studied with the aid of a majorization result. Our findings suggest that the diversity of the system is limited by the hop experiencing severer fading, and co-channel interferences do not reduce the diversity order of the system, instead, they degrade the outage performance by affecting the coding gain of the system.

On the Performance of Eigenvalue-Based Spectrum Sensing for Cognitive Radio

In this paper, the performance of cloud radio access networks (CRANs) where spatially distributed remote radio heads (RRHs) aid the macro base station (MBS) in transmission is analysed. In order to reflect a realistic scenario, the MBS and the RRHs are assumed to be equipped with multiple antennas and distributed according to a Poisson point process. Both, the MBS and the RRHs, are assumed to employ maximal ratio transmission (MRT) or transmit antenna selection (TAS). Considering downlink transmission, the outage performance of three schemes is studied; first is the selection transmission (ST) scheme, in which the MBS or the RRH with the best channel is selected for transmission. In the second scheme, all the RRHs participate (ARP) and transmit the signal to the user, whereas in the third scheme, a minimal number of RRHs, to attain a desired data-rate, participate in transmission (MRP). Exact closed-form expression for the outage probability is derived for the ST scheme. For the ARP and MRP schemes, analytical approximations of the outage probability are derived which are tight at high signal-to-noise ratios. In addition, for the MRP scheme, the minimal number of RRHs required to meet a target data rate is also calculated which can be useful in characterizing the system complexity. Furthermore, the derived expressions are validated through numerical simulation. It is shown that the average diversity gains of these schemes are independent of the intensity/number of RRHs and only depend on the number of antennas on the MBS. Furthermore, the ARP scheme outperforms the ST scheme when the MBS/RRHs transmit with maximum power. However, in case of a sum power constraint and equal power allocation, the ST scheme outperforms the ARP scheme.

Performance analysis of fixed-gain AF dual-hop relaying systems over Nakagami-m fading channels in the presence of interference

In this work, interference alignment is designed for peer-to-peer underlay MIMO cognitive radio network in which single primary user (PU) coexists with multiple secondary users (SUs). The proposed scheme chooses the transmit precoding and receiver interference subspace to minimize the total interference leakage while limiting the interference level to the PU. With perfect knowledge of local channel information, the optimization problem is solved iteratively, in which the transmitter and receivers take turns to update the precoding and interference receiving matrices, respectively. It is proven that the algorithm converges monotonically, and simulation results reveal the effectiveness of the proposed interference alignment scheme for cognitive radio network.

Performance Analysis of Cloud Radio Access Networks With Distributed Multiple Antenna Remote Radio Heads

We consider the problem of detecting a vector signal transmitted over a multiple input-multiple output (MIMO) channel. A number of suboptimal detectors have been proposed to solve that problem, given that maximum likelihood (ML) detection is NP-hard. After reviewing the main concepts of the ML and the minimum mean square error (MMSE) metrics, we introduce an unbiased MMSE metric that can be applied to existing MIMO detectors in order to improve their performance. Applying the biased and unbiased MMSE metrics together with a real-valued representation of the system, the performance and complexity of a number suboptimal MIMO detectors is compared in this paper, showing how the QR decomposition-M (QRD-M) can be used to approximate ML performance with low complexity. In order to further validate those results, the QRD-M algorithm has been implemented on a field-programmable gate array (FPGA) platform, showing an excellent fixed-point performance under real-time conditions. Finally, the resulting real-time detector has been compared to state-of-the-art detectors previously implemented, in terms of complexity, error performance and throughput.

Interference alignment for peer-to-peer underlay MIMO cognitive radio network

Opportunistic interference projection (OIP) is a cognitive radio (CR) scheme thats enables secondary users to co-exist with the licensed primary users in a spectrum sharing system and thereby improving the spectrum utilization. The presence of multiple cognitive terminals offer multiuser diversity gain, which enhances the throughput performance. Interference projection techniques works well when the transmitters have perfect channel knowledge, which is quite unrealistic assumption in real-time. In this paper, we investigate the benefits of multiuser diversity and the application of limited feedback precoding schemes for CR network with a primary and multiple cognitive MIMO links. The primary receiver feedbacks the codebook index corresponding to the precoding matrix to the cognitive transmitter through a finite rate feedback. The cognitive receiver involves in the selection of the cognitive transmitter that maximizes the system throughput performance. We present numerical simulation results of the data rate achieved in both the links for various system settings.

FPGA implementation of MMSE metric based efficient near-ML detection

This paper considers a K-user multiple-input multiple-output (MIMO) interference channel in which un-coordinated interference appears. Due to the uncoordinated interference, perfect interference alignment (IA) may be not attained. In order to maximize the achievable degrees-of-freedom (DoF) per user, the interference alignment is formulated as a rank constrained rank minimization (RCRM) problem which maximizes the rank of the interference matrix while keeping a full-rank constraint on the direct signal space. Because of the non-convexity of the optimization problem, we propose a new approach to provide a tight convex approximation for the rank function, instead of using the standard nuclear norm approximation. The optimum precoders and receiver subspaces are obtained iteratively via alternating minimizing approach, with convergence guaranteed. Simulation results are presented to validate the effectiveness of the proposed algorithms.