Specific Rate Constraints Research Articles

Decentralizing Multicell Beamforming via Deterministic Equivalents

This paper focuses on developing a decentralized framework for coordinated minimum power beamforming wherein $L$ base stations (BSs), each equipped with $N$ antennas, serve $K$ single-antenna users with specific rate constraints. This is realized by considering user specific intercell interference (ICI) strength as the principal coupling parameter among BSs. First, explicit deterministic expressions for transmit powers are derived for spatially correlated channels in the asymptotic regime in which $N$ and $K$ grow large with a non-trivial ratio $K/N$ . These asymptotic expressions are then used to compute approximations of the optimal ICI values that depend only on the channel statistics. By relying on the approximate ICI values as coordination parameters, a distributed non-iterative coordination algorithm, suitable for large networks with limited backhaul, is proposed. A heuristic algorithm is also proposed relaxing coordination requirements even further as it only needs pathloss values for non-local channels. The proposed algorithms satisfy the target rates for all users even when $N$ and $K$ are relatively small. Finally, the potential benefits of grouping users with similar statistics are investigated to further reduce the overhead and computational effort of the proposed solutions. Simulation results show that the proposed methods yield near-optimal performance.

Energy‐efficient precoding design for cloud radio access networks

In cloud radio access network, a baseband unit (BBU) performs the baseband processing for a cluster of low-power low-cost remote radio heads (RRHs) that are connected to the BBU through low-latency fronthaul links. In this study, the authors study the optimisation of two energy-efficient compression and precoding strategies which take transmit power constraint, fronthaul capacity constraint and user specific rate constraint into account. To overcome the non-convexity nature of the original problem, they first transform the objective of the original problem into a parameterised subtractive form and obtain an approximate convex problem via the successive convex approximation. Then, an effective optimisation algorithm with provable convergence is designed to solve the effective problem. Numerical results reveal that the proposed scheme outperforms the conventional maximum sum rate and minimum total power consumption schemes in terms of the energy-efficiency criterion. In particular, compression after precoding strategy outperforms compression before precoding strategy when both of their RRHs perform the same user scheduling, while the opposite conclusion can be drawn otherwise.

Bandwidth Allocation for Multimedia Applications at Mobile Stations

A user in B3G (Beyond 3rd Generation) mobile communications systems may choose to simultaneously launch various multimedia applications. In this letter, we suggest that the mobile station (MS) shares its available resources among the user's applications, based on her/his preferences and the applications' quality of service (QoS) requirements. A utility maximiztion problem is formulated. From the formulated optimization problem, and using Karush-Kuhn-Tucker (KKT) conditions, we derive an optimum scheme to perform this task at the MS. The scheme maximizes user satisfaction under application- specific rate constraints, and is applicable to both downlink and uplink.