In this paper, we propose a novel sequential channel estimation approach for multiband cognitive radio (CR) systems. We introduce a general model and test two scenarios of practical interest. The two scenarios are as follows: 1) CR users optimally estimate all the available bands; and 2) CR users find one good channel with a large gain. In particular, we use a sequential search in which the CR users estimate the available channels one by one. During the search, the CR users determine whether to terminate the current channel estimation process and switch to the next channel based on the training symbols received so far. Our objective is to design a switch function, an estimator, and a stopping rule that minimize a combination of estimation time and error. For the multiband estimation scenario, we show that the optimal rule is to find the optimal number of symbols required for each channel in a joint optimization problem. For the good channel search problem, we show that the optimal decision rules that minimize a properly chosen cost function have a simple structure. In particular, both the termination and switching rules are threshold based. Numerical results are provided to illustrate the effectiveness of the proposed algorithms.

This paper provides an analytical framework to study the performance of linear companding techniques proposed in the OFDM literature, thus settling the numerous controversial claims that are based solely on simulation results. Linear companding transforms are widely employed to reduce the peak-to- average-power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. Two main linear companding classes have been considered in the literature: linear symmetrical transform (LST) and linear asymmetrical transform (LAST). In the literature, the bit error rate (BER) performance superiority of the basic LAST (with one discontinuity point) over the LST is claimed based on computer simulations. Also, it has been claimed that a LAST with two discontinuity points outperforms the basic LAST with one discontinuity point. These claims are however not substantiated with analytical results. Our analysis shows that these claims are, in general, not always true. We derive a sufficient condition, in terms of the companding parameters, under which the BER performance of a general LAST with M-1 discontinuity points is superior to that of LST. The derived condition explains the contradictions between different reported results in the literature and validates some other reported simulation results. It also serves as a guideline in the process of choosing proper values for companding parameters to obtain a specific trade-off between PAPR reduction capability and BER performance. In particular, the derived sufficient condition shows that the BER performance for LAST depends on the slopes of the LAST rather than on the number of discontinuity points as has been indicated so far. Moreover, we derive conditions for the companding parameters in order to keep the average transmitted power unchanged after companding. Our theoretical derivations are supported by simulation results.

We propose an auxiliary strategy, called per-user caching, for locating users who move from place to place while using Personal Communications Services (PCS). The caching strategy augments the basic location strategy proposed in existing standards such as GSM and IS-41, with the objective of reducing network signaling and database loads in exchange for increased CPU processing and memory costs. Since technology trends are driving the latter costs down, the auxiliary strategy will become increasingly attractive. The idea behind caching is to reuse the information about a called user's location for subsequent calls to that user, and is useful for those users who receive calls frequently relative to the rate at which they change registration areas. This idea attempts to exploit the spatial and temporal locality in calls received by users, similar to the idea of exploiting locality of file access in computer systems. We use a reference PCS architecture and the notion of a user's local call-to-mobility ratio (LCMR) to quantify the costs and benefits of using caching and classes of users for whom it would be beneficial. We also present two simple algorithms for estimating users' LCMR and the situation in which each is preferable. We show that under a variety of assumptions caching is likely to yield significant net benefits in terms of reduced signaling network traffic and database loads.>

The paper analyses and simulates the impact of providing voice and non-voice personal communications services (PCS) on the volume of network database transactions. A number of activities in PCS, such as user mobility and call origination and delivery, require data management functions. These include mobility registration, radio channel management, service profile query, security-related functions such as authentication and privacy, and special billing arrangements. A large portion of these data management activities may be performed using elements of the intelligent network such as switches (e.g., service switching point or SSP) and network databases (e.g., service control point or SCP). The authors extend the single logical database model to include data partitioning into multiple databases. This model is helpful in case a single database is inadequate to handle all the transaction volume generated due to PCS. They give a first-cut analysis using such a model. A simulation framework is described for data management under various scenarios. This work pertains mainly to data management. In addition, qualitative effects of data partitioning on signaling traffic are outlined.>

Coding schemes for the quantization of line drawings that outperform basic chain codes are investigated. First, subpixel accuracy reconstruction is obtained by a simple linear filtering of the chain code points, which achieves a factor-of-three to-four reduction in average reconstruction distortion for smooth curves. Second, the basic chain encoding schemes are generalized to a multipath-tree-searched encoding scheme. A variation of the (M,L)-algorithm is used to maintain M contending chain code paths in storage and choose the best path from these. Over a wide variety of source curves, tree-searched chain coding results in nearly an order of magnitude reduction in average reconstruction distortion over smoother chain codes. The performance improvement for curves is obtained with only a slight increase in bit rate over basic chain codes.>

The capture property of a receiver is used to design a collision resolution algorithm for a ternary feedback random access channel. Group testing techniques are employed under the assumption of finite users model. Users are assumed to generate a packet with probabilitypduring a collision resolution interval. Two groups of users with different transmission powers are assumed to exist in the system. Performance of this algorithm is shown to be considerably better than that of the algorithm without capture. Effect of varying the number of users in both groups on the expected collision resolution interval is studied. One of the features of this algorithm is that it is always superior to TDMA for any probabilitypas long as there is at least one user in the high power group.

A parallel processor version of the stack algorithm is proposed that searches the code tree in parallel. The parallel stack algorithm is then implemented and tested using a loop architecture with four Intel 8086 microprocessors. The two versions of the stack algorithm, the uniprocessor and multiprocessor implementations, are then used to encode a voiced speech sound. The multiprocessor version simultaneously improves two conflicting performance measures, namely, the signal-to-noise ratio and node computation per processor, and may indeed lead to a real-time implementation of the stack algorithm.

The(M, L)-algorithm has been widely used in speech and image encoding. Recently, use of(M, L)-Iike algorithms has been suggested for decoding phase codes. With its ever-increasing use, there arises a need to explore architectures suitable for real-time applications. Toward this end, we present a multiprocessor architecture for the(M, L)algorithm that employs an SIMD (single instruction-multiple data) machine structure. The considerations involved in interconnection network design are discussed. The main functions of the network controller are switch state selection and synchronization. The number of switching elements required is significantly less than the elements required in the universal permutation network. These features make this architecture suitable for VLSI implementation. The tradeoff between number of processors and encoding time is also discussed.

Tree codes find wide use in a variety of problems such as source encoding, sequential decoding, pattern recognition, and related fields. Efficient algorithms exist to explore the code trees and are well documented in the literature. All of these algorithms search code trees in an incremental manner, releasing a path map symbol at a time. A recent work has investigated the effect of releasing multiple symbols on the performance of the(M, L)algorithm used with speech. Here we investigate the effect of multiple symbol release rules on the performance of the stack algorithm in the context of speech encoding. We show that significant computational reduction can result with the use of such rules. We use an efficient data structure, the AVL tree data structure, to store code tree paths.

The cost of a number of sequential coding search algorithms is analyzed in a systematic manner. These algorithms search code trees, and find use in data compression, error correction, and maximum likelihood sequence estimation. The cost function is made up of the size of and number of accesses to storage. It is found that algorithms that utilize sorting are much more expensive to use than those that do not; metric-first searching regimes are less efficient than breadth-first or depth-first regimes. Cost functions are evaluated using experimental data obtained from data compression and error correction studies.

Code tree search algorithms find wide applicability in source encoding, channel decoding, pattern recognition, and maximum likelihood sequence estimation. These algorithms search code trees and may be classified as depth-first, breadth-first, and metric-first depending on the search criterion employed. We define here a criterion for metric-first algorithms to be optimal. We show that implementations of metric-first searches proposed heretofore are not optimal, and we propose and analyze two algorithms which are. Experimental data obtained by encoding a voiced speech sound point to superiority of the proposed implementation over earlier versions.

A metric-first tree coding algorithm, similar to the stack algorithm, is used to encode voiced speech. From experimental evidence, it is shown how to optimize the algorithm's performance with respect to the algorithm's storage, execution time, and number of tree branches searched per symbol released as output. For each of these, the optimal parameterizing of the algorithm differs markedly. Similarities are pointed out between our results for speech and earlier theoretical results for the binary i.i.d, source with Hamming distortion measure. Comparisons to theMalgorithm are made.