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This paper focuses on a downlink beamforming problem in the cognitive radio~(CR) communication system where primary users~ (PU) coexist with secondary users~(SU). It is assumed that the SU transmitter has multiple antennas and transmits data to another SU's single-antenna receiver using the beamforming technique. By properly designing a beamforming vector, SU can maximize its channel gain while maintaining an interference with PU below a predefined level. In order to construct an optimal beamforming vector, the SU transmitter requires knowledge of the downlink channel information of both PU and SU receivers sent on the feedback channel. However, it is impractical to assume that the transmitter has the perfect channel state information~(CSI) considering the tremendous feedback overhead. One way to tackle this feedback overhead problem is to use a finite number of feedback bits indicating the index of a predefined codeword in the codebook. We analyze interference to the PU receiver and propose an algorithm to design a beamforming vector considering an error attributed to the partial CSI. The simulation shows that the analysis is quite accurate and that the beamforming vector, designed according to the proposed algorithm, keeps interference to PU below a predefined level while taking into account the error owing to the partial CSI. By using the proposed scheme, the CR system can become more robust against errors attributed to the partial CSI.

This paper considers the object tracking problem in three dimensional (3-D) space when the azimuth and elevation of the object are available from the passive acoustic sensor. The particle filtering technique can be directly applied to estimate the 3-D object location, but we propose to decompose the 3-D particle filter into the three planes" particle filters, which are individually designed for the 2-D bearings-only tracking problems. 2-D bearing information is derived from the azimuth and elevation of the object to be used for the 2-D particle filter. Two estimates of three planes" particle filters are selected based on the characterization of the acoustic sensor operation in a noisy environment. The Cramer-Rao Lower Bound of the proposed 2-D particle filter-based algorithm is derived and compared against the algorithm that is based on the direct 3-D particle filter.

This paper analyzes the system-level performance of the long term evolution (LTE)/LTE-Advanced (LTE-A). LTE/LTE-A has been considered to be a promising next generation communication system. It is proposed to ITU-R to be acknowledged as an IMT-Advanced technology. The performance of candidate technology proposals for IMT-Advanced should be evaluated to see if it satisfies the predefined minimum requirement of ITU-R. Note that ITU-R provides a report on evaluation guidelines, assumptions and minimum requirements, and it is strongly recommended that the guidelines and assumptions are followed when evaluating performance. This article summarizes the simulation methodology based on ITU-R guidelines and investigates the key technology, Multi-User MIMO (MU-MIMO), of LTE/LTE-A for IMT-Advanced. Simulation shows that LTE/LTE-A with the advanced MU-MIMO feature achieves performance above the ITU-R requirements, which cannot be achieved with Single-User MIMO (SU-MIMO).

We consider a queuing model with applications to electric vehicle (EV) charging systems in smart grids. We adopt a scheme where Electric Service Company (ESCo) broadcasts one bit signal to consumers indicating on-peak periods for the grid. EVs randomly suspend/resume charging based on the signal. To model the dynamics of the population of EVs we analyze an M/M/∞ queue with random interruptions, and propose estimates using time-scale decomposition. Using the estimates we show how ESCo can optimally adjust the indicator signal so as to minimize the mean number of charging EVs during the actual on-peak periods. Next we consider the case where EVs respond to the signal based on the individual loads. Simulation results show that performance is improved if the EVs carrying higher loads are less sensitive to the on-peak indicator signal.

An approach for dynamic object association and identification is proposed for heterogeneous sensor network consisting of visual and identification sensors. Visual sensors track objects by a 2D localization, and identification sensors (i.e., RFID system, fingerprint, or iris recognition system) are incorporated into the system for object identification. This paper illustrates the feasibility and effectiveness of information association between the position of objects estimated by visual sensors and their simultaneous registration of multiple objects. The proposed approach utilizes the object dynamics of entering and leaving the coverage of identification sensors, where the location information of identification sensors and objects is available. We investigate necessary association conditions using set operations where the sets are defined by the dynamics of the objects. The coverage of identification sensor is approximately modeled by the maximum sensing coverage for a simple association strategy. The effect of the discrepancy between the actual and the approximated coverage is addressed in terms of the association performance. We also present a coverage adjustment scheme using the object dynamics for the association stability. Finally, the proposed method is evaluated with a realistic scenario. The simulation results demonstrate the stability of the proposed method against nonideal phenomena such as false detection, false tracking, and inaccurate coverage model.

