Musbah Shaat

Computationally efficient power allocation algorithm in multicarrier-based cognitive radio networks: OFDM and FBMC systems

Cognitive Radio (CR) systems have been proposed to increase the spectrum utilization by opportunistically access the unused spectrum. Multicarrier communication systems are promising candidates for CR systems. Due to its high spectral efficiency, filter bank multicarrier (FBMC) can be considered as an alternative to conventional orthogonal frequency division multiplexing (OFDM) for transmission over the CR networks. This paper addresses the problem of resource allocation in multicarrier-based CR networks. The objective is to maximize the downlink capacity of the network under both total power and interference introduced to the primary users (PUs) constraints. The optimal solution has high computational complexity which makes it unsuitable for practical applications and hence a low complexity suboptimal solution is proposed. The proposed algorithm utilizes the spectrum holes in PUs bands as well as active PU bands. The performance of the proposed algorithm is investigated for OFDM and FBMC based CR systems. Simulation results illustrate that the proposed resource allocation algorithm with low computational complexity achieves near optimal performance and proves the efficiency of using FBMC in CR context.

Asymptotically Optimal Resource Allocation in OFDM-Based Cognitive Networks with Multiple Relays

In this letter, the problem of resources allocation in decode-and-forward (DF) relayed OFDM based cognitive system is considered. The dual decomposition technique is adopted to obtain an asymptotically optimal subcarrier pairing, relay selection, and power allocation. The resources are optimized under the individual power constraints in source and relays so that the sum rate is maximized while the interference induced to the primary system is kept below a pre-specified interference temperature limit. Moreover, a sub-optimal scheme is presented to avoid the high computational complexity of the optimal scheme. The sub-optimal algorithm allocates jointly the different resources taking into account the channel qualities, the DF-relaying strategy, the interference induced to the primary system, and the individual power budgets. The performance of the different schemes and the impact of the constraints values are discussed through the numerical simulation results.

A Two-Step Resource Allocation Algorithm in Multicarrier Based Cognitive Radio Systems

This paper presents a two-step downlink resource allocation algorithm for multicarrier based cognitive radio systems. The algorithm allocates the subcarriers to the users in the first step. In the second step, the power is allocated to these subcarriers in order to maximize the downlink capacity of the system without causing excessive interference to the primary user. The performance of the proposed algorithm is investigated using computer simulations to prove that it achieves near optimal performance and it is better than other existing algorithms. Moreover, the throughput of Orthogonal frequency division multiplexing (OFDM) and filter bank multicarrier system (FBMC) based cognitive radio systems are compared to show the efficiency of using FBMC in future cognitive radio systems.

Spectrum sensing and resource allocation for multicarrier cognitive radio systems under interference and power constraints

Multicarrier waveforms have been commonly recognized as strong candidates for cognitive radio. In this paper, we study the dynamics of spectrum sensing and spectrum allocation functions in cognitive radio context using very practical signal models for the primary users (PUs), including the effects of power amplifier nonlinearities. We start by sensing the spectrum with energy detection-based wideband multichannel spectrum sensing algorithm and continue by investigating optimal resource allocation methods. Along the way, we examine the effects of spectral regrowth due to the inevitable power amplifier nonlinearities of the PU transmitters. The signal model includes frequency selective block-fading channel models for both secondary and primary transmissions. Filter bank-based wideband spectrum sensing techniques are applied for detecting spectral holes and filter bank-based multicarrier (FBMC) modulation is selected for transmission as an alternative multicarrier waveform to avoid the disadvantage of limited spectral containment of orthogonal frequency-division multiplexing (OFDM)-based multicarrier systems. The optimization technique used for the resource allocation approach considered in this study utilizes the information obtained through spectrum sensing and knowledge of spectrum leakage effects of the underlying waveforms, including a practical power amplifier model for the PU transmitter. This study utilizes a computationally efficient algorithm to maximize the SU link capacity with power and interference constraints. It is seen that the SU transmission capacity depends critically on the spectral containment of the PU waveform, and these effects are quantified in a case study using an 802.11-g WLAN scenario.

