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 $\mathcal{NP}$ -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.

/pdf/interference-alignment-with-frequency-clustering-for-1vb9toe82p.pdf

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

Underwater acoustic (UWA) channel is characterized as a severe multipath propagation channel due to signal reflections from the surface and bottom of the sea, that is affected by a variety of ambient noise profiles unique to underwater environment. Further the motion of water introduces a Doppler. Multicarrier modulation schemes can be adapted to meet a given Quality of service (QoS) in such environments. In this paper the underwater acoustic channel is modelled using the Thorp and Ainslie-McColm models for absorption and their limitations are analyzed. Signal to noise ratio (SNR) profiles at various distances employing Discrete Multitone Modulation (DMT) are obtained considering different types of ambient noise sources such as shipping, wind, thermal, bubble and turbulence. To meet the QoS different Rate Adaptive and Margin Adaptive Tone loading algorithms are simulated and compared based on system margin, utilizing these SNR profiles.

Discrete multi-tone loading algorithms for underwater acoustic communication

Underwater acoustic (UWA) channel is characterized as a severe multipath propagation channel due to signal reflections from the surface and bottom of the sea, that is affected by a variety of ambient noise profiles unique to underwater environment. Further the motion of water introduces a Doppler. Multicarrier modulation schemes can be adapted to meet a given Quality of service (QOS) in such environments. In this paper the underwater acoustic channel is studied using the Thorp and Ainslie-McColm models for absorption and their limitations are analyzed. Signal to noise ratio (SNR) profiles at various distances employing Discrete Multitone Modulation are obtained considering different types of ambient noise sources such as shipping, wind, thermal, bubble and turbulence. To meet the QOS different Rate Adaptive and Margin Adaptive Tone loading algorithms are simulated and compared based on system margin, utilizing these SNR profiles.

Rate reach profile and tone loading algorithms for underwater acoustic communication

In this paper, we propose an adaptive multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system based on quasi-orthogonal space time/frequency block coding (QO-STBC/SFBC) with an improved angle feedback scheme. First we exploit the improved feedback scheme which can minimize the non-orthogonality of QO-STBC/SFBC by rotating constellation symbols. Then we investigate its quantification method and the related criterions. Furthermore, we apply the adaptive modulation technique to this scheme in frequency selective channel. Simulation results show that the proposed feedback scheme can provide higher signal-to-noise ratio (SNR) gains, and systems with such scheme can get significant improvement by applying adaptive modulation technique.

Adaptive MIMO-OFDM System Based on QO-STBC/SFBC with Improved Feedback Scheme

Adaptive bit and power loading algorithm with low complexity in MIMO-OFDM systems

Adaptive Power and Bit Allocation in Multicarrier Systems

A novel approach of unitarily interpolated array MVDR (UIA-MVDR) is proposed, aiming at avoiding the signal cancellation caused by broadband signal-correlated interferences. UIA-MVDR belongs to the classic approaches of spectral averaging. However, it is distinguished from the conventional interpolated array MVDR (IA-MVDR) by two points: 1) It imposes a unitary constraint on the transform matrices. 2) It only optimizes the worst-case performance of array manifold approximation. As a result, the restriction on the order of Bessel function expansion is released, so that very accurate approximation can be achieved even in the case of small or middle arrays. Compared with many related approaches, UIA-MVDR destroys the correlation more completely and then achieves better performance. Its excellent performance in both correlated and uncorrelated broadband interferences suppression is confirmed via a number of numerical examples.

On Broadband Adaptive Beamforming in the Presence of Correlated Interferences

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Papers

Adaptive bit and power loading algorithm with low complexity in MIMO-OFDM systems

Adaptive Power and Bit Allocation in Multicarrier Systems

On Broadband Adaptive Beamforming in the Presence of Correlated Interferences