Object tracking by an acoustic sensor based on particle filtering is extended for the tracking of multiple objects. In order to overcome the inherent limitation of the acoustic sensor for the simultaneous multiple object tracking, support from the visual sensor is considered. Cooperation from the visual sensor, however, is better to be minimized, as the visual sensor's operation requires much higher computational resources than the acoustic sensor-based estimation, especially when the visual sensor is not dedicated to object tracking and deployed for other applications. The acoustic sensor mainly tracks multiple objects, and the visual sensor supports the tracking task only when the acoustic sensor has a difficulty. Several techniques based on particle filtering are used for multiple object tracking by the acoustic sensor, and the limitations of the acoustic sensor are discussed to identify the need for the visual sensor cooperation. Performance of the triggering-based cooperation by the two visual sensors is evaluated and compared with a periodic cooperation in a real environment.

In this paper. we consider an admission control algorithm for cellular networks. It is based on direct/dynamic monitoring of the QoS performances -- the delay tail of the admitted users. The main purpose of the direct monitoring of QoS performances is to guarantee the required QoS provision more precisely. The system delay tail is effectively computed by the proposed delay tail estimation algorithm. With the estimated delay tails, each base station determines the admission or rejection for a new user to the system. By doing so, the admission control algorithm becomes more robust against time-varying fading channel environment. Simulation results in OFDMA cellular system shows that the proposed algorithm can provide substantial capacity gains in offering QoS. We also use a general Neyman-Pearson-like framework in evaluating various admission control mechanisms.

In this paper, we consider the frequency reuse issue in the downlink of a multi-cell OFDMA system. We first implement the static frequency reuse scheme in the OFDMA sub-carrier assignment over the multi-cell system in order to control the inter-cell interference. Then, we add the random access sub-band to adopt the dynamic frequency reuse. The main purpose of introducing the random access sub-band is to improve the fairness of the system. In order to efficiently share the random access sub-band over the multi-cell sectors, the sector load information is considered. We assume that there is only a minimal coordination between the sectors so the central network controller provides only the access probabilities to each cell. With these probabilities, the sectors transmit the data on the random access channel. By doing so, the usage of the random access sub-band is randomized, and the fairness across the sector is provided by controlling the probabilities. Simulation results show that the proposed random access scheme achieve a performance improvement in the cell-edge user throughput. Index Terms—OFDMA, Multi-cell Scheduling, Frequency Reuse Factor

In this paper we focus on a SC-FDMA system's resource allocation problem considering the uplink of the 3GPP Long Term Evolution system. We first define a utility function at each sector aiming at maximizing sum of average SINR, and implement the fairness factor which enables the resource allocator to schedule resources fairly among the users. Then, for the fairness-aware utility function, the optimization problem is solved using the iterative Hungarian. In multi-cell system, as the users suffer a uncorrelated inter-cell interference, it is difficult to find the globally optimal radio resource allocation. We propose a distributed allocation method which avoids the drastic interference level changes. Results exhibit that the proposed allocation method has a robustness to the interference variation and can be close to the globally optimal allocation. Index Terms—OFDMA, SC-FDMA, Resource Allocation, Multi-Cell, Inter-Cell Interference

This paper revisits an optimal rate and power allocation problem to maximize throughput in uplink CDMA single-cell packet data communications. First, we show that the widely-accepted belief that an optimally selected rate always keeps a constant value of the resulting bit energy to the interference plus noise power spectral density ratio is not true in most practical CDMA packet transmission environments, where the packet size varies in proportion to the rate. Then, we derive the rate-dependent optimal bit energy-to-interference-noise power spectral density ratio, based on which we convert the original joint optimization problem of rate and power to an equivalent but simple power allocation problem. Finally, we derive an optimal power allocation strategy by applying the convex optimization theory. Through two instructive examples, we show that the optimality of the well-known bang bang power control, that is, each user (except at most one user) should either transmit his data at the maximum allowed power level or at the minimum required power level meeting the SINR requirement in order to maximize the system throughput, may or may not be true depending on the incorporated channel coding scheme.

Medicinal herbs are increasingly used in the search for safe and efficient drug candidates for hepatitis C virus infection. In this study, we have investigated the anti-HCV effect of compounds from Mori Cortex Radicis. During a screening for extracts with anti-HCV affinity from medicinal plants (173 species), the methanol extract of Mori Cortex Radicis was selected. Fractionation of the extract by monitoring antiviral activity with a replicon cell-based assay resulted in the isolation of five compounds, mulberroside C ( 1), moracin P ( 2), moracin O ( 3), moracin M ( 4) and mulberrofuran K ( 5) from the ethyl acetate-soluble fraction. Compounds 1 approximately 4 showed significant inhibitory activities. Compounds 2 and 3 showed potent inhibitory activity (IC (50) 35.6 microM, 80.8 microM, respectively) in the replicon cell assay, which was confirmed by NS3 helicase inhibitory activity (IC (50) 42.9 microM, 27.0 microM, respectively).

The optimal resource allocation policy is studied in this paper, for nonreal-time users in CDMA reverse link. The resource allocation policy of interest includes channel coding, spreading gain control and power allocation under the conventional receiver operation-multiuser detection technique is not considered. The constraints in the optimization include peak transmit power of the mobile station, total received power at the base station and QoS in the form of minimum SINR for each user. The coding and spreading gain control can be separated from the power allocation strategy. Our results show that the optimal power allocation policy depends on the objective function: to maximize the sum of throughput from each user, a greedy policy is optimal where the good users (mobile stations with good radio conditions) transmit with full power, bad users (mobile stations with poor radio conditions) barely achieve their QoS and there is at most one user in-between; on the other hand, to maximize the product of throughput from each user, a fair policy is optimal where the bad users transmit with full power and the good users transmit with powers to reach a common received power level. The fairness of the optimal policy in the latter case makes QoS constraint unnecessary. Furthermore, we have found a unified approach in deriving these optimal policies. This approach can also be applied to other power allocation problems in CDMA reverse link. We also present numerical results on the channel capacity under both objectives and the effect of QoS constraint.

A novel forward link supervision algorithm applicable to power controlled CDMA systems is presented. This new algorithm relies upon the quality of the dedicated power control commands and is therefore compatible with systems that offer packet data service without an assigned dedicated Walsh code channel such as that found in commercial systems denned by IS-2000 Rev C. The algorithm is analyzed both analytically and with simulations. The conclusion from these analyzes show that the proposed forward link supervision algorithm does not affect the call quality, minimizes the impact on the reverse link capacity from unreliable power control commands and leads to call termination only if necessary.

The information-theoretic sum capacity of reverse link CDMA systems is investigated in this paper. As the reverse link CDMA systems are interference-limited, for given channel and noise conditions, the information-theoretic system capacity can be achieved by optimally managing the interference from mobile stations. Optimal interference management means optimal allocation of the transmit powers of the mobile stations. The exhaustive search of the optimal power allocation policy that maximizes the aggregate system capacity, requires O(N/sup M/) computations, where M is the number of the mobile station in the system and N is the granularity of the transmit power of a mobile station. In this paper, we prove that for a single cell, the number of computations to find the optimal power allocation solution can be reduced to O(NM), without sacrificing the optimality. We also show that an upper and a lower bound can be computed with O(M) computations, and the bounds are tight for small signal to noise ratio.

