Operationally efficient radio networks typically feature a high degree of self-organization. This means less planning efforts and manual intervention, and a potential for better radio resource utilization when network elements adapts its operation to the observed local conditions. The focus in this paper is selfoptimization of the random access channel (RACH) in the 3G Long Term Evolution (LTE). A comprehensive tutorial about the RACH procedure is provided to span the complexity of the selfoptimization. Moreover, the paper addresses RACH key performance metrics and appropriate modeling of the various steps and components of the procedure. Finally, some coupling between parameters and key performance metrics as well as selfoptimization examples are presented together with a feasibility discussion. The main ambition with this workshop paper is to present and define a relevant set of self-optimization problems, rather than to provide a complete solution.
Future radio access networks are expected to show a high degree of self-organization. This paper addresses self-tuning of the random access channel (RACH) in the 3G Long Term Evolution (LTE). The feasibility of self-tuning is investigated by means of simulation, where the coupling between several parameters and the performance of RACH is provided. The conclusion of the simulations is that RACH self-tuning is indeed possible given that UE assisted measurements are available for the self-tuning mechanism.
In this paper a preprocessing algorithm for binary quadratic programming problems is presented. For some types of binary quadratic programming problems, the algorithm can compute the optimal value for some or all integer variables without approximations in polynomial time. When the optimal multiuser detection problem is formulated as a maximum likelihood problem, a binary quadratic programming problem has to be solved. Fortunately, the low correlation between different users in the multiuser detection problem enables the use of the preprocessing algorithm. Simulations show that the preprocessing algorithm is able to compute almost all variables in the problem, even though the system is heavily loaded and affected by noise.
The optimum multiuser detection problem can be formulated as a maximum likelihood problem, which yields a binary quadratic programming problem to be solved. Generally this problem is NP-hard and is therefore hard to solve in real time. In this paper, a preprocessing algorithm is presented which makes it possible to detect some or all users optimally for a low computational cost if signature sequences with low cross correlation, e.g., Gold sequences, are used. The algorithm can be interpreted as, e.g., an adaptive tradeoff between parallel interference cancellation and successive interference cancellation. Simulations show that the preprocessing algorithm is able to optimally compute more than 94,% of the bits in the problem when the users are time-synchronous, even though the system is heavily loaded and affected by noise. Any remaining bits, not computed by the preprocessing algorithm, can either be computed by a suboptimal detector or an optimal detector. Simulations of the time-synchronous case show that if a suboptimal detector is chosen, the bit error rate (BER) rate is significantly reduced compared with using the suboptimal detector alone.
An evaluation of the performance of coexistent voice and best effort data users in Enhanced Uplink WCDMA is studied in this paper. The main focus is on deriving the capacity regions and compare with previous WCDMA releases. It is shown that the Enhanced Uplink yields a large capacity gain in many aspects for all fractions of voice users compared to previous WCDMA releases. It is also shown, by the cumulative distribution functions of noise rise at the capacity limits, that the best effort data users experience bad quality at lower noise rise than voice users. This means that the capacity is in fact limited by the best effort users.
The telecommunication industry is capitalizing on continuous evolution of the HSPA (high speed packet access) broadband technology, which is implemented in the form of 3GPP Release 7, 8, and 9. The novel solutions effectively meets the increased demands for higher data rates and greater cell capacity driven by the success of the mobile broadband. The HSPA 3GPP Release 7 supports the higher order modulation, multiple input, multiple output (MIMO) technology in the downlink, data rates of up to 28Mbps in the downlink, and 11.5 Mbps in the uplinks. The features of HSGPA 3GPP Release 8 include multicarrier operation, higher order modulation combined with MIMO, and enhancements to common states, and integrated mobile broadcast. The technology facilitates the existing WCDMA operators a cost-effective way of broadcasting data through 5MHz of unpaired spectrum. The ongoing works to standardization 3GPP Release 9 focuses on the support of features that further increases bit rates.
