Cross-layer Adaptive Transmission Research Articles

Adaptive congestion control scheme in mobile ad-hoc networks

In the past, several authors have expressed their concerns over the poor congestion control in mobile wireless ad-hoc networks using traditional reference layer model. Many solutions were proposed to handle growing traffic and congestion in the network, using link layer information. Existing solutions have shown difficulties in dealing with congestion with varying packets drop. Moreover, ensuring the superior performance of congestion control schemes with traditional referenced layer model is a challenging issue, due to quick topology changes, dynamic wireless channel characteristics, link-layer contentions, etc. In this paper, we propose an effective cross-layer adaptive transmission method to handle the congestion in mobile wireless ad-hoc networks adequately. Simulation results exemplify the usefulness of the proposed method in handling congestion, and yields better results compared to existing approaches.

Cross-layer adaptive transmission with incomplete system state information

We consider a point-to-point communication system in which data packets randomly arrive to a finite-length buffer and are subsequently transmitted to a receiver over a time-varying wireless channel. Data packets are subject to loss due to buffer overflow and transmission errors. We study the problem of adapting the transmit power and rate based on the buffer and channel conditions so that the system throughput is maximized, subject to an average transmit power constraint. Here, the system throughput is defined as the rate at which packets are successfully transmitted to the receiver. We consider this buffer/channel adaptive transmission when only incomplete system state information is available for making control decisions. Incomplete system state information includes delayed and/or imperfectly estimated channel gain and quantized buffer occupancy. We show that, when some delayed but error-free channel state information is available, optimal buffer/channel adaptive transmission policies can be obtained using Markov decision theory. When the channel state information is subject to errors and when the buffer occupancy is quantized, we discuss various buffer/channel adaptive heuristics that achieve good performance. In this paper, we also consider the tradeoff between packet loss due to buffer overflow and packet loss due to transmission errors. We show by simulation that exploiting this tradeoff leads to a significant gain in the system throughput.

Cross-layer Adaptive Transmission: Optimal Strategies in Fading Channels

We consider cross-layer adaptive transmission for a single-user system with stochastic data traffic and a time- varying wireless channel. The objective is to vary the transmit power and rate according to the buffer and channel conditions so that the system throughput, defined as the long-term average rate of successful data transmission, is maximized, subject to an average transmit power constraint. When adaptation is subject to a fixed bit error rate (BER) requirement, maximizing the system throughput is equivalent to minimizing packet loss due to buffer overflow. When the BER requirement is relaxed, maximizing the system throughput is equivalent to minimizing total packet loss due to buffer overflow and transmission errors. In both cases, we obtain optimal transmission policies through dynamic programming. We identify an interesting structural property of these optimal policies, i.e., for certain correlated fading channel models, the optimal transmit power and rate can increase when the channel gain decreases toward outage. This is in sharp contrast to the water-filling structure of policies that maximize the rate of transmission over fading channels. Numerical results are provided to support the theoretical development.

A cross-layer adaptive transmission scheme combined with SR-ARQ over correlated fading channels

Current adaptive transmission schemes all assume independent block fading. However, in slow fading channels, it is highly possible for consecutive block transmissions to be correlated. In this paper, we propose a cross-layer adaptive transmission scheme, which is an optimum combination of modulation format and packet size, combined with selective repeat automatic repeat request (SR-ARQ) to improve the throughput in correlated slow fading channels. We apply a multi-state Markov system model to analyze the system performance and to optimize the selection of modulation levels at the physical layer and packet sizes at the data link layer in a correlated slow fading channel, which is also described by a finite-state Markov chain. A general closed-form expression of the average throughput for this cross-layer adaptive transmission scheme is presented. Simulation results show that our adaptive transmission scheme combined with SR-ARQ can obtain a good performance in correlated slow fading channels.

A cross-layer adaptive transmission scheme over correlated fading channels

Conventional adaptive transmission schemes perform poorly in wireless correlated slow-fading channels. A cross-layer adaptive transmission scheme combined with selective repeat automatic repeat request (SR-ARQ) is proposed. We apply a multi-state Markov system model for analyzing the performance of systems and optimizing the selection of modulation levels and packet sizes in correlated fading channels, which is also described by a finite-state Markov chain. A general closed-form expression of the average throughput for our suggested scheme is presented. Numerical results show that our adaptive scheme combined with SR-ARQ can obtain good performance in correlated fading channels.