In this paper we investigate the HDR CDMA system reverse link data channel throughput and obtain both an upper bound, which is derived from the pole capacity, and more practical results applicable when considering variable rate transmission with probabilistic flow control. From the analytical derivation of the pole capacity, a simple but effective rate control algorithm is devised that maintains the reverse link outage probability below a desired level while attempting at maximizing the reverse link utilization. The pole capacity accounts for the various overhead channels, and their effect on capacity is assessed. Simulations are then used to estimate reverse link throughput using the proposed rate control algorithm for both a single-cell and multi-cell scenarios. The effect of bursty traffic typical of non-streaming applications is also investigated. The results obtained not only provide a realistic estimate of the reverse link throughput, but also an insight into the effect of overhead, probabilistic flow control, and bursty traffic on the HDR reverse link throughput.

In this paper, we consider a DS-CDMA mobile network supporting real-time and non-real-time services. We study how the delay tolerance of non-real-time traffic can be exploited by allowing both transmission power control and variable spreading gain (transmission rate) control. Two control mechanisms adapt the received energy per bit to the current channel conditions and efficiently manage the multiple access interference so as to optimize performance. We provide the jointly optimal power and spreading gain allocation strategy of non-real-time sources. Our strategy maximizes non-real-time throughput subject to constraints on peak transmission power and protects QoS of real-time-services. We show that under the optimal strategy, the optimal spreading gains are inverse linear in the signal to interference plus noise ratio (SINR), and transmission power is allocated to the non-real-time sources in decreasing order of channel gain according to a greedy control strategy. We also present numerical results comparing the throughput and delay performance of the optimal strategy with other common strategies; the optimal strategy can offer substantial performance gains.

We consider a direct-sequence code division multiple access (DS-CDMA) network consisting of a single base station and a collection of mobile wireless terminals. There are two classes of traffic: voice and data. We provide a spectrally efficient multiple access protocol based on the dynamic control of the spreading gain of the data terminals. We also obtain expressions for key quality of service (QOS) metrics in terms of the number of active voice and data terminals. This work contributes to a better understanding of the relationships between the QOS, number of active terminals, and the allocation of radio resources in DS-CDMA networks.

In this paper, we consider a time-slotted DS-SSMA network consisting of a single radio access point and a finite number of mobile wireless terminals. The terminals generate "bursty" packet data and transmit in a random access fashion over a common broadband channel to the access point using different spreading codes. As in narrowband ALOHA systems, the performance of random access spread spectrum networks can be severely hampered due to saturation effects caused by inherent bistable behavior. We study the affect of dynamic spreading gain control on the stability and throughput properties of the network. We provide an optimal algorithm and establish a necessary and sufficient condition under which the algorithm eliminates bistability. If the condition holds, then the resulting operating point is the best possible; otherwise, the two resulting stability points are, in some sense, the best possible. In either case, the algorithm achieves high throughput.

In this paper, we investigate the code allocation problem of forward link channelization, i.e., allocation of Walsh codes and quasi-orthogonal functions (QOF's) in cdma2000 systems. Given multipath power profiles, geometry factors, and allocated codes of mobile stations (MSs), we propose a simple solution for the total sector transmit power. It is shown that the sector transmit power can be expressed in terms of a single variable, namely, the lumped geometry factor (LGF), which accounts for MS geometry factors, code channel activities, and cross-correlations among all the allocated codes. The formula is used to devise a code allocation algorithm that is proven optimum in the sense of maximizing capacity, under the condition of single-path channels.

We study the radio resource allocation problem of distributed joint transmission power control and spreading gain allocation in a DS-CDMA mobile data network. The network consists of K base stations and M wireless data users. The data streams generated by the users are treated as best-effort traffic, in the sense that there are no pre-specified constraints on the quality of the radio channels. We are interested in designing a distributed algorithm that achieves maximal (or near-maximal in some reasonable sense) aggregate throughput, subject to peak power constraints. We provide an algorithm where base stations coordinate in a distributed fashion to control the powers and spreading gains of the users, and show that it converges to a Nash equilibrium point. In general, there may be multiple equilibrium points; however, certain structural properties of the throughput expression can be exploited to significantly trim the search space and induce an ordering on the users in each cell. The numerical results indicate that with these modifications, the algorithm frequently converges in just a few iterations to the throughput maximizing (globally optimal) power and spreading gain allocation.