Expected high demand of user applications in the WLAN is a driver for WLANs to share radio resources more efficiently. The move to 802.11be with OFDMA and MU-MIMO makes Radio Resource Management (RRM) a multi-dimensional problem in a complex wireless environment. Traditionally, the way that an RRM problem is formulated always leads to either a large state space or action space, which makes reinforcement learning impossible to be applied. In this paper, we propose a Sequential State Q-learning algorithm (SSQL) aimed at solving the Resource Unit (RU) allocation for scheduled uplink transmission to maximize system bitrate in a multi-AP 802.11be OFDMA network. The AP acts as the agent with the serving stations as ‘states’ and their RU allocations as ‘actions’. The AP observes the wireless environment, continuously refreshing the Q-values of the state-action pairs and outputs the RU allocation to optimize the objective. Through simulations, we demonstrated that the performance of SSQL is 89.67% of the global optimal with very fast convergence, which makes it more practical for use in varying wireless networks.

In this paper we evaluate the game-theory approach we have used for radio resource block allocation in sliced multi-cell networks with distributed control against a centralized control strategy. This is done in the context of an approach that allocates resources according to the QoS requirements of users. The objective is to see whether the game-theory approach is worth using throughout a network with mixed decentralized and centralized control and the conclusion is that the performance of the game-theory approach is equally suitable for both types.

In this paper, we demonstrate how isolation can be achieved in dynamic network slicing using an appropriate Connection Admission Control (CAC) mechanism. The scenario adopted is a multi-cell OFDMA network and the resource allocation is performed using a non-cooperative game. Simulation results show that such an approach leads to implicit isolation (a term we define in the paper) being achieved, at the same time reaping the capacity benefits of dynamic slicing.

In this paper, we use a Spectrum Sharing/allocation algorithm to implement a Cognitive Radio network without spectral awareness. This allows radio resources to be allocated to primary users and to secondary users in such a way that primary system and secondary system are aware of each other. By doing this, sensing of spectrum holes is avoided but the primary users will be protected and will always be allocated sufficient bandwidth to meet their QoS requirements. However, secondary users also have the concept of QoS and only those that can be given sufficient resources are actually allocated any, so avoiding wasting resources on users that cannot meet their QoS requirements. The scenario adopted is a multi-cell OFDMA network and the resource allocation is formulated as a non-cooperative game: each cell is a player whose aim is to maximise the number of secondary users that can reach their bitrates subject to the premise that all primary users in that cell can achieve their bitrate. Once spectrum is allocated we implement a power-minimisation algorithm to minimise the power consumption in the network while maintaining the number of users meeting their QoS requirements. Simulation results show the benefit of the approach.

In today's wireless communications, the need to consider the Quality of Service (QoS) requirements of individual users is gaining widespread acceptance. Previous work showed that an OFDMA spectrum sharing network solution based on semi-smart antennas gave a performance improvement of around 10% in terms of the number of qualified users. Optimization of the semi-smart antenna radiation patterns using Genetic Algorithm produced a dynamic cell boundary and flexible cell coverage. However in a realistic network, it is not sensible to expect cell boundaries to change rapidly as this would lead to increased handovers and signalling. In this paper the optimization approach is tested with users moving as movement would lead to the greatest likelihood of patterns changing and hence increased handovers to research when to change antenna pattern with user movement. This paper proposes a periodic optimization scheme that is found to lead to a significant improvement in the ratio of qualified users.

Mobility load balancing MLB redistributes the traffic load across the networks to improve the spectrum utilisation. This paper proposes a self-organising cluster-based cooperative load balancing scheme to overcome the problems faced by MLB. The proposed scheme is composed of a cell clustering stage and a cooperative traffic shifting stage. In the cell clustering stage, a user-vote model is proposed to address the virtual partner problem. In the cooperative traffic shifting stage, both inter-cluster and intra-cluster cooperations are developed. A relative load response model is designed as the inter-cluster cooperation mechanism to mitigate the aggravating load problem. Within each cluster, a traffic offloading optimisation algorithm is designed to reduce the hot-spot cell's load and also to minimise its partners' average call blocking probability. Simulation results show that the user-vote-assisted clustering algorithm can select two suitable partners to effectively reduce call blocking probability and decrease the number of handover offset adjustments. The relative load response model can address public partner being heavily loaded through cooperation between clusters. The effectiveness of the traffic offloading optimisation algorithm is both mathematically proven and validated by simulation. Results show that the performance of the proposed cluster-based cooperative load balancing scheme outperforms the conventional MLB. Copyright © 2013 John Wiley & Sons, Ltd.

Teamwork is a very important attribute for future engineers. China graduates a large number of engineering graduates every year, so it is necessary to investigate the teamwork knowledge and performance level of the Chinese engineering students, and work out a better mechanism of teamwork teaching for them. This work investigates the team knowledge and team performance of the Chinese engineering students in a Year 3 senior technical module — Software Engineering, in which teamwork skills are one of the course objectives. The test results demonstrated that the declarative knowledge of the Year 3 students on team working increased through the years of learning but it was not successfully transferred into action, the skill based outcome. It was found that the participation rate for teamwork training in the technical module was low, and students focused more on the technical production. It was suggested to include the peer rating of team citizenship with a certain percentage (5–10%) in the final coursework mark, and also a certain percentage for individual contribution (5–10%). This will switch the product oriented to both teamwork and product oriented, and the individual contribution assessment will prevent social loafing and hitchhiking.

Teamwork has been considered as an important learning outcome for engineering graduates. A pilot study on teamwork training was conducted in a joint degree programme between a leading British university and a top Chinese university in 2011. A supplementary experiment in the module "Personal Development Plan" was carried out using a large sample (624 students) to compare different methods for forming groups, taking into account both team and academic performance. For the first time this work has attempted to introduce some tests and checks in the group project of a technical module. This paper reports the new findings from the supplementary experiments in the Personal Development Plan module and the technical module. An improved strategy for teamwork teaching in undergraduate engineering programmes, particularly in China, is now suggested: students would learn teamwork skills in the PDP module in the first year of the university; attend selective workshops for the practical instruction to transfer knowledge into action; and complete some technical coursework in groups in senior technical modules.

Location based services are the hottest applications on mobile devices nowadays and the growth is continuing. Indoor wireless positioning is the key technology to enable location based services to work well indoors, where GPS normally could not work. Bluetooth has been widely used in mobile devices like phone, PAD etc. therefore Bluetooth based indoor positioning has great market potential. Radio Signal Strength (RSS) is a key parameter for wireless positioning. New Bluetooth standard (since version 2.1) enables RSS to be discovered without time consuming pre-connection. In this research, general wireless positioning technologies are firstly analysed. Then RSS based Bluetooth positioning using the new feature is studied. The mathematical model is established to analyse the relation between RSS and the distance between two Bluetooth devices. Three distance-based algorithms are used for Bluetooth positioning: Least Square Estimation, Three-border and Centroid Method. Comparison results are analysed and the ways to improve the positioning accuracy are discussed.

The need for teamwork skills has been recognised as one of the key requirements for engineering graduates by industries world-wide, including in China. A pilot on teamwork training was conducted in a joint degree programme between a leading British university and a top Chinese university in 2011. This paper attempts to evaluate the effectiveness of this cooperative learning practice to Chinese engineering students and to identify the gap between the declarative knowledge and the skill-based outcomes. This evaluation focuses on the open-ended and qualitative items in students' expectations agreements, team function evaluation forms, peer ratings, and questionnaires. The data collected were analysed using descriptive statistics, with class observation and informal interview responses also being discussed. This qualitative study provides a good supplement to the previous quantitative findings and contributes to understanding by displaying how students perceived a Cooperative Learning practice in a mainland Chinese context, and how they reacted to the experience. It also provides an insight into the underlying cultural considerations behind the team behaviour. Instructors can design and improve team tasks for Chinese students based on these findings.

Teamwork has been considered as one of the important learning outcomes for engineering graduates. Industry sees higher education as being where graduates should be prepared with these professional skills. Every year, a lot of engineering students graduate in China and how best to train these students to be good team players is an urgent and important need. This paper describes a planned, improved mechanism for teamwork teaching on a joint degree programme between a top Chinese university and a key British university. A previous experiment about teamwork teaching to Chinese engineering students was conducted in a Personal Development Plan (PDP) module that takes professional skills as its main objectives. This work describes an improved approach to teamwork teaching based on the experience derived from the previous practice and a summary of students' feedback about PDP that was collected from several questionnaire-based semi-structured interviews. The improved approach will be conducted in both the PDP module and a technical module - Software Engineering.

Cooperative spectrum sensing is employed in Cognitive Radio (CR) networks to reliably detect Primary User (PU) transmissions by fusing the sensed data of multiple Secondary Users (SUs). The local detection reliability of an individual SU is closely related to its channel condition. In this paper, we propose a scheme that uses SNR to evaluate the reliability of each individual SU's local decision. We optimize the number of SUs for the sensing based on their channel conditions to achieve the optimal global detection probability at the fusion centre. Simulation results show that the proposed algorithm is robust against noise uncertainty with the optimal number of SUs and better receiver operating characteristic (ROC) performance is obtained in comparison to conventional schemes.

Interference mitigation between femtocells and the surrounding macrocells is one of the major challenges in femtocell deployment. This paper proposes a system architecture of using TV White Space (TVWS) in LTE femtocell networks, which includes: (i) a Geo-location database to obtain locally available TVWS information, and (ii) a new resource allocation scheme using the locally available TVWS to mitigate the downlink cross-tier interference between macrocell users and nearby femtocells. A two-tier multi-femtocell simulator is established to demonstrate the system performance. Simulations at different scenarios are conducted to compare the performance of the traditional all-shared resource allocation scheme, dynamic resource partitioning scheme and the proposed scheme. Simulation results show that the proposed scheme has better downlink interference mitigation performance in comparison with the other two schemes.

Teamwork skills are recognized internationally as important skills for engineering professionals. Literature shows that professional skills, especially teamwork skills, have not been included into the curriculum design and assessment in Chinese engineering programmes, and little work has been done to find the effective way to learn teamwork for engineering students in academic settings in China. This work attempts to implement successful cooperative learning practices from the West to a Personal Development Plan module with teamwork skills as one of its main teaching objectives in a joint Sino-UK degree programme in China. This paper reports the real situation of cooperative learning for Chinese engineering students. Experimental results indicate that there is no significant difference between different grouping methods on both academic and teamwork performance, although self-selected groups do not appear to be the best approach for Chinese students. No statistical correlation was observed between peer rating and the mark obtained for the task. Students can rate themselves and others, and different genders without bias. In the MBTI test, we found higher frequencies of Feeling over Thinking, and Judging over Perceiving. These students need more knowledge and training on conflict resolution skills and multi-task management skills to overcome their intrinsic weakness in cooperative learning.

Teamwork skills have been acknowledged as the key skills of potential engineers by industries internationally, including Chinese enterprises. This paper reports research in a joint Sino-UK programme in China on how teamwork can best be taught. Literature shows that little work has been done to find effective ways to teach teamwork to engineering students in China. This work attempts to implement successful cooperative learning practices of the West to a module that takes teamwork skills as one of its key teaching objectives and tries to design a new model for instructors to follow to teach teamwork effectively to Chinese engineering students. Preliminary results show that Chinese engineering students need training and practices in teamwork skills, and the situation is not exactly the same as previous research in other Confucius Heritage Culture countries.

Future wireless multimedia services require a quality of service guarantee and ubiquitous high data rate for all users. In this paper a scheduling algorithm is proposed for multimedia services in relay-based cellular networks. The decode-and-forwarding relaying protocol with transparent frame structure is used. The scheduling priority takes into account the packet delay and maximum tolerance packet loss probability for both direct-link users and relay-link users. Since the relay-link users have two hops, the priority factor of the first hop of relay-link users is defined as the average priority factors of relay-link users in the second hop, and a match factor is proposed considering the capacity match between the first hop link and the second hop link for each relay. Simulation results show that the proposed algorithm achieves overwhelming significant performance gain on the average packet delay and packet loss rate, although suffering some throughput and fairness reduction.

Load balancing (LB) is an important function of the self-organizing network (SON) for coping with the uneven load distribution to achieve higher spectrum efficiency and lower operational expenditure. This paper proposes a cluster based self-organizing LB scheme, which employs a user-vote mechanism to avoid the ‘virtual partner’ problem experienced by current LB schemes with the load-based partner selection. The user-vote can assist the hot-spot base station (BS) to efficiently select partner BSs for constructing its cluster, and then shift the traffic to the partners within the cluster. Simulation results show that the proposed scheme can effectively solve the ‘virtual partner’ problem. Furthermore, it can reduce the call blocking rate via a small number of partner BSs.

This paper considers using wideband slope as the measure to compare the energy efficiency between different transmission schemes for wideband cooperative wireless relay networks. Two different scenarios are considered (relay with unlimited power supply and relay with limited power supply) and two different relay strategies (amplify and forward, decode and forward) with direct transmission being used as a benchmark. The condition for getting optimal energy efficiency is obtained using theoretical analysis and simulation. The results show that (i) the source-relay distance is the most important factor influencing the energy efficiency of the whole system and (ii) the conditions for optimum energy efficiency depend on the type of relay mode.

This paper proposes a learning approach to solve adaptive Connection Admission Control (CAC) schemes in future wireless networks. Real time connections (that require lower delay bounds than non-real-time) are subdivided into hard realtime (requiring constant bandwidth capacity) or adaptive (that have flexible bandwidth requirements). The CAC for such a mix of traffic types is a complex constraint reinforcement learning problem with noisy fitness. Noise deteriorates the final location and quality of the optimum, and brings a lot of fitness fluctuation in the boundary of feasible and infeasible region. This paper proposes a novel approach that learns adaptive CAC policies through NEAT combined with Superiority of Feasible Points. The objective is to maximize the network revenue and also maintain predefined several QoS constraints.

In a distributed antenna system, the optimal antenna deployment design scheme is proposed, in which both the location and the number of the distributed antennas (called access point, AP) are considered for energy efficiency. By minimizing the average distance between users and the APs, the optimal AP distribution is given. The optimal number of APs can be obtained considering both the circuit power and the transmission power for each AP. The simulation results show that the transmission power can be reduced by optimal AP location design. The simulation also considered the trade-off between the circuit power and the transmission power consumption and the total system power can be reduced significantly.

In coordinated multi-point transmission (CoMP) systems, the optimal remote radio unit (RRU) location is analyzed theoretically and a RRU location design scheme for energy efficiency in practical scenarios is given. An average minimum access distance criterion is given for RRU location optimization. By minimizing the average distance between users and RRU, the optimal RRU distribution can be obtained when users are located uniformly in the cell. Taking into account the fact that user distribution will not be completely uniform in a practical environment, the k-means clustering algorithm is used to get the optimized RRU deployment in a practical user distribution. Simulation results show that the uplink transmission power can be greatly reduced with the RRU optimized location design in both the uniform and non-uniform user distribution.

Orthogonal frequency division multiplexing (OFDMA) offers great spectrum efficiency and flexible frequency allocation to users without intra-cell interferences in LTE system. However, the cell edge users will experience high interferences from neighbouring cells. Many frequency reuse schemes have been proposed for improving the Signal to Interference and Noise Ratio (SINR) performance for cell edge users, most of them dividing available frequencies into groups for cell centre and cell edge users. In this research, we combine the traditional frequency scheme with novel semi-smart antennas and learning algorithm - Genetic Algorithm (GA). The semi-smart antennas can produce flexible coverage patterns for base stations (BSs) and the learning algorithm can coordinate the coverage patterns between BSs to minimise interferences for mobile units (MUs). A system level simulation contains 25 BSs and 1000 MUs has been developed. Simulation results show that the proposed scheme improves the total traffic load and reduces antenna propagation power for all cells compares to system with fixed coverage patterns.

We analyse different worm and patch propagation models along with the ones we have developed and evaluated as a part of our ongoing passive P2P worm & patch modelling project. This is followed by a brief discussion on worm detection mechanisms proposed by various authors. Towards the very end of this article, we propose a distributed framework for passive worm throttling in P2P networks and discuss its feasibility and efficiency keeping in view different design considerations.

The power allocation problem with co-channel interference is studied in multi-cell OFDMA cellular relay systems. The multi-cell non-cooperative power allocation game model is given in the first time subslot for base stations (BSs) and in the second time subslot for relay stations (RSs) respectively. In all the cells, each transmitter (BS or RS) controls the power allocation on each subchannel to maximize its own utility in a distributed way. In the first time subslot, a match factor is defined for considering the mismatch between the first hop link data rate and the second hop link data rate and the pricing factor for the RS will be adjusted adaptively by this match factor. As a Nash equilibrium is used to determine the solution of this problem, the existence and uniqueness of the Nash equilibrium are studied. The simulation results of system throughput and transmission power of BS and RS is given with different pricing factors. Compared with equal power allocation, the system throughput is improved and transmission power is reduced.

A load-based relay selection algorithm that improves the fairness of resource allocation is proposed for relay-based OFDMA systems. This algorithm takes into account the traffic load condition (bandwidth requirement) of relay link users and direct link users. The transmission mode (direct transmission mode or relay transmission mode) of each user will be adjusted based on the user average data rate; this will make the long-term average data rate of relay link users and direct link users equal so that user fairness is enhanced. The simulation results show that the proposed algorithm will improve the user fairness compared with a popular traditional relay selection algorithm, for both uniform distribution and hot-spot scenarios.

In this paper the fairness of the subchannel allocