Optimal Rate Adaptation Research Articles

Performance Evaluation of Generalized Selection Combiners Over Slow Fading with Estimation Errors

In this paper we derive closed-form expressions for the single-user adaptive capacity of generalized selection combining (GSC) system, taking into account the effect of imperfect channel estimation at the receiver. The channel considered is a slowly varying spatially independent flat Rayleigh fading channel. The complex channel estimate and the actual channel are modelled as jointly Gaussian random variables with a correlation that depends on the estimation quality. Three adaptive transmission schemes are analyzed: (1) optimal power and rate adaptation; and (2) constant power with optimal rate adaptation, and (3) channel inversion with fixed rate. In addition to deriving an exact expression for the capacity of the aforementioned adaptive schemes, we analyze the impact of channel estimation error on the capacity statistics and the symbol error rate for GSC systems. The capacity statistics derived in this paper are the moment generating function, complementary cumulative distribution function and probability density function for arbitrary number of receive antennas. Moreover, exact closed-form expressions for M-PAM/PSK/QAM employing GSC are derived. As expected, the channel estimation error has a significant impact on the system performance.

Capacity of Orthogonalized Weibull MIMO Channels Under Different Adaptive Transmission Techniques

Space-time block codes (STBCs) are known to orthogonalize the multiple input multiple out (MIMO) wireless channels. In this paper, we study the capacity of STBCs over Weibull MIMO channels under three adaptive transmission techniques: optimal power and rate adaptation, optimal rate adaptation with constant transmit power and channel inversion with fixed rate, and obtain closed-form expressions for the corresponding capacity. This capacity provides an upper bound on spectral efficiency using these techniques and avoids Monte Carlo simulations. Moreover, we also examine the effects of the fading severity on the concerned quantities. The figures show that our theoretical results of channel capacity line up exactly with the simulations.

Is rate adaptation beneficial for inter-session network coding?

This paper considers the interplay between rate adaptation and inter-session network coding gains in wireless mesh or ad hoc networks. Inter-session network coding opportunities at relay nodes depend on packets being overheard by surrounding nodes ? The more packets nodes overhear, the more opportunities relays have to combine packets, resulting in a potential increase in network throughput. Thus, by adapting its transmission rate, a node can increase the range over which its packets are overheard, enabling additional opportunities for coding and increased overall throughput. This paper considers inter-session coding, restricted to a single relay (bottleneck) node, or star network topology. Even for such simple topologies the optimal joint rate adaptation and network coding policy is known to be NP-hard. Optimal rate vector selection is a combinatorial optimization problem, which is NP-hard, and finding optimal coding scheme turns out to be a clique partitioning problem which is also NP-hard. So, we provide heuristics to find a suboptimal rate vector and coding scheme. Additionally, we provide a linear programming formulation for network coding when only pairwise intersession coding is allowed. We evaluate the averaged throughput in two different scenarios, in which relays have different access opportunities, giving some intuition on the impact of rate adaptation in lightly and heavily loaded systems. The gains of joint rate adaptation and network coding are marginal when the relay has a higher access opportunity than other nodes, or when the MAC operates ideally it ranges from 9% to 19% as compared to a network without network coding and 4% over a network using regular network coding. While, when the relay has equal access opportunity as other source nodes, which is more typical of todays MAC protocols under heavy loads, the gain ranges from 40% to 62% as compared to the standard relaying case and is upto around 20% as compared to a network with regular pairwise network coding. This can further be increased to a gain of 40% to 120% by replacing pairwise coding with sub-optimal general network coding scheme.

Spectral efficiency of maximum ratio combining (MRC) over slow fading with estimation errors

In this paper, we derive closed-form expressions for capacity statistics of the maximal ratio combining (MRC) system, taking into account the effect of imperfect channel estimation at the receiver. The channel considered is a slowly varying flat Rayleigh fading that is also spatially independent. The combiner weights are assumed to be affected by Gaussian errors at the receiver. In particular, we derive the moment generating function (MGF), complementary cumulative distribution function (CDF) and the probability density function (PDF) of the capacity. Furthermore, we derive closed-form expressions for the system capacity when employing different adaptive transmission schemes such as (1) optimal power and rate adaptation (opra); (2) constant power with optimal rate adaptation (ora); and (3) channel inversion with fixed rate (cifr). Analytical results show accurately the impact of the channel estimation error on the achievable spectral efficiency.

On the capacity of Rayleigh fading cooperative systems under adaptive transmission

In this letter, the use of adaptive source transmission with amplify-and-forward relaying is proposed. Three different adaptive techniques are considered: (i) optimal simultaneous power and rate adaptation; (ii) constant power with optimal rate adaptation; (iii) channel inversion with fixed rate. The capacity upper bounds of these adaptive protocols are derived for the amplify-and-forward cooperative system over both independent and identically distributed (i.i.d.) Rayleigh fading and non-i.i.d. Rayleigh fading environments. The capacity analysis is based on an upper bound on the effective received signal-to-noise ratio (SNR). The tightness of the upper bound is validated by the use of a lower bound and by Monte Carlo simulation. It is shown that at high SNR the optimal simultaneous power and rate adaptation and the optimal rate adaptation with constant power provide roughly the same capacity. Channel inversion is shown to suffer from a deterioration in capacity relative to the other adaptive techniques.

On the performance analysis of composite multipath/shadowing channels using the G-distribution

Composite multipath fading/shadowing environments are frequently encountered in different realistic scenarios. These channels are generally modeled as a mixture of Nakagami-m multipath fading and log-normal shadowing. The resulting composite probability density function (pdf) is not available in closed form, thereby making the performance evaluation of communication links in these channels cumbersome. In this paper, we propose to model composite channels by the G-distribution. This pdf arises when the log-normal shadowing is substituted by the inverse-Gaussian one. This substitution will prove to be very accurate for several shadowing conditions. In this paper we conduct a performance evaluation of single-user communication systems operating in a composite channel. Our study starts by deriving an analytical expression for the outage probability. Then, we derive the moment generating function of the G-distribution, hence facilitating the calculation of average bit error probabilities. We also derive analytical expressions for the channel capacity for three adaptive transmission techniques, namely, i) optimal rate adaptation with constant power, ii) optimal power and rate adaptation, and iii) channel inversion with fixed rate.

Spectral efficiency evaluation for selection combining diversity (SCD) scheme over slow fading

In this paper we derive closed-form expressions for the single-user capacity of selection combining diversity (SCD) system, taking into account the effect of imperfect channel estimation at the receiver. The channel considered is a slowly varying spatially independent flat Rayleigh fading channel. The complex channel estimate and the actual channel are modelled as jointly Gaussian random variables with a correlation that depends on the estimation quality. Three adaptive transmission schemes are analysed: 1) optimal power and rate adaptation opra; 2) constant power with optimal rate adaptation ora; and 3) channel inversion with fixed rate cifr. Furthermore, we derive in this paper analytical results for capacity statistics including moment generating function (MGF), complementary cumulative distribution function (CDF) and probability density function (PDF). These statistics are valid for arbitrary number of receive antennas. Our numerical results show the effect of Gaussian channel estimation error on the achievable spectral efficiency.

Toward Practical Opportunistic Routing With Intra-Session Network Coding for Mesh Networks

We consider opportunistic routing in wireless mesh networks. We exploit the inherent diversity of the broadcast nature of wireless by making use of multipath routing. We present a novel optimization framework for opportunistic routing based on network utility maximization (NUM) that enables us to derive optimal flow control, routing, scheduling, and rate adaptation schemes, where we use network coding to ease the routing problem. All previous work on NUM assumed unicast transmissions; however, the wireless medium is by its nature broadcast and a transmission will be received by multiple nodes. The structure of our design is fundamentally different; this is due to the fact that our link rate constraints are defined per broadcast region instead of links in isolation. We prove optimality and derive a primal-dual algorithm that lays the basis for a practical protocol. Optimal MAC scheduling is difficult to implement, and we use 802.11-like random scheduling rather than optimal in our comparisons. Under random scheduling, our protocol becomes fully decentralized (we assume ideal signaling). The use of network coding introduces additional constraints on scheduling, and we propose a novel scheme to avoid starvation. We simulate realistic topologies and show that we can achieve 20%-200% throughput improvement compared to single path routing, and several times compared to a recent related opportunistic protocol (MORE).

On Channel Capacity Estimation and Prediction for Rate-Adaptive Wireless Video

Packet drops caused by residue errors (MAC-layer errors) can severely deteriorate the wireless video quality. Prior studies have shown that this loss of quality can be circumvented by using forward error correction (FEC) to recover information from the corrupted packets. The performance of FEC encoded video streaming is critically dependent upon the choice of source and channel coding rates. In practice, the wireless channel conditions can vary significantly, thus altering the optimal rate choices. Thus, it is essential to develop an architecture which can estimate the channel capacity and utilize this estimate for rate allocation. In this paper we develop such a framework. Our contributions consist of two parts. In the first part we develop a prediction framework that leverages the received packets' signal to silence ratio (SSR) indications and MAC-layer checksum as side information to predict the operational channel capacity. In the second part, we use this prediction framework for rate allocation. The optimal rate allocation is dependent upon the channel capacity, the distribution of the (capacity) prediction error and the rate-distortion (RD) characteristics of the video source. Consequently, we propose a framework that utilizes the aforementioned statistics for RD optimal rate adaptation. We exhibit the efficacy of the proposed scheme by simulations using actual 802.11b wireless traces, an RD model for the video source and an ideal FEC model. Simulations using source RD models derived from five different popular video codecs (including H.264), show that the proposed framework provides up-to 5-dB improvements in peak signal-to-noise ratio (PSNR) when compared with conventional rate-adaptive schemes.

Adaptive variance function estimation in heteroscedastic nonparametric regression

We consider a wavelet thresholding approach to adaptive variance function estimation in heteroscedastic nonparametric regression. A data-driven estimator is constructed by applying wavelet thresholding to the squared first-order differences of the observations. We show that the variance function estimator is nearly optimally adaptive to the smoothness of both the mean and variance functions. The estimator is shown to achieve the optimal adaptive rate of convergence under the pointwise squared error simultaneously over a range of smoothness classes. The estimator is also adaptively within a logarithmic factor of the minimax risk under the global mean integrated squared error over a collection of spatially inhomogeneous function classes. Numerical implementation and simulation results are also discussed.

Cross-Layer Rate and Power Adaptation Strategies for IR-HARQ Systems over Fading Channels with Memory: A SMDP-Based Approach

Incremental-redundancy hybrid automatic repeat- request (IR-HARQ) schemes are proposed in several wireless standards for increased throughput-efficiency and greater reliability. We investigate transmit power and modulation order adaptation strategies for the IR-HARQ schemes over correlated Rayleigh fading channels using semi-Markov decision process-based model. In order to jointly analyze physical layer and link layer, transmitter model incorporates a finite-size buffer that receives randomly varying traffic from a higher layer application. It is assumed that channel variations can be modeled with a first-order Markov chain. We show that the optimal transmission power and rate adaptation laws under buffering delay and packet overflow constraints can be obtained using the framework of semi-Markov decision process. We discuss three different adaptation models for the IR-HARQ schemes and compare their performances with the non-adaptive scheme. It is shown that unique optimal policy exists for each case and it can be computed using linear programming approach. This optimal policy is then applied for realistic channel fading and incoming traffic samples to evaluate its performance for both hard-decision and soft-decision decoding. Simulation results in general point out that substantial power savings can be achieved using adaptation and also if the transmission-delay requirements are relaxed.

Impact of Spatial Fading Correlation and Keyhole on the Capacity of MIMO Systems with Transmitter and Receiver CSI

This paper investigates the impact of spatial fading correlation and keyhole (pinhole) condition on the capacity of multiple-input multiple-output (MIMO) channels when instantaneous channel state information (CSI) is available at the transmitter and receiver sides. A separable correlation model is considered, whereby spatial fading correlation is accounted for at either or at both sides of the collocated MIMO wireless channel. Two extreme scenarios of a double scattering environment are analyzed: (i) an extremely rich scattering environment corresponding to a conventional semi-correlated Rayleigh fading channel and (ii) a double-correlated rank-deficient keyhole channel with a single degree of freedom. In the case of semi-correlated Rayleigh fading, the capacity expressions are derived for two types of correlation structures among the transmitting or the receiving antennas, namely, a constant correlation model and an arbitrary correlation model, the latter being induced by a full-rank Hermitian covariance matrix with non-repeating distinct eigenvalues. On the other hand, the capacity expressions pertaining to the double-correlated keyhole channel are derived given arbitrary Hermitian covariance matrices at the transmitter and the receiver. For all channel types and correlation structures, closed-form expressions for the capacity of the eigen-mode optimal power and rate adaptation policy as well as for the sub-optimal eigen-mode channel inversion and its truncated variant are derived. Monte Carlo simulations are also carried out thereby upholding our theoretical analysis.

On the capacity of generalized-k fading channels

This letter investigates the capacity of generalized-k fading channels. This very general model describes accurately composite multipath/shaodwing fading channels which are widely encountered in real-world environments. We derive closed-form expressions for three adaptive transmission techniques, namely, i) optimal rate adaptation with constant power, ii) optimal power and rate adaptation, and iii) channel inversion with fixed rate. The analytical expressions obtained match perfectly the results obtained by computer simulations. These expressions provide a good tool to assess the spectral efficiency of the aforementioned adaptive transmission techniques over composite channels.

Capacity of MIMO Rician fading channels with transmitter and receiver channel state information

This paper investigates the capacity of multiple- input multiple-output (MIMO) wireless communication systems when instantaneous channel state information (CSI) is available at both the transmitter and the receiver in a line-of-sight Rician fading environment. Specifically, an infinite series representation for the ergodic capacity of MIMO channels subject to uncorrected Rician fading (URiF) is derived, assuming both transmitter and receiver CSI. The ergodic capacity and its associated outage probability are expressed as a function of a cutoff value capturing the optimal power allocation scheme. Moreover, an equation for evaluating the cutoff value using standard numerical search techniques is derived, along with closed-form expressions for the capacity of the URiF MIMO channel when the so-called eigen-mode channel inversion technique and its truncated variant are implemented. We then provide numerical results showing the effects of Ricianness on the capacity of the eigen-mode optimal power and rate adaptation, and the sub-optimal channel inversion techniques and compare the achievable spectral efficiencies with and without channel knowledge at the transmitter thereby highlighting the capacity gains enabled by channel side information in a Rician fading environment.

Slow Adaptive -QAM under Third-Party Received Signal Constraints in Shadowing Environments

Motivated by recent interest in dynamic spectrum sharing between primary and secondary spectrum users, we investigate slow adaptive quadrature amplitude modulation (QAM) under third-party received power constraints. The optimal rate and power adaptation schemes are derived to maximize the average spectral efficiency (SE) for the secondary users. Additionally, closed-form expressions of the achievable SE are presented for correlated lognormal shadow fading environments. Our analytical and numerical results underscore the importance of exploiting shadowing correlation in the proposed adaptive schemes.

End-to-End Optimal Algorithms for Integrated QoS, Traffic Engineering, and Failure Recovery

This paper addresses the problem of optimal quality of service (QoS), traffic engineering (TE) and failure recovery (FR) in computer networks by introducing novel algorithms that only use source inferrable information. More precisely, optimal data rate adaptation and load balancing laws are provided which are applicable to networks where multiple paths are available and multiple classes of service (CoS) are to be provided. Different types of multiple paths are supported, including point-to-point multiple paths, point-to-multipoint multiple paths, and multicast trees. In particular, it is shown that the algorithms presented only need a minimal amount of information for optimal control, i.e., whether a path is congested or not. Hence, the control laws provided in this paper allow source inferred congestion detection without the need for explicit congestion feedback from the network. The proposed approach is applicable to utility functions of a very general form and endows the network with the important property of robustness with respect to node/link failures; i.e., upon the occurrence of such a failure, the presented control laws reroute traffic away from the inoperative node/link and converge to the optimal allocation for the ldquoreducedrdquo network. The proposed control laws set the foundation for the development of highly scalable feature-rich traffic control protocols at the IP, transport, or higher layers with provable global stability and convergence properties.

Cross-layer optimized rate adaptation and scheduling for multiple-user wireless video streaming

We present a cross-layer optimized video rate adaptation and user scheduling scheme for multi-user wireless video streaming aiming for maximum quality of service (QoS) for each user,, maximum system video throughput, and QoS fairness among users. These objectives are jointly optimized using a multi-objective optimization (MOO) framework that aims to serve the user with the least remaining playback time, highest delivered video seconds per transmission slot and maximum video quality. Experiments with the IS-856 (1timesEV-DO) standard numerology and ITU pedestrian A and vehicular B environments show significant improvements over the state-of- the-art wireless schedulers in terms of user QoS, QoS fairness, and the system throughput.

Distributed adaptive rate system for wireless packet networks

A distributed adaptive rate system for wireless packet networks is proposed. Compared to the centralized adaptive rate system that needs to know the packet retransmission probability to maximize the throughput, this system need not know the packet retransmission probability in advance and can achieve the optimal adaptive rate system that maximizes the throughput for wireless packet networks.

Adaptive Rate System for Wireless Packet Networks

The severe channel and interference condition can limit the throughput of the wireless packet networks. We thus propose an adaptive rate system to increase the throughput of the wireless packet networks. In this system, the data rate is adapted to the channel and interference condition. By optimizing the data rate for a given channel and interference condition, we establish the optimal adaptive rate system. It can be shown that the optimal adaptive rate system provides higher throughput than the fixed rate system.

Capacity of dual‐branch selection diversity receivers in correlative Weibull fading

AbstractAn analysis for the Shannon channel capacity of dual‐branch selection diversity receivers operating over correlative Weibull fading is presented under three adaptive policies: constant power with optimal rate adaptation, optimal power and rate adaptation and channel inversion with fixed rate. In this context, useful formulae for the average channel capacity with not necessarily identical fading statistics and arbitrary parameters for both the correlation coefficient and fading severity are derived in closed form. The analysis also includes the performance of single‐branch receivers where special cases of the expressions agree with known results. Illustrative numerical examples are also presented, demonstrating the effects of the correlation coefficient, fading severity and signal‐to‐noise ratio unbalance on the receiver's performance. Copyright © 2005 AEIT.