Low complexity power loading scheme in cognitive radio networks: FBMC capability

Quick development of wireless communication makes the spectrum scarcity as a one of the serious problems. Cognitive radio (CR) is considered to be one of the possible solutions to solve the spectrum efficiency problem. Multicarrier communications are considered to be used in CR networks. Due to its high spectral efficiency, filter bank multicarrier (FBMC) can be considered as an alternative to conventional orthogonal frequency division multiplexing (OFDM) for transmission over the CR networks. This paper addresses the problem of resource allocation in multicarrier based CR networks. The objective is to maximize the downlink capacity of the network under both total power and interference introduced to the primary users (PUs) constraints. The optimal solution has high computational complexity which makes it unsuitable for practical applications and hence a low complexity suboptimal solution is proposed. The performance of using FBMC instead of OFDM in CR systems is investigated. Simulation results illustrate that the proposed resource allocation algorithm with low computational complexity achieves near optimal performance and prove the efficiency of using FBMC in CR context.

Comparison of OFDM and FBMC performance in multi-relay cognitive radio network

A multicarrier based cognitive radio (CR) network is considered in this paper. The goal is to maximize the total sum rate of the CR system while ensuring that no excessive interference is induced to the primary system. The optimal scheme adopts the dual decomposition technique and in order to reduce the computational complexity of the optimal scheme, a greedy suboptimal algorithm is proposed. Selected numerical results is discussed to reveal the near-optimal performance of the suboptimal scheme and the superiority of the proposed algorithm over the random and the signal-to-noise ratio (SNR) based schemes. This paper highlights the advantages of using filter bank multicarrier (FBMC) instead of OFDM in the physical layer of the future CR systems.

Interference alignment with frequency-clustering for efficient resource allocation in cognitive radio networks

In this paper, we investigate the resource management problem in orthogonal frequency division multiplexing (OFDM) based multiple-input multiple-output (MIMO) cognitive radio (CR) systems. We propose performing resource allocation based on interference alignment (IA) in order to improve the spectral efficiency of CR systems without affecting the quality of service of the primary system. IA plays a role in the proposed algorithm to enable the secondary users (SUs) to cooperate and share the available spectrum, which leads to a considerable increase in the spectral efficiency of CR systems. However, IA based spectrum sharing is restricted to a certain number of SUs per subcarrier in order to satisfy the IA feasibility conditions. Accordingly, the resource allocation problem is formulated as a mixed-integer optimization problem, which is considered an

Pilot Pattern Adaptation and Channel Estimation in MIMO WiMAX-like FBMC System

\mathcal{NP}

An uplink resource allocation algorithm for OFDM and FBMC based cognitive radio systems

-hard problem. To reduce the computational complexity of the problem, a two-phases efficient sub-optimal algorithm is proposed. In the first phase, frequency-clustering is performed in order to satisfy the IA feasibility conditions, where each subcarrier is assigned to a feasible number of SUs. Whenever possible, frequency-clustering stage considers the fairness among the SUs. In the second stage, the available power is allocated among the subcarriers and SUs without violating the constraints that limit the maximum interference induced to the primary system. Simulation results show that IA with frequency-clustering achieves a significant sum rate increase compared to CR systems with orthogonal multiple access transmission techniques.

Optimal Power Allocation Algorithm for OFDM-Based Decode-and-Forward Dual-Hop Cognitive Systems

In this paper we analyzed possibilities to adapt the DL-PUSC pilot grid in filters bank based multicarrier (FBMC) system. We showed that by applying certain designed pilot patterns especially for FBMC, the BER can outperforms in certain cases that achieved in conventional CP-OFDM system. The performance evaluations are done in hypothetical WiMAX scenario on which the FBMC system will substitute the CP-OFDM by maintaining as much as possible the physical layer compatibilities.