In this paper, we study the energy efficiency of small-cell on/off control schemes in which small-cells turn on when the number of active users reaches a certain threshold value called on-threshold. In particular, we derive analytical formulas for various performance metrics such as expected small-cell power consumption, average consumed energy per transmitted bit, expected energy saving, and energy saving probability. Moreover, we show that the expected small-cell power consumption strictly decreases with increased on-threshold value and derive a mathematical expression for the optimal on-threshold value that minimizes the average consumed energy per transmitted bit. With simulation results, we not only verify the validity of the analytical results but also discuss how the theoretical results can be used in system performance evaluation and optimization. We believe that many of the results in this paper can be used in practical small-cell network design and operation.

In this paper, we analyze a 28 GHz suburban channel using a hybrid ray-tracing simulation. Hybrid ray-tracing technique is a combination of image method and shooting-and-bouncing rays (SBR) method. The SBR method finds a rough propagation path and the image method predicts the exact propagation path. The hybrid ray-tracing simulation is compared with a measurement campaign conducted in Wolpyeong-dong, Daejeon, Korea, and its performance is verified. The transmitter is placed on a 29m building; the heights of the other buildings are between 10m and 12m. Based on a reasonable agreement between the results of ray-tracing and the measurement results, five streets of Wolpyeong-dong were analyzed using ray-tracing simulation. The path loss, power delay profile, root mean square delay spread, angle of arrival and angular spread were obtained.

We propose employing receiver cooperation in centralized topology control to improve energy efficiency as well as network connectivity. The idea of transmitter cooperation has been widely considered in topology control to improve network connectivity or energy efficiency. However, receiver cooperation has not previously been considered in topology control. In particular, we show that we can improve both connectivity and energy efficiency if we employ receiver cooperation in addition to transmitter cooperation. Consequently, we conclude that a system based both on transmitter and receiver cooperation is generally superior to one based only on transmitter cooperation. We also show that the increase in network connectivity caused by employing transmitter cooperation in addition to receiver cooperation is at the expense of significantly increased energy consumption. Consequently, system designers may opt for receiver-only cooperation in cases for which energy efficiency is of the highest priority or when connectivity increase is no longer a serious concern.

Recently, a cooperative cognitive radio network (CCRN) and multiple-input multiple-output (MIMO) cognitive radio (CR) network have been proposed and investigated individually as promising paradigms for CR networks. Herein, we consider applying the MIMO techniques to a CCRN in order to achieve increased spectral efficiency. Assuming that the system comprises a single-input single-output (SISO) primary user (PU) pair and a multi-input single-output (MISO) secondary user (SU) pair, we propose jointly optimizing the beamforming vector and power allocation for the SU transmitter in order to maximize the rate for the SU while meeting the rate requirement for the PU. As the problem is nontrivial, we circumvent it using the uplink and downlink duality and equality of the left and right eigenvalues. Further, we introduce an iterative algorithm with a proof of convergence. From the numerical results, the proposed algorithm converges in a small number of iterations and outperforms the zero-forcing (ZF) beamforming algorithm while providing an upper bound for the CCRN-MIMO performance. Furthermore, the application of the proposed algorithm is not limited to CCRN-MIMO; it can also be extended to the conventional relay MIMO and/or MU-MIMO with a quality-of-service (QoS) requirement.

With the purpose of reducing energy consumption and increasing network connectivity, the cooperative communication (CC) technique has been adopted for topology control. In previous studies, the concept of transmit diversity, which adds partial signals using a maximum ratio combiner, had only been considered and never fully exploited for receiver diversity. In this paper, we introduce a novel topology control algorithm that uses a receiver diversity. Compared with existing topology control algorithms, proposed scheme shows significant improvements in connectivity, computational complexity, and average power consumption per communication link.

This paper focuses on a downlink beamforming problem in the cognitive radio (CR) communication system where primary users (PUs) coexist with secondary users (SUs). It is assumed that the SU transmitter has multiple antennas and transmits data to another SU's single-antenna receiver by employing the beamforming. By properly designing a beamforming vector, a SU can maximize its channel gain while maintaining an interference with PU below a predefined level. Designing a beamforming vector includes steering beamforming vector direction as well as adjusting transmit power. In order to construct the 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. In addition, we propose a feedback bit allocation mechanism, in order to maximize the gain of the SU link. By using the proposed scheme, the CR system become robust against errors attributed to the partial CSI.

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 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).

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.

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.

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.

The optimal resource allocation policy is studied for non-real-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. 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: a greedy policy is optimal to maximize the sum of throughput from each user, whereas a fair policy is optimal to maximize the product of throughput from each user. A unified approach is taken to derive the optimal policies, and it can also be applied to other power allocation problems in CDMA reverse link. Numerical results of the channel capacity are presented for both objectives along with the effect of QoS constraints.

The information-theoretic sum capacity of reverse link CDMA systems with QoS constraints is investigated in this paper. Since the reverse link of CDMA systems are, for a given channel and noise conditions, interference-limited, the sum capacity can be achieved by optimally allocating the transmit powers of the mobile stations with the optimal (Shannon) coding. Unfortunately, the sum capacity is usually achieved via unfair resource allocation. This can be avoided by imposing QoS constraints on the system. The results here show that for a single cell system, the sum capacity can be achieved while meeting the QoS constraints with a semi-bang-bang power allocation strategy. Numerical results are then presented to show the multi-user diversity gain and the impact of QoS constraints. The implication of TDM operation in a practical reverse link CDMA system is also discussed.

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 allocating the transmit powers of the mobile stations. The maximum capacity is often achieved by unfair resource allocation. To avoid such a case, QoS constraints are imposed to individual mobile stations. The exhaustive search of the optimal power allocation solution that maximizes the aggregate 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. The paper shows that for a single cell, the optimal power allocation solution can be found by polynomial times of computations, without sacrificing the optimality. Numerical results are presented to show the multi-user diversity gain and the impact of QoS constraints.

This paper addresses the problem of dynamic resource allocation in a multiservice direct-sequence code-division multiple-access (DS-CDMA) wireless network supporting real-time (RT) and nonreal-time (NRT) communication services. For RT users, a simple transmission power allocation strategy is assumed that maximizes the amount of capacity available to NRT users without violating quality of service requirements of RT users. For NRT users, a joint transmission power and spreading gain (transmission rate) allocation strategy, obtained via the solution of a constrained optimization problem, is provided. The solution maximizes the aggregate NRT throughput, subject to peak transmission power constraints and the capacity constraint imposed by RT users. The optimization problem is solved in a closed form, and the resulting resource allocation strategy is simple to implement as a hybrid CDMA/time-division multiple-access strategy. Numerical results are presented showing that the optimal resource allocation strategy can offer substantial performance gains over other conventional resource allocation strategies for DS-CDMA networks.

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 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.

Article Optimality of greedy power control and variable spreading gain in multi-class CDMA mobile networks Share on Authors: Seong-Jun Oh Electrical Engineering and Computer Science Department, University of Michigan, 1301 Beal Ave., Ann Arbor, MI Electrical Engineering and Computer Science Department, University of Michigan, 1301 Beal Ave., Ann Arbor, MIView Profile , Kimberly M. Wasserman Electrical Engineering and Computer Science Department, University of Michigan, 1301 Beal Ave., Ann Arbor, MI Electrical Engineering and Computer Science Department, University of Michigan, 1301 Beal Ave., Ann Arbor, MIView Profile Authors Info & Claims MobiCom '99: Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networkingAugust 1999 Pages 102–112https://doi.org/10.1145/313451.313498Online:01 August 1999Publication History 38citation813DownloadsMetricsTotal Citations38Total Downloads813Last 12 Months2Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

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.

In this paper, we consider a direct-sequence code division multiple access (DS-CDMA) network consisting of a single radio access point and a collection of wireless terminals. The network offers two classes of service: class-1 (real-time) and class-2 (reliable). We are interested in studying the effect of dynamic spreading gain control (SGC) on the dynamics of multiple access interference (MAI), spectral efficiency, and the quality of service (QoS) experienced by each service class. We first consider a time-slotted system in which class-2 terminals operate in a random access fashion. We show that under optimal (throughput maximizing) dynamic SGC: (1) the optimal retransmission probability is equal to one, and (2) the optimal spreading gain increases linearly, or equivalently, the transmission rate decreases inverse linearly, as the MAI level increases. We then model the system as a continuous-time finite-source queueing system with processor sharing, and obtain an explicit (closed-form) expression for the stationary distribution of the number of active class-1 and class-2 terminals, that is, the MAI level. This distribution is used to derive expressions for various QoS measures and define a capacity or admissible region. The results obtained by simulation and analysis are in extremely close agreement. This work contributes to a better understanding of the relationships between QoS, multiple access interference, and allocation of radio resources in DS-CDMA networks.

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.

We consider a time-slotted DS-CDMA network consisting of a single radio access point and a finite number of mobile wireless terminals. The terminals generate non-real-time packet data and transmit, subject to constraints on the average energy consumed per packet transmission, 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 effect of dynamic spreading gain control on the stability and throughput properties of the network. We first impose no energy constraints and provide an optimal (throughput maximizing) algorithm under which (i) the asymptotically optimal retransmission probability is equal to one, and (ii) the optimal spreading gain increases linearly as the multiaccess interference (MAI) level increases, or equivalently, the transmission rate decreases inverse linearly as the MAI level increases. We also obtain a simple closed-form expression for the asymptotic throughput as the number of backlogged terminals becomes large. We then impose energy constraints and modify the optimal algorithm by controlling both the spreading gain and retransmission probability of the terminals. The resulting algorithm may or may not eliminate bistability; however, in either case, it achieves high throughput.