Adaptive hybrid ARQ for goodput optimization in BIC-OFDM systems

In next generation wireless networks, high data rates under strict quality of service (QoS) constraints call for flexible radio interfaces capable of adapting their configuration on the fly to the time-varying operating environment. Motivated by this need, this paper first derives a simple link performance prediction model for bit interleaved coded orthogonal frequency division multiplexing (BIC-OFDM) systems using incremental redundancy (IR) hybrid automatic repeat request (HARQ) mechanisms. Then, an adaptive HARQ strategy is formulated whose aim is maximizing the goodput (GP) metric, i.e., the number of error-free information bits delivered to the user by unit of time, over the coding rate, the bit distribution and an on-off power allocation across the active subchannels. Simulation results corroborate the GP performance gains of the proposed approach compared with non-adaptive transmissions, while keeping the computational complexity at affordable levels. © 2011 IEEE

A Consensus Approach for Cooperative Communications in Cognitive Radio Networks

In this paper, we investigate a decentralized power allocation (PA) algorithm, i.e., without the need of a fusion center, for a coalition of bit-interleaved coded (BIC) OFDM-based cognitive radio (CR) devices. Taking advantages of a game theoretical description for our problem, it is shown that the reliability of the secondary cooperative link can be remarkably improved through a simple average consensus algorithm keeping the interference produced to the primary users (PUs) under a prescribed threshold. Finally, the performance gain of the proposed PA policy is highlighted comparing it with conventional power allocation algorithms

Packet Transmissions in Cognitive Radio Networks: How to Cheaply Get Efficiency and Reliability

The ever growing demand for wireless multimedia applications and services occurred in the last years has spurred the research community to tackle several demanding technical challenges. Advanced next-generation wireless systems solicit the designer to solve a hard multi-facet severely constrained problem, that is to say, providing very high data rates under strict quality of service (QoS) levels, while at the same time facing the lack of wide available segments in the overcrowded electromagnetic spectrum

Trading-off Troughput vs. Energy in Adaptive BIC-OFDM over Nonlinear Channels: a Novel Approach

This paper presents an accurate tool yielding a reliable prediction of the link quality for the down-link of a BIC- OFDM system featuring bandlimited pulse shaping to control spectral sidelobe emission, plus AMC, and operating over a nonlinear channel. The tool enables an effective design of the communication system, with special respect to the setting of the operating point of the transmitter’s power amplifier. First, an analytical characterization of the nonlinear distortion effects caused by the amplifier on bandlimited BIC-OFDM signals is carried out by resorting to the extended version of the Bussgang theorem. Then, after a survey of some link quality prediction methods, the equivalent additive noise model provided by the Bussgang-based analysis is taken into account in the derivation of a novel method, named BESM. Finally, the novel BESM tool is employed in the link design phase for choosing the best amplifier setting, aimed at maximizing the layer-3 offered traffic over a realistic wireless channel, featuring both multipath propagation and nonlinear distortions

A Game Theoretical Approach for Coded Cooperation in Cognitive Radio Networks

In this paper, the authors focus on a game theoretical approach for cooperation in cognitive radio (CR) networks. In particular, an integrated design framework which relies on the effective SNR methodology is proposed. The authors derive a distributed power allocation policy aimed at maximizing the reliability of a cooperative BIC OFDM link wherein pragmatic modulation and coding schemes are considered. More in detail, the cognitive devices adapt their power to enable efficient cooperation and coexistence between cognitive nodes and primary networks. First of all, the gain due to the cooperation protocol is analytically derived, resorting to a simple first order recursive equation that depends on the current channel conditions. Then, after an accurate formalization of the optimization problem, a distributed iterative solution based on a novel algorithm, named Successive Set Reduction, is proposed. In particular, the authors show that : i) the proposed power allocation policy takes into account the cooperative gain through a simple scalar value, named cooperative effective SNR; ii) it is effective in improving the packet error rate performance with respect to other conventional power allocation strategies, thus allowing a better coverage for the secondary network; iii) the convergence of the distributed algorithm has exponential speed and requires only local signaling between secondary users

Resource Allocation in OFDMA Underlay Cognitive Radio Systems Based on Ant Colony Optimization

This work deals with dynamic resource allocation problem for OFDMA-based cognitive radio systems. The proposed solution is specifically tailored for a secondary base stations transmitting to secondary users (SUs) over the same bands of the licensed primary users (PUs) in underlay fashion. The downlink transmission goodput is thereby maximized while keeping the interference on the PUs within a tolerable range. The NP-hard goodput maximization problem is tackled resorting to an efficient meta-heuristic algorithm based on Ant Colony Optimization framework

Optimal and Sub-optimal Power Allocation Algorithms for Goodput Optimization in Cognitive Multi-channel Wireless Systems

This paper studies the power allocation problem for a cognitive wireless system transmitting over multiple parallel channels. The goal of the power allocation is to maximize the total system goodput, or, the offered layer 3 data rate, keeping at the same time the interference caused to the licensed users, which transmit over the same bands of the cognitive device, under the prescribed threshold. This optimization problem results to be convex and then solvable with conventional numerical methods. Due to the high computational time required by these meth- ods, a sub-optimal approach is also proposed, offering a good trade-off between quality of solution and speed of the algorithm

Resource Allocation in OFDMA Underlay Cognitive Radio Systems Based on Ant Colony Optimization

This paper presents a novel technique for cross-layer adaptive modulation and coding, suited for bit interleaved turbo-coded OFDM packet transmission, and aimed at maximizing the goodput (i.e., the number of data bits delivered without error per unit of time). The optimization problem is formalized through an accurate modeling on the link performance, and a greedy iterative solution is derived. Simulation results demonstrate that performance improvement provided by the proposed method amount to 4 dB with respect to static transmission and about 1.2 dB with respect to adaptive transmission with uniform bit allocation

A Greedy Algorithm for Goodput-Oriented AMC in Turbo-Coded OFDM

This paper presents a novel technique for cross-layer adaptive modulation and coding, suited for bit interleaved turbo-coded OFDM packet transmission, and aimed at maximizing the goodput (i.e., the number of data bits delivered without error per unit of time). The optimization problem is formalized through an accurate modeling on the link performance, and a greedy iterative solution is derived. Simulation results demonstrate that performance improvement provided by the proposed method amount to 4 dB with respect to static transmission and about 1.2 dB with respect to adaptive transmission with uniform bit allocation

A game theoretical approach for reliable packet transmission in noncooperative BIC-OFDM systems

In this work, we investigate the power allocation (PA) problem aimed at minimizing the users' packet error rate (PER) over a noncooperative link, i.e., a link where the set of users, employing packet-oriented bit-interleaved coded (BIC) orthogonal frequency division multiplexing (OFDM) systems, compete for the same bandwidth. For these kind of systems, the PER is not available in closed-form, but a very efficient solution is offered by the effective SNR mapping (ESM) technique. This method allows each user to evaluate a single scalar value, the effective SNR (ESNR), accounting for all the SNIRs experienced over the active subcarriers, and to univocally map it into a PER value. Thus, in order to derive a decentralized strategy allowing each user to minimize its own PER, the problem is described as a strategic game, called min-PER game, with the set of player, utilities and strategies represented by the competitive users, the ESNRs and the set of feasible power allocations, respectively. We will show both the existence of at least one Nash Equilibrium (NE) for the min-PER game and its equivalence with a Nonlinear Variational Inequality (NVI) problem. Finally, relying on the theory of contraction mappings, we will derive a distributed algorithm to reach the NE of the game