When the systems evolved from analog to digital, the performance was improved by the use of power control on the one hand and different modulations and coding schemes on the other. Condensing the available information we are able to propose a new concept of power control. The concept is applicable to real systems, since it uses the available measurements for estimating parameters necessary for the power control. It also supports the use of an adequate quality measure together with a quality specification supplied by the operator. We will use frequency hopping GSM as an example and the resulting control algorithm is ready for implementation in the software in the base stations where the output powers are computed. No modifications are needed in the GSM standard, the mobile terminals, the radio interfaces or in the base station transmitters. Finally we provide simulation results confirming the benefits of using the new concept for power control.
The problem to track time-varying parameters in cellular radio systems is studied, and the focus is on estimation based only on the signals that are readily available. Previous work have demonstrated very good performance, but were relying on analog measurement that are not available. Most of the information is lost due to quantization and sampling at a rate that might be as low as 2 Hz (GSM case). For that matter a maximum likelihood estimator have been designed and exemplified in the case of GSM. Simulations indicate good performance both when most parameters are varying slowly, and when subject to fast variations as in realistic cases. Since most computations take place in the base stations, the estimator is ready for implementation in a second generation wireless system. No update of the software in the mobile stations is needed.
A method and system for quality-based transmission power control in a cellular communications system (100) are disclosed, whereby a network operator can specify the transmission quality requirements using a measurement that better reflects the actual quality perceived by the users. All transmitter power levels in the network can be controlled by identical power regulators (200), each of which can adapt to individual traffic situations in order to achieve the specified quality. For example, in a GSM frequency-hopping network, the FER together with the parameters estimated from the current traffic situation (54), are mapped onto a target C/I (56), which in turn, the power control algorithm strives (16) to achieve (58, 60). Consequently, the power regulators can adapt to the traffic situation experienced by each receiver.
Time delays reduces the performance of any controlled system. If neglected in the design phase, the system may even become unstable when using the designed controller. Several power control strategies have been proposed in order to improve the capacity of cellular radio systems, but time delays are usually neglected. Here, it is shown that the problems can be handled by considering the time delays in the design phase in order to choose the appropriate parameter values. Most popular algorithms can be seen as special cases of an integrating controller. This structure is extended first to a proportional integrating (PI)-controller and then further on to a general linear controller of higher orders. Corresponding design procedures are outlined based on techniques, such as pole placement, from the field of automatic control. The PI-controller is a very appealing choice of structure, with better performance compared to an I-controller and less complex than a higher order controller. The benefits are further illuminated by network simulations.
In many real-time applications, sample values and time stamps are delivered in pairs, where sampling times are non-uniform. Frequency analysis using non-uniform data occurs in various real life problems and embedded systems, such as vibrational analysis in cars and control of packet network queue lengths. Our contribution is to first overview different ways to approximate the Fourier transform, and secondly to give analytical expressions for how non-uniform sampling affects these approximations. The results are expressed in terms of frequency windows describing how a single frequency in the continuous time signal is smeared out in the frequency domain, or, more precisely, in the expected value of the Fourier transform approximation.
In nonuniform sampling (NUS), signal amplitudes and time stamps are delivered in pairs. Several methods to compute an approximate Fourier transform (AFT) have appeared in literature, and their posterior properties in terms of alias suppression and leakage have been addressed. In this paper, the sampling times are assumed to be generated by a stochastic process. The main result gives the prior distribution of several AFTs expressed in terms of the true Fourier transform and variants of the characteristic function of the sampling time distribution. The result extends leakage and alias suppression with bias and variance terms due to NUS. Specific sampling processes as described in literature are analyzed in detail. The results are illustrated on simulated signals, with particular focus to the implications for spectral estimation.
Control signaling strategies for scheduling information in cellular OFDM systems are studied. A single-cell multiuser system model is formulated that provides system capacity estimates accounting for the signaling overhead. Different scheduling granularities are considered, including the one used in the specifications for the 3G Long Term Evolution (LTE). A greedy scheduling method is assumed, where each resource is assigned to the user for which it can support the highest number of bits. The simulation results indicate that the cost of control signaling does not outweigh the scheduling gain, when compared with a simple round-robin scheme that does not need signaling of scheduling information. Furthermore, in the studied scenario, joint coding and signaling of scheduling information over all selected users is found to be superior to separate coding and signaling for each user. The results also indicate that the scheduling granularity used for LTE provides better performance than the full granularity.
When operating a cellular radio system nearly at full capacity, admitting yet another user may jeopardize the stability of the system as well as the performance of the individual users. Therefore, proper admission control is crucial. The core idea in this work is to predict the relative load of the system, given that a user is admitted. Then, the user will be admitted if the predicted load in the specific cell, and in its neighbors, is below some threshold. This provide an interesting alternative to algorithms based on hard capacity, which might be utilizing the resources inefficiently in order to be robust. The proposed uplink admission control algorithm utilizes measurements readily available in the system. Simulations indicate performance improvements. Furthermore, multi-services are naturally handled, and availability of high data-rate services are automatically limited with respect to coverage, compared to services of lower data-rate.
The maximum capacity of a CDMA cellular system’s radio interface depends on the time varying radio environment. This makes it hard to establish the amount of currently available capacity. The received interference power is the primarily resource in the uplink. Ability to predict how different resource management decisions affect this spatial quantity is therefore of utmost importance. The uplink interference power is related to the uplink load through the pole equation. In this chapter, we discuss both theoretical and practical aspects of uplink load estimation.
Well-operating resource-management algorithms are crucial in wireless networks for ensuring the quality of service and, perhaps more importantly, for securing stability when operating at high load. These algorithms benefit from accurate feedback of the current network load. In the uplink of a code-division-multiple-access cellular network, the load is strongly related to the uplink noise rise, i.e., the ratio between total received power and background-noise power. This paper is primarily concerned with characterizing and approximating the uplink load. Two different load definitions are made. These relate to the received and transmitted carrier powers, respectively. Bounds that can be established in practice, e.g., before a resource decision is made, are used to develop a procedure for approximating the uplink load in practice. Furthermore, a stochastic approach to link budgets is used to establish the uplink load's role in the tradeoff between coverage and individual user satisfaction. Simulations indicate that the average error of the proposed load approximations is small for all load levels expected to appear in practice.
In the uplink of a WCDMA system, a natural choice of resource quantity is the uplink noise rise, i.e., total received power over noise power. Unfortunately this quantity is hard to measure and estimates are often noisy. This paper focuses on relative load which is closely related to the noise rise. Model-based signal processing with change detection techniques is herein used to suppress noise and minor oscillations while being alert on fast load changes. The time varying model identified in the process can also be used for prediction of future values, something which resource management algorithms can benefit from.
Radio resource management (RRM) in cellular radio system is an example of automatic control. The system performance may be increased by introducing decentralization, shorter delays and increased adaptation to local demands. However, it is hard to guarantee system stability without being, too conservative while using decentralized resource management. In this paper, two algorithms that both guarantee system stability and use local resource control are proposed for the uplink (mobile to base station). While one of the algorithms uses only local decisions, the other uses a central node to coordinate resources among different local nodes. In the chosen design approach, a feasible solution to the optimization problems corresponds to a stable system. Therefore, the algorithms will never assign resources that lead to an unstable system. Simulations indicate that the proposed algorithms also provide high capacity at any given uplink load level.
In the uplink of a WCDMA system, a natural choice of resource management control quantity is the uplink noise rise, i.e., total received power over noise power. Unfortunately this quantity is hard to measure. In this paper, we propose and evaluate a number of noise rise estimates which all rely on path gain measurements. These measurements can be made available either periodically or event-driven as described in 3GPP (Release 99). Simulations show that event-driven measurements yield comparable performance to periodic measurements, but with much fewer measurement reports. Despite severely limited path gain knowledge due to that some users report to another RNC, we still manage to estimate the uplink noise rise reasonably well.
All cellular radio systems have radio resource management algorithms which rely on some sort of resource quantity. In the uplink of a WCDMA system, a natural choice of such a quantity is the uplink noise rise, i.e., total received power over noise power. Unfortunately this quantity is hard to measure. In this paper, we propose and evaluate four different noise rise 711 estimates. The best performing estimate provides an average error of less than 1 dB for practical load levels. Due to low standard deviation of single estimates it is possible to apply a simple error correction algorithm.
All cellular radio systems depend on well performing radio resource management algorithms to efficiently utilize available resources. These algorithms make their decisions based on some sort of resource quantity. In the uplink of a WCDMA system, the total received power at the base stations is a natural choice of such a quantity. Unfortunately this quantity cannot be measured with enough accuracy to be used by resource management algorithms. One way of getting around this problem is to estimate a closely related quantity, namely the uplink noise rise. In this paper, we propose and evaluate four different methods to estimate the noise rise. The estimates are insensitive to users bit rate and use data readily available in the system. The best performing method estimates, on average, the uplink noise rise with an error of less than 1 dB for practical load scenarios.
The ultimate resource in wireless networks is transmission power. The system stability and the resource sharing algorithms all rely on well functioning power control. To realistically address resource management algorithms, it is important to consider fundamental limitations of the radio resource and of power control. Exact and approximate capacity expressions are derived and related to Quality of Service (QoS) requirements of services. Power control is subject to limited update rate, limited feedback bandwidth, time delays, measurement errors, feedback errors and filtering effects which all affect the resulting performance. Simulations further illustrate the hampering effects and motivates models of power control inaccuracies.
Power control is considered as an important means to combat near-far fading effects and maintain acceptable connections in wireless communications systems. When applying power control in practice, the performance is restricted by a number of fundamental limitations. Here, these are addressed from a control theory perspective. Limited update rate, limited feedback bandwidth, time delays, measurement errors, feedback errors, and filtering effects among other aspects all affect the resulting performance, and are related to radio channnel characteristics. Simulations further illustrate the hampering effects.
The primary goal of cellular radio systems is to provide communications services to a large number of mobile users. Due to the dramatic increase in number ofusers and their demand for more advanced services, the available resources haveto be utilized efficiently. Closed-loop power control is considered as an important component in this resource management.
For practical reasons, the powers have to be computed locally for each connection, though performance and stability depend on how the different connections interact. We consider the power control problem as a decentralized control system, consisting of interconnected local control loops. Methods from control theory are used to analyze existing algorithms locally and to design controllers with improved performance. Thereby, performance degradation due to time delays and nonlinearities, can be handled by careful controller design. On a global level, we provide results on stability and convergence of the designed controllers. The results are illustrated by simulations using both small and large-scale simulation environments.
The global communications systems critically rely on control algorithms of various kinds. In UMTS (universal mobile telephony system) - the third generation mobile telephony system just being launched, power control algorithms play an important role for efficient resource utilization. This chapter describes power control fundamentals including both theoretical and practical limitations. The relations to session management such as admission and congestion control is also addressed. Concepts and algorithms are illustrated by simple examples and simulations.
Radio network management simplification concerns to some extent the removal, not the simplification, of tasks. In this paper we present an approach for automatic network management in 3G long term evolution (LTE), namely, methods for automatic configuration of locally-unique physical cell identities and neighbor cell relation lists. We show that these issues can be removed from the list of planning tasks and completely replaced by autonomous algorithms. These algorithms make use of mobile measurements to detect local cell identity conflicts, resolve them, and to update the neighbor cell relation lists in the cells. The performance of the approach is determined using simulations of realistically deployed macro networks. The simulations illustrate the ability of the algorithms to resolve local cell identity conflicts. In particular, the algorithms are capable of both accommodating new cells and handling a worst case scenario where all cells are initiated with the same local cell identities and where neighbor cell relation lists are empty. The contributions in this paper are meant to aid operators by allowing them to replace time consuming and costly tasks with automatic mechanisms, thus, reducing operational expenditure.
Due to the rapid expansion of the cellular radio systems market, and the need for wireless multimedia services, the available resources have to be utilized efficently. A common strategy is to control the transmitter powers of the mobiles and base stations. However, when applying power control to real systems, a number of challenges are prevalent. The performance is limited by time delays, nonlinearities and the availability of measurements and adequate quality measures. In this paper we present a Power Regulator concept, which comprises an Unknown Input Observer, a Quality Mapper and a Power Control Algorithm. The applicability of the concept is exemplified using frequency hopping GSM, and simulations indicate benefits of employing the proposed concept.
The problem to track time-varying parameters in cellular radio systems is studied. The focus is on estimation based only on the signals that are readily available. Previous work has demonstrated very good performance relying on analog measurement. In a real system most of the information is lost due to quantization and sampling at a rate that might be as low as 2 Hz (GSM case). Therefore a different approach is required and for that matter a maximum likelihood estimator has been designed and exemplified in the case of GSM. The needed probability functions of the measurements cannot be described analytically. Instead point-mass approximations can be obtained from Monte-Carlo simulations for each point in a grid covering the interesting parameter space. The proposed algorithm can be tuned to track both slowly and fast varying parameters individually. Since most computations take place in the base stations, the estimator is ready for implementation in a second generation wireless system. No update of the software in the mobile stations is needed.
Thorough analytical analysis of cellular radio networks is difficult in general. Therefore simulation environments are adequate tools to gain understanding about the behaviour of algorithms used in cellular radio networks. In this report MOSE (MObile communications System Emulator) is described. The objective has been to develop an intuitive and user-friendly environment supported by a graphical user-interface. The implemented models include time-varying communication channels, co-channel interference, time delays and constraints. Several filtering and power control algorithms are implemented, and dedicated tests facilitate comparison with respect to different aspects.
The problem to track time-varying parameters in cellular radio systems is studied. The focus is on estimation based only on the signals that are readily available. Previous work have demonstrated very good performance relying on analog measurement. In a real system most of the information is lost due to quantization and sampling at a rate that might be as low as 2 Hz (GSM case). Therefore a different approach is required and for that matter a Maximum Likelihood Estimator has been designed and exemplified in the case of GSM. The needed probability functions of the measurements cannot be described analytically. Instead point-mass approximations can be obtained from Monte-Carlo simulations for each point in a grid covering the interesting parameter space. The proposed algorithm can be tuned to track both slowly and fastly varying parameters individually. Since most computations take place in the base stations, the estimator is ready for implementation in a second generation wireless system. No update of the software in the mobile stations is needed.
Many algorithms in communications systems can be considered as control loops, where the computed quantities depend on feedback information. A common scheme is to use increase/decrease signaling for bandwidth efficiency. Furthermore, the feedback information is delayed. The time delay itself, and even more pronounced in combination with nonlinearities, such as the increase/decrease mechanism, may cause oscillations and instabilities in the system. In this work, analysis methods based on root locus and describing functions are discussed. Design and tuning of algorithms are employed using pole placement techniques. Particular examples include clock synchronization in ADSL modems, control of available bit rate in data networks and, as studied in this project, distributed implementation of power control in cellular radio systems. The relevance of the methods is further illuminated by simulations.
Stability is a fundamental property desirable for any controlled system. We briefly review the root locus and describing function techniques, which are tools for stability analysis, and show how they can be applied to power control algorithms in cellular radio networks. The root locus method is used to find stability limits on controller parameters, and describing functions for predicting the presence of oscillations in the system. Thus these methods can be used to support the design phase, when deciding upon the appropriate controller parameters. These tools are demonstrated for various control algorithms and when different smoothing filters are applied. The analysis reveals that the distributed power control (DPC) algorithm, which works fine under ideal circumstances, yields an unstable system when subject to a small time delay. Furthermore, it is concluded that the performance with respect to stability is better when the measurements are averaged by an exponential forgetting filter than by the moving average filter.
When operating a cellular radio system at nearly full capacity, admitting yet another user may jeopardize the stability of the system as well as the performance of the individual users. Therefore, proper admission control is crucial. Prior art includes algorithms which are limiting the number of users or the uplink interference per cell. Both are known to yield roughly the same performance, but the former is difficult to configure, and the latter is based on a quantity, which is hard to measure accurately. The core idea in this work is to predict the relative load of the system directly, given that a user is admitted. Then, the user will be admitted if the predicted load in the specific cell, and in its neighbors, is below some threshold. The proposed uplink relative load estimate is focused on WCDMA. It utilizes measurements readily available in that system, either periodically scheduled or from handover events. Multi-services are naturally handled, and availability of high data-rate services are automatically limited with respect to coverage, compared to services of lower data-rate. Simulations indicate that the admission control operates satisfactory in different traffic situations with a universal parameter setting. Furthermore, the reporting overhead with periodical measurements can be avoided, since handover event-driven measurements yield roughly the same performance.
The limiting factor in the uplink of all CDMA cellular systems is the relation between uplink noise rise and intended coverage. In link budgets, noise rise is usually simply handled as a constant contribution to the background noise in logarithmic scale, often referred to as interference margin. In practice, however, it is not constant. We model the uplink noise rise as a lognormal distribution, and investigate the impact to link budgets. Simulations and numerical calculations show that the uplink noise rise variance does not critically affect the uplink capacity and coverage. System feasibility and its relation to the uplink load is also discussed. It is shown that approximative load expressions provides an upper bound on the uplink load and therefore they can be used to imply system feasibility. Furthermore, the uplink load expressions provide accurate approximations of the load given that the load is within the practical limits given by the link budgets.
The global communication systems critically rely on control algorithms of various kinds. In universal mobile telephony system (UMTS)-the third generation mobile telephony system just being launched-power control algorithms play an important role for efficient resource utilization. This survey article describes and discusses relevant aspects of UMTS power control with emphasis on practical issues, using an automatic control framework. Generally, power control of each connection is distributedly implemented as cascade control, with an inner loop to compensate for fast variations and an outer loop focusing on longer term statistics. These control loops are interrelated via complex connections, which affect important issues such as capacity, load and stability. Therefore, both local and global properties are important. The concepts and algorithms are illustrated by simple examples and simulations.
Drive tests are important means to evaluate critical properties of a wireless network in operation. The network coverage is vital, and therefore, the received power of pilot signals from the base stations are monitored to estimate the spatial distributions and variations of the power gain. With uniform time-sampling and a varying velocity, the typical temporal filter fails to extract the interesting information. In this paper we apply convolutional spatial filtering, both causal and non-causal, to resolve the problem. Relations to spatial data analysis methods are also commented upon. Simulations indicate significant improvements.
The primary goal of cellular radio systems is to provide communications services to a large number of mobile users. Due to the dramatic increase of this market, the available resources have to be utilized efficiently. Closed-loop power control is considered as an important component in these resource management algorithms. Here, relevant aspects on power control are discussed, using an automatic control framework. Generally, power control strategies are implemented as cascade control, with an inner loop to compensate for fast variations and an outer loop focusing on longer term statistics. Issues as capacity, load and stability are discussed and related to whether it is possible to accommodate the requirements of all users or not. The operation of such algorithms are illustrated by simulations.
The global communications systems critically relyon control algorithms of various kinds. In wireless communications systems, power control algorithms play an important role for efficient resource utilization. This survey article discusses relevant aspects of power control with emphasis on practical issues, using an automatic control framework. Generally, power control of each connection is distributedly implemented as cascade control, with an inner loop to compensate for fast variations and an outerloop focusing on longer term statistics. These control loops are interrelated via complex connections, which affect important issues such as capacity, load and stability. Therefore, both local and global properties are important. The concepts and algorithms are illustrated by simple examples and simulations.