Soheil Salari

Relay Beamforming in Cognitive Two-Way Networks with Imperfect Channel State Information

A cooperative bidirectional relaying scheme based on relay beamforming is proposed for an underlay cognitive relay network (CRN) which consists of two secondary transceivers and K cognitive relay nodes and a primary network (PN) with a transmitter and receiver, all equipped with single antenna. The result of incoordination between PN and SN is that the instantaneous channel gains of interference links between two networks are unavailable. So, it is reasonable to assume the availability of second-order statistics (SOS) of the channel coefficients between the relays and PN. Also the perfect channel state information (CSI) is assumed for SN itself. In this paper we find the beamforming coefficients based on requirements of PN or SN. To do so we propose signal-to-interference-plus-noise ratio (SINR) balancing and interference minimization approaches. Our simulation results show that the performance of the network can be degraded considerably by uncertainty about the channel coefficients.

Performance Analysis of Energy Detection-Based Spectrum Sensing over Fading Channels

The key enabling functionality of a cognitive radio is to ensure that it would not interfere with primary users, by reliably detecting primary user signals. Due to the low computational complexity, Energy detector is a widely used spectrum sensing method. The performance of energy detector in fading channels has been previously analyzed in some papers. However, these analyses are based on the exact model which makes the results computationally complex. In this paper, we propose some simple and reliable closed forms solutions for probability of detection in Nakagami fading channels. Furthermore, since cognitive users should be able to adjust the spectrum sensing time according to the desired probability of detection and tolerable probability of false alarm, a direct relationship between sensing time and SNR in terms of the aforementioned probabilities is needed. In this article, the N-SNR relationship is also calculated for Nakagami fading channels under some tolerable simplifications.

Interference minimization approach for distributed beamforming in cognitive two-way relay networks

This paper investigates the problem of interference minimization which restricts the secondary users (SUs) quality of service (QoS) while coexisting the primary users (PUs), using distributed beamforming for a bidirectional cognitive relay network. We consider a network which consists of two secondary transceivers and K cognitive relay nodes and a primary network with a transmitter and receiver, all equipped with single-antenna. For effective use of spectrum we propose a two-step two-way relaying for cognitive relay networks. Our aim is to design the beamforming coefficients for a bidirectional cognitive relay network through interference minimization approach subject to two constraints on each transceiver QoS which is solved using convex optimization. Our simulation results demonstrate that our distributed relay beamforming scheme improve network performance significantly so that the interference power is decreased by increasing the number of relay nodes while QoS of the secondary network is guaranteed.

Distributed beamforming in cognitive relay networks with partial channel state information

In this study, the authors consider the problem of distributed relay beamforming in an underlay-based cognitive relay network in which a secondary network transmits its data using multiple relays under an amplify-and-forward protocol simultaneously with a primary network over the same spectrum. For such a network, assuming that the partial channel state information (CSI) is available, the authors study two different beamforming approaches to improve performance of the secondary transmissions while ensuring the quality-of-service of the primary transmissions. In the first approach, the authors obtain the beamforming weights as well as the transmit power of the secondary source such that the signal-to-interference plus noise ratio (SINR) at the secondary destination is maximised whereas the interference power from the secondary to the primary network is kept below a predefined threshold. In the second approach, the beamforming weights are obtained through minimising the received interference power at the primary receiver subject to a constraint on SINR at the secondary destination. The authors prove that both proposed approaches result in closed-form solutions. Simulation results show that as the uncertainty in CSI decreases, the proposed schemes achieve better performances. In addition, increasing the number of relays improves the overall system performance.

Joint maximum-likelihood frequency offset and channel estimation for multiple-input multiple-output-orthogonal frequency-division multiplexing systems

The problem of joint maximum-likelihood estimation of the carrier-frequency offset (CFO) and channel coefficients in multiple-input multiple-output orthogonal frequency-division multiplexing systems is investigated, assuming that a training sequence is available. The exact solution to this problem turns out to be too complex for practical purposes. To overcome this difficulty, the authors resort to the expectation-maximisation (EM) algorithm and propose an iterative scheme which iterates between estimating the channel parameters and the frequency offset. This results in an estimation algorithm of a reasonable complexity which is suitable for practical applications. Moreover, the Cramer-Rao bounds (CRB) for both CFO and channel estimators are developed to evaluate the performance of the proposed scheme. Simulation results show that the proposed algorithm achieves almost ideal performance compared with the CRBs in all ranges of signal-to-noise ratio for both channel and frequency offset estimates.

Cluster-based cooperative spectrum sensing over correlated log-normal channels with noise uncertainty in cognitive radio networks

In this study, the authors consider the problem of cooperative spectrum sensing (CSS) based on linear combination of observations over correlated log-normal shadow-fading channels. To reduce the effects of imperfect reporting channels, a cluster-based CSS framework and a new cluster head selection algorithm are proposed. Using the received energies (as local observations) from different clusters, the fusion centre can make the final decision by linearly combining the noisy cluster observations. To calculate the combination weights, the authors come across the problem of joint distribution approximation of sum of the correlated log-normal random variables corresponding to different clusters. A joint moment generating function (MGF) matching algorithm is proposed in this study to estimate the summations by a single log-normal vector. Monte Carlo simulations confirm the accuracy of the proposed MGF-based approach in estimating the desired statistics and efficiency of the cluster-based spectrum-sensing algorithm in terms of primary signal detection.

Joint Carrier-Frequency Offset and Channel Estimation for MIMO-OFDM Transmission

In this paper, we consider a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system operating over frequency-selective fading channels. We propose a novel scheme for joint carrier-frequency offset (CFO) and channel estimation based on the expectation–maximization (EM) algorithm. Furthermore, the Cramer-Rao bounds (CRBs) for both CFO and channel estimators are exploited to evaluate the performance of the proposed scheme. Computer simulations show that the proposed algorithm achieves almost ideal performance compared with the CRBs for both channel and frequency offset estimations.

RLS-Based Estimation and Tracking of Frequency Offset and Channel Coefficients in MIMO-OFDM Systems

In this paper, we investigate the problem of carrier frequency-offset (CFO) synchronization and channel estimation in multiple-input multiple-output orthogonal frequency-division multiplexing systems operating over unknown frequency-selective fading channels. We first propose a novel joint CFO and channel estimator, assuming time-domain training blocks are available. The proposed joint estimator consists of two recursive least-square (RLS) algorithms which iterate their estimated CFO and CIR values. We then derive a more precise pilot-aided RLS algorithm to estimate the residual frequency synchronization errors or track small CFO changes. With this, the accuracy of channel estimation is also enhanced. The analysis and simulation results show that, the proposed estimation and tracking scheme which is fully compatible with the existing standards is able to attain fast convergence, high stability, and ideal performances as compared with relevant Cramer–Rao bounds in all ranges of signal-to-noise ratio. Moreover, it can work well for wide tracking range up to ±0.5 of the subcarrier spacing.

Iterative Receiver Design with Joint Carrier-Frequency Offset and Channel Estimation for LDPC-Coded MIMO-OFDM Systems

In this paper, we study the design of expectation-maximization (EM)-based iterative receivers for low-density parity check -coded multiple-input multiple-output orthogonal frequency-division multiplexing systems with the presence of carrier-frequency offset (CFO). First, starting from the maximum-likelihood principle, we devise a novel EM-based pilot-aided scheme for joint estimation of CFO and channel coefficients. Then, this estimator is incorporated into the initialization step of the iterative receiver. Simulation results show the effectiveness of our receiver design in combating CFO over unknown frequency selective fading channels.

EM-based turbo receiver design for low-density parity-check-coded MIMO-OFDM systems with carrier-frequency offset

The design of expectation-maximisation (EM)-based turbo receivers for low-density parity-check-coded multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems with the presence of carrier-frequency offset (CFO) is studied. First, starting from the maximum-likelihood principle, a novel EM-based CFO estimator for MIMO-OFDM systems is devised. This estimator iteratively provides the CFO estimate with the aid of pilot symbols. It is also capable of accommodating any space-time-coded-OFDM transmission. Then this CFO estimator is incorporated into the initialisation step of the turbo receiver. Simulation results show the effectiveness of the receiver design in combating CFO over unknown frequency-selective fading channels.