Lokman Sboui

A Unified Framework for the Ergodic Capacity of Spectrum Sharing Cognitive Radio Systems

We consider a spectrum sharing communication scenario in which a primary and a secondary users are communicating, simultaneously, with their respective destinations using the same frequency carrier. Both optimal power profile and ergodic capacity are derived for fading channels, under an average transmit power and an instantaneous interference outage constraints. Unlike previous studies, we assume that the secondary user has a noisy version of the cross link and the secondary link Channel State Information (CSI). After deriving the capacity in this case, we provide an ergodic capacity generalization, through a unified expression, that encompasses several previously studied spectrum sharing settings. In addition, we provide an asymptotic capacity analysis at high and low signal-to-noise ratio (SNR). Numerical results, applied for independent Rayleigh fading channels, show that at low SNR regime, only the secondary channel estimation matters with no effect of the cross link on the capacity; whereas at high SNR regime, the capacity is rather driven by the cross link CSI. Furthermore, a practical on-off power allocation scheme is proposed and is shown, through numerical results, to achieve the full capacity at high and low SNR regimes and suboptimal rates in the medium SNR regime.

Achievable rate of cognitive radio spectrum sharing MIMO channel with space alignment and interference temperature precoding

In this paper, we investigate the spectral efficiency gain of an uplink Cognitive Radio (CR) Multi-Input Multi-Output (MIMO) system in which the Secondary/unlicensed User (SU) is allowed to share the spectrum with the Primary/licensed User (PU) using a specific precoding scheme to communicate with a common receiver. The proposed scheme exploits at the same time the free eigenmodes of the primary channel after a space alignment procedure and the interference threshold tolerated by the PU. In our work, we study the maximum achievable rate of the CR node after deriving an optimal power allocation with respect to an outage interference and an average power constraints. We, then, study a protection protocol that considers a fixed interference threshold. Applied to Rayleigh fading channels, we show, through numerical results, that our proposed scheme enhances considerably the cognitive achievable rate. For instance, in case of a perfect detection of the PU signal, after applying Successive Interference Cancellation (SIC), the CR rate remains non-zero for high Signal to Noise Ratio (SNR) which is usually impossible when we only use space alignment technique. In addition, we show that the rate gain is proportional to the allowed interference threshold by providing a fixed rate even in the high SNR range.

Achievable Rate of a Cognitive MIMO Multiple Access Channel With Multi-Secondary Users

We study the secondary sum-rate of an underlay cognitive multiple access channel consisting of a primary user and multiple secondary users (SUs) communicating with a common destination. We propose a particular linear precoding and SU selection scheme that maximize the cognitive sum-rate. This scheme is based on space alignment strategy allowing SUs to share the spectrum without interfering with each other. We derive the optimal power allocation for each selected SU after applying perfect or imperfect successive interference cancellation. Numerical results show that the proposed scheme provides a significant sum-rate improvement as the number of SUs increases. In addition, it achieves almost the same performance as an exhaustive search selection, mainly in low and high power ranges.

Achievable Rate of Spectrum Sharing Cognitive Radio Systems Over Fading Channels at Low-Power Regime

We study the achievable rate of cognitive radio (CR) spectrum sharing systems at the low-power regime for general fading channels and then for Nakagami fading. We formally define the low-power regime and present the corresponding closed-form expressions of the achievable rate lower bound under various types of interference and/or power constraints, depending on the available channel state information of the cross link (CL) between the secondary-user transmitter and the primary-user receiver. We explicitly characterize two regimes where either the interference constraint or the power constraint dictates the optimal power profile. Our framework also highlights the effects of different fading parameters on the secondary link (SL) ergodic achievable rate. We also study more realistic scenarios when there is either 1-bit quantized channel feedback from the CL alone or 2-bit feedback from both the CL and the SL and propose simple power control schemes and show that these schemes achieve the previously achieved rate at the low-power regime. Interestingly, we show that the low-power regime analysis provides a specific insight into the maximum achievable rate behavior of CR that has not been reported by previous studies.

Achievable Rate of Spectrum Sharing Cognitive Radio Multiple-Antenna Channels

We investigate the spectral efficiency gain of an uplink cognitive radio (CR) multi-input-multi-output system in which the secondary user (SU) is allowed to share the spectrum with the primary user (PU) using a specific precoding scheme to communicate with a common receiver. The proposed scheme exploits, at the same time, the free eigenmodes of the primary channel after a space alignment procedure and the interference threshold tolerated by the PU. At the common receiver, we adopt a successive interference cancellation (SIC) technique to eliminate the effect of the detected primary signal transmitted through the exploited eigenmodes. Furthermore, we analyze the SIC operation inaccuracy as well as the CSI estimation imperfection on the PU and SU throughputs. Numerical results show that our proposed scheme enhances considerably the cognitive achievable rate. For instance, in case of a perfect detection of the PU signal, the CR rate remains non-zero for high signal to noise ratio, which is usually impossible when we only employ a space alignment technique. We show that a modified water-filling power allocation policy at the PU can increase the secondary rate with a marginal degradation of the primary rate. Finally, we investigate the behavior of the PU and SU rates through the study of the rate achievable region.

Capacity of Cognitive Radio under imperfect secondary and cross link Channel State Information

In this paper, we study the ergodic capacity of secondary user channel in a spectrum sharing scenario in which the secondary transmitter is instantaneously aware of estimated versions of the cross link (between the secondary transmitter and the primary receiver) and the secondary link Channel State Information (CSI). The secondary link optimal power profile along with the ergodic capacity are derived for a class of fading channels, under an average power constraint and an instantaneous interference outage constraint. We also show that our framework is rather general as it encompasses several previously studied spectrum sharing settings as special cases. In order to gain some insights on the capacity behavior, numerical results are shown for independent Rayleigh fading channels where it is found for instance, that at low SNR regime, only the secondary channel estimation matters and that the cross link CSI has no effect on the ergodic capacity; whereas at high SNR regime, the capacity is rather driven by the cross link CSI.

Capacity of spectrum sharing Cognitive Radio systems over Nakagami fading channels at low SNR

In this paper, we study the ergodic capacity of Cognitive Radio (CR) spectrum sharing systems at low power regime. We focus on Nakagami fading channels. We formally define the low power regime and present closed form expressions of the capacity in the low power regime under various types of interference and/or power constraints, depending on the available channel state information (CSI) of the cross link (CL) between the secondary user transmitter and the primary user receiver. We explicitly characterize two regimes where either the interference constraint or the power constraint dictates the optimal power profile. Our framework also highlights the effects of different fading parameters on the secondary link ergodic capacity. Interestingly, we show that the low power regime analysis provides a specific insight on the capacity behavior of CR that has not been reported by previous studies.

Energy-Efficient Power Allocation for Underlay Cognitive Radio Systems

We present a power allocation framework for spectrum sharing cognitive radio (CR) systems based on maximizing the energy efficiency (EE). First, we show that the relation between the EE and the spectral efficiency (SE) is strictly increasing in contrast with the SE-EE tradeoff discussed in the literature. We also solve a nonconvex problem and explicitly derive the optimal power for the proposed average EE under either a peak or an average power constraint. We apply our results to the underlay CR systems where the power is limited by an additional interference constraint. When the instantaneous channel is not available, we provide a necessary and sufficient condition for the optimal power and present a simple suboptimal power. In the numerical results, we show that the proposed EE corresponds to a higher SE at midrange and high-power regime compared to the classical EE. We also show that the suboptimal solution is very close to the optimal solution. In addition, we deduce that the absence of instantaneous CSI affects the EE and the SE at high power regime compared to full CSI. In the CR context, we show that the interference threshold has a minimal effect on the EE compared to the SE.

On the throughput of a relay-assisted cognitive radio MIMO channel with space alignment

We study the achievable rate of a multiple antenna relay-assisted cognitive radio system where a secondary user (SU) aims to communicate instantaneously with the primary user (PU). A special linear precoding scheme is proposed to enable the SU to take advantage of the primary eigenmodes. The used eigenmodes are subject to an interference constraint fixed beforehand by the primary transmitter. Due to the absence of a direct link, both users exploit an amplify-and-forward relay to accomplish their transmissions to a common receiver. After decoding the PU signal, the receiver employs a successive interference cancellation (SIC) to estimate the secondary message. We derive the optimal power allocation that maximizes the achievable rate of the SU respecting interference, peak and relay power constraints. Furthermore, we analyze the SIC detection accuracy on the PU throughput. Numerical results highlight the cognitive rate gain achieved by our proposed scheme without harming the primary rate. In addition, we show that the relay has an important role in increasing or decreasing PU and SU rates especially when varying its power and/or its amplifying gain.

On energy efficient power allocation for power-constrained systems

Recently, the energy efficiency (EE) has become an important factor when designing new wireless communication systems. Due to economic and environmental challenges, new trends and efforts are oriented toward “green” communication especially for energy-constrained applications such as wireless sensors network and cognitive radio. To this end, we analyze the power allocation scheme that maximizes the EE defined as rate over the total power including circuit power. We derive an explicit expression of the optimal power with instantaneous channel gain based on EE criterion. We show that the relation between the EE and the spectral efficiency (SE) when the optimal power is adopted is strictly increasing in contrast with the SE-EE trade-off discussed in the literature. We also solve a non-convex problem and compute explicitly the optimal power for ergodic EE under either a peak or an average power constraint. When the instantaneous channel is not available, we provide the optimal power equation and compute simple sub-optimal power. In the numerical results, we show that the sup-optimal solution is very close to the optimal solution. In addition, we show that the absence of the channel state information (CSI) only affects the EE and the SE performances at high power regime compared to the full CSI case.