Hadi Saki

Cross-Layer Resource Allocation for Video Streaming Over OFDMA Cognitive Radio Networks

In this paper, a cross-layer resource allocation algorithm is proposed in the context of orthogonal frequency division multiple access (OFDMA)-based cognitive radio (CR) video application systems. User video quality and channel awareness are incorporated in the design, towards an optimal subcarrier and power allocation scheme, subject to minimum secondary receiver (SRx) video quality and primary receiver (PRx) interference threshold constraints. First, the relationship between PRx interference margin and power limits at the secondary transmitter (STx) is analytically derived. Then, to provide PRx with satisfactory quality of service (QoS), we propose a new probabilistic approach to mitigate the total imposed interference of the STx on PRx, considering imperfect STx to PRx channel state information (CSI). The effect of PRx interference limit violation probability, interference threshold, and error variance of imperfect CSI are evaluated through mathematical analysis and computer simulations. Results indicate that significant improvement in SRx total video quality is achieved through our proposed quality-aware (QA) algorithm over other state-of-the-art non-quality-aware (NQA) designs in the literature. The enhanced performance was obtained whilst guaranteeing SRx minimum quality and PRx prescribed QoS constraints.

Multi-user scalable video transmission over cognitive radio networks

We propose an optimal radio resource allocation (RRA) scheme for scalable H.264/SVC multi-user video transmission over downlink orthogonal frequency division multiple Access (OFDMA)-based cognitive radio (CR) networks. Our framework adopts a new probabilistic approach to mitigate the total imposed interference by cognitive users on the licensed spectrum. We consider two fundamental network service objectives, i.e., the number of satisfied users and the video quality. We devise the 3-dimensional scalable quality of the H.264/SVC video transmission for an OFDMA-based CR network and develop efficient suboptimal algorithms to solve the probabilistic constrained mixed discrete-continuous non-linear programming (MDCNLP) problem. Simulation results indicate that the proposed quality-aware scheme can achieve up to 1.3 dB increase in the average peak signal-to-noise ratio (PSNR) per user over the conventional non-quality-aware RRA algorithms.

Cross-layer resource allocation for video streaming over OFDMA cognitive radio networks with imperfect cross-link CSI

In this paper, novel cross-layer radio resource allocation (RRA) algorithm is proposed in the context of Orthogonal frequency division multiple access (OFDMA)-based cognitive radio (CR) video application systems. User video quality and channel awareness are incorporated in the design, to exploit joint optimization of rate and power for secondary receivers (SRs), subject to minimum SR video quality and primary receiver (PR) interference threshold constraints. Firstly, the relationship between PR interference margin and power limits at the secondary transmitter (ST) is analytically derived. Then, to provide PRs with satisfactory quality of service (QoS), we propose a new probabilistic approach to mitigate the total imposed interference of the ST on PRs, considering imperfect ST to PR channel state information (CSI). The effect of PR interference limit violation probability, interference threshold, and error variance of imperfect CSI are evaluated using computer simulations. Results indicate that significant improvement in SR total video quality is achieved through our proposed algorithm over other state-of-the-art Non-Quality-Aware (NQA) designs in the literature. The enhanced performance was obtained whilst guaranteeing SR minimum quality and PR prescribed QoS constraints.

Stochastic resource allocation for hybrid spectrum access OFDMA-based cognitive radios

A stochastic radio resource allocation (RRA) algorithm is designed to maximize the total transmission rate of orthogonal frequency-division multiple access (OFDMA) cognitive radios (CRs) with hybrid (i.e., joint underlay and overlay) spectrum access strategy. Our novel solution incorporates the probabilities of channel availability obtained through spectrum sensing for allocating power and subcarrier in a multi-user multi-band environment. In order to protect the licensed users from harmful intervention under imperfect sensing information, stochastic transmit and interference power constraints are imposed on the CRs. The performance of the proposed RRA algorithm and advantages over the conventional hard-decision-based approaches are demonstrated via simulation.

Active queue management for congestion avoidance in multimedia streaming

Reducing the queue length and queuing delay in the buffer which in turn reduces congestion and latency in the network are of great importance for real-time video services. This paper proposes a congestion avoidance active queue management, tailored for scalable video coding (SVC). This distortion-constrained (DC) queue management mechanism maximally decreases the queue length and queuing delay of video traffic for a given maximum allowable distortion in each video. DC prioritizes video layers in accordance with their hierarchical layer structure into multiple virtual queues inside the buffer. Losses in different layers of the hierarchy introduce different amounts of reduction in PSNR. Therefore, we determine the optimal drop rate in each virtual queue which causes minimal distortion to the stream while achieving a maximal drop rate. This in turn produces the highest reduction in the average buffer queue length and queuing delay for a given distortion. Compared with the widely deployed tail drop mechanism, our proposed scheme would increase the fraction of QoS-satisfied users and maintain a considerably shorter queue length in the buffer which would combat congestion and decrease queuing delay.

Adaptive modulation and coding and cooperative ARQ in a cognitive radio system

In this paper, a joint cross-layer design of adaptive modulation and coding (AMC) and cooperative automatic repeat request (C-ARQ) scheme is proposed for a secondary user in a shared-spectrum environment. First, based on the statistical descriptions of the channel, closed-form expressions of the average spectral efficiency (SE) and the average packet loss rate (PLR) are presented. Then, the cross-layer scheme is designed, with the aim of maximizing the average SE while maintaining the average PLR under a prescribed level. An optimization problem is formed, and a sub-optimal solution is found: the target packet error rates (PER) for the secondary system channels are obtained and the corresponding sub-optimal AMC rate adaptation policy is derived based on the target PERs. Finally, the average SE and the average PLR performance of the proposed scheme are presented.

Spectral efficiency of multi-user adaptive cognitive radio networks

In this correspondence, the comprehensive problem of joint power, rate, and subcarrier allocation have been investigated for enhancing the spectral efficiency of multi-user orthogonal frequency-division multiple access (OFDMA) cognitive radio (CR) networks subject to satisfying total average transmission power and aggregate interference constraints. We propose novel optimal radio resource allocation (RRA) algorithms under different scenarios with deterministic and probabilistic interference violation limits based on perfect and imperfect availability of cross-link channel state information (CSI). In particular, we propose a probabilistic approach to mitigate the total imposed interference on the primary service under imperfect cross-link CSI. A close form mathematical formulation of the cumulative density function (cdf) for the received signal-to-interference-plus-noise ratio (SINR) is formulated to evaluate the resultant average spectral efficiency (ASE). Dual decomposition is utilized to obtain sub-optimal solutions for the non-convex optimization problems. Through simulation results, we investigate the achievable performance and the impact of parameters uncertainty on the overall system performance. Furthermore, we present that the developed RRA algorithms can considerably improve the cognitive performance whilst abiding to the imposed power constraints. In particular, the performance under imperfect crosslink CSI knowledge for the proposed ‘probabilistic case’ is compared over the conventional scenarios to show the potential gain in employing this scheme.

Cross-layer radio resource allocation for multi-service networks of heterogeneous traffic

A cross-layer design framework, in the sense of maximizing sum-throughput, is proposed for a multi-service network of heterogeneous traffic. Considering different prescribed target packet loss rates and maximum automatic repeat request (ARQ) delays for the services in the data link control (DLC)-layer, we derive the respective optimum signal-to-interference-plus-noise ratio (SINR)-targets and variable spreading factor (VSF)s of the services in the physical (PHY)-layer, analytically as functions of the multi-user interference (MUI) and fading fluctuations. A multi-dimensional Markov chain is employed to model the packet traffic characteristics in the network. Performance of the proposed optimized cross-layer system is demonstrated and compared to state-of-the-art universal mobile telecommunication system (UMTS) standard, with conventional power, rate, and error control, for various practical system settings using theoretical and simulation results. Considerable improvement in sum-throughput performance of the multi-service mobile communication network is achieved through joint optimization of PHY-layer and DLC-layer parameters, whilst satisfying unique quality of service (QoS) constraints of different traffic types.