Power Adaptation Algorithm Research Articles

TCP-aware power and rate adaptation in DS∕CDMA networks

A novel joint power and rate adaptation scheme for DS/CDMA networks is proposed using information from the TCP state machine. The impetus behind this cross-layer optimisation approach is to satisfy the varying transmission rates of TCP flows which depend on the congestion window and round-trip time. Initially, a new family of objective functions is defined that encompasses TCP based information. Then by solving the proposed bi-objective optimisation problem using the ɛ-constraint method the Pareto front is calculated, which gives insight into the trade-off between the desired transmission rate and the corresponding transmitted power. Using a polynomial description of the Pareto front, the solution with the minimum L2-norm from a defined utopia point is selected as the optimum trade-off between power consumption and required rate transmission, even though different heuristics can be used. Although the Pareto frontier has been calculated using derivative based optimisation techniques, prominent paradigms of knowledge-based techniques can increase the computational efficiency. Previously proposed schemes allocate resources based on lower-layer information, such as channel conditions and link-layer buffer occupancy. The novelty and prerogative of this cross-layer optimisation approach is that critical transport layer information is integrated into the design of a power and rate adaptation algorithm for DS/CDMA networks.

Analysis of Linear Iterative Learning Control Schemes -A 2D Systems/Repetitive Processes Approach

This paper first develops results on the stability and convergence properties of a general class of iterative learning control schemes using, in the main, theory first developed for the branch of 2D linear systems known as linear repetitive processes. A general learning law that uses information from the current and a finite number of previous trials is considered and the results, in the form of fundamental limitations on the benefits of using this law, are interpreted in terms of basic systems theoretic concepts such as the relative degree and minimum phase characteristics of the example under consideration. Following this, previously reported powerful 2D predictive and adaptive control algorithms are reviewed. Finally, new iterative adaptive learning control laws which solve iterative learning control algorithms under weak assumptions are developed.

Capacity and power control in spread spectrum macrodiversity radio networks

What is the capacity of the uplink of a radio network of receivers? We consider a spread spectrum model in which each user is decoded by all the receivers in the network (macrodiversity). We use a carrier-to-interference performance criterion that we derive from Shannon theory; each user must find the right transmitter power level to satisfy its carrier-to interference constraint. Satisfying this requirement for all users is equivalent to solving a fixed point problem. We use this power control problem to derive the network capacity region and find that the feasibility of a configuration of users is independent of their positions in the network; each user can be assigned a bandwidth that is independent of the user's position in the network. Our capacity region is an upper bound over all schemes that treat the interference of other users as pure noise. To show that the capacity can be realized in practice, we propose a decentralized power adaptation algorithm and prove global convergence to the fixed point via a monotonicity argument.

Packet combining systems based on the Viterbi decoder

Type-I hybrid-ARQ protocols can be used to construct powerful adaptive rate algorithms through the use of packet combining techniques. In this paper several packet combining schemes are presented for use in conjunction with the Viterbi decoder over stationary and time-varying channels. The first technique presented is an averaged diversity combiner, which is shown to be identical in performance to an interleaved code combiner over an AWGN channel. The averaged diversity combiner is then generalized to make use of packet weights based on either ideal channel state information or weights derived from side information generated by the Viterbi decoder. It is shown that the weighted diversity combiner using decoder side information performs almost as well as the system using ideal channel state information. All of the packet combining schemes discussed in this paper provide improved throughput and reliability performance relative to that provided by the standard type-I hybrid-ARQ or EEC systems. This performance improvement is obtained at the expense of negligible to moderate modifications to the transmitter and receiver. Performance bounds are derived for each of the combining schemes and their tightness verified through simulation results.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>