Equal Rate Allocation Research Articles

Optimal inter-view rate allocation for multi-view video plus depth over MPEG-DASH using QoE measures and paired comparison

Rapid advances in compression and transmission technologies enabled multi-view video streaming over the Internet through state-of-the-art MPEG standards such as dynamic adaptive streaming over HTTP (DASH) and high-efficiency video coding. Yet, standards for subjective and objective measurement of quality of experience (QoE) are lagging in the area. The MPEG-DASH system requires constant bitrate (CBR) coding and an efficient rate control strategy in order to increase QoE. Multi-view video plus depth format is preferable due to high compression gain but quality of intermediate view is crucial, strictly depending on performance of inter/intra-view rate allocation as well as rendering algorithms. We propose to find optimal ratio for inter-view rate allocation in CBR using our previously developed objective QoE measures using depth maps and structural similarities. To assess small differences and discriminate similar quality levels, a new subjective assessment methodology is also proposed as a multiple stimuli plus simultaneous presentation for paired comparison. The results show that the unequal rate allocation is superior to the equal rate allocation in terms of objective QoE as 0.012–0.04 (which translates into a bit rate saving of 15–24%) and subjective QoE as 0.3–0.5. Furthermore, a very high correlation is achieved between the new QoE measures and paired comparison results.

A PDF/PMF Function Based Frequency Allocation Scheme in Fractional Frequency Reuse Aided OFDMA Networks

A novel frequency allocation scheme based on probability density/mass function functions (PDF/PMF) of random variables is proposed in this paper, which is capable of adjusting the balance between long term fairness and performance in fractional frequency reuse aided orthogonal frequency division multiple access based networks. This scheme divides the allocation process into two steps, including the intra-group allocation and the inter-group allocation. By adjusting the values of a set of parameters, such as rate parameters of PDF/PMF functions, and the ratio of radii of the center region and the whole cell, the presented scheme achieves a flexible adjustment between user-fairness and cell-throughput. Simulation results indicate that compared with the proportional fairness allocation and the equal rate allocation, the proposed scheme has significant performance advantage when the values of parameters are appropriate, and also has continuous controllability between "absolutely fair" and "absolutely unfair".

Delay-Constrained Shortest Paths: Approximation Algorithms and Second-Order Cone Models

Routing real-time traffic with maximum packet delay in contemporary telecommunication networks requires not only choosing a path but also reserving transmission capacity along its arcs, as the delay is a nonlinear function of both components. The problem is known to be solvable in polynomial time under quite restrictive assumptions, i.e., equal rate allocations (all arcs are reserved the same capacity) and identical reservation costs, whereas the general problem is $$\mathcal {NP}$$ NP -hard. We first extend the approaches to the equal rate allocation (ERA) version to a pseudo-polynomial Dynamic Programming one for integer arc costs and a FPTAS for the case of general arc costs. We then show that the general problem can be formulated as a mixed-integer Second-Order Cone (SOCP) program and therefore solved with off-the-shelf technology. We compare two formulations: one based on standard big-M constraints and one where Perspective Reformulation techniques are used to tighten the continuous relaxation. Extensive computational experiments on both real-world networks and randomly generated realistic ones show that the ERA approach is fast and provides an effective heuristic for the general problem whenever it manages to find a solution at all, but it fails for a significant fraction of the instances that the SOCP models can solve. We therefore propose a three-pronged approach that combines the fast running time of the ERA algorithm and the effectiveness of the SOCP models, and show that it is capable of solving realistic-sized instances with high accuracy at different levels of network load in a time compatible with real-time usage in an operating environment.

Resource Allocation in Coordinated Uplink Multicell Multicarrier Systems

We consider joint optimization of transmit power, serving base station cluster (BSC) for coherent reception, beamforming and subcarrier allocation for the uplink channel of a multicell multicarrier system. The objective is to minimize the sum transmit power subject to user-specific rate constraints. Since the problem is nonconvex and NP-hard, finding the optimal solution is challenging and not practically appealing. We propose two bit loading algorithms, in which the data rate of users is iteratively increased until the rate targets are satisfied. A joint power control, BSC selection and beamforming design problem with fixed rate allocation per subcarrier is optimally solved in every iteration. A bit switching (BSW) algorithm is further proposed in order to search for better rate allocations. The performances of the proposed algorithms are compared to upper and lower bounds achieved by the capacity-achieving scheme and equal rate allocation over subcarriers (ER), respectively. Simulation results show that proposed algorithms achieve significantly better performance than the ER scheme. The performance gains become larger as the number of users is increased.

Rate Allocation for Multipath Routing in Wireless Multihop Networks with Security Constraints Based on Erasure Channel Modeling

Multipath routing can offer various advantages for wireless multihop networks. Among those advantages, in this paper, we focus on an advantage of multipath routing for security using the notion of information-theoretic security. We formulate an optimization problem that maximizes the transmission rate from a source node to a destination node with information-theoretic security constraints to avoid eavesdropping that can be carried out at some nodes within a wireless multihop network. Binary erasure channel (BEC) modeling is employed to model wireless links that suffer from fading and interference. It is shown that the proposed throughput maximization problem is a linear optimization problem and the optimal rate allocation can be found by standard optimization techniques. We also study performance analysis including an asymptotic analysis to see whether or not multipath routing (with equal rate allocation) could be secure in terms of an information-theoretic security point of view. Through performance analysis, we can show that multipath routing can provide not only more secure routing against eavesdropping, but also a higher throughput as more multipaths are available.

Joint power rate allocation for minimum mean transmission delay in cellular CDMA downlink

An optimum power and rate allocation rule for cellular code division multiple access (CDMA) downlink networks is derived; it minimises mean transmission delay of the active users with different channel qualities under the constraints of total transmission power and the required signal-to-interference ratio. The proposed rule states that the power assigned to a user is inversely proportional to the square root of the user's channel quality factor, whereas the rate assigned to a user is proportional to the square root of the user's channel quality factor. The amount of reduction in average mean transmission delay by the proposed optimum allocation rule against the equal rate allocation with power control and the equal power allocation with rate control is also derived for the case when each user undergoes shadowing, path loss and inter-cell interference. It is shown that the proposed allocation rule not only achieves the minimum mean transmission delay, but also minimises the probability of the data rate being less than a tolerable threshold, against the equal rate or equal power allocation schemes.

Forward Error Correction-Based 2-D Layered Multiple Description Coding for Error-Resilient H.264 SVC Video Transmission

In this paper, we propose a novel 2-D layered multiple description coding (2DL-MDC) for error-resilient video transmission over unreliable networks. The proposed 2DL-MDC scheme allocates multiple description sub-bitstreams of a 2-D scalable bitstream to two network paths with unequal loss rates. We formulate the 2-D scalable rate-distortion problem and derive the expected distortion for the proposed scheme. To minimize the end-to-end distortion given the total rate budget and packet loss probabilities, we need to optimally allocate source and channel rates for each hierarchical sublayer of the scalable bitstream. The conventional Lagrangian multiplier method can be utilized to solve this problem but with overwhelming computational complexity. Therefore, we consider the use of the genetic algorithm to solve the rate-distortion optimization problem. The simulation results verify that the proposed method is able to achieve significant performance gain as opposed to the conventional equal rate allocation method.

Statistical Multimode Transmit Antenna Selection for Limited Feedback MIMO Systems

In a wireless multiple-input multiple-output (MIMO) system, transmit antenna selection is an effective means of achieving good performance with low complexity. We consider spatial multiplexing with linear receivers, and equal power and equal rate allocation over different selected transmit antennas in order to reduce feedback overhead. Under these constraints, we address the problem of statistical multimode transmit antenna subset selection to improve the capacity of spatially correlated MIMO fading channels. In particular, we first derive an analytical closed-form expression for the expectation of the lower bound on the capacity using the smallest eigenvalue distribution of a Wishart matrix. Then, we propose a transmit antenna subset selection criterion of maximizing this average lower-bound capacity.

Rate and Power Allocation for Layered Transmission With Superposition Coding

We consider layered transmission of a Gaussian source over a quasi-static fading channel. A broadcast strategy is used in which multiple layers of source data are superimposed, and each layer is allocated a different power and transmission rate. For a multiple-antenna system where either the transmitter or the receiver has a single antenna, we propose a low-complexity algorithm for minimizing the expected end-to-end distortion of the received signal. Numerical results for a Rayleigh fading channel are presented, and the performance gain over a time-sharing strategy is quantified. It is numerically shown that for a wide range of operating conditions, equal rate allocation is as good as unequal rate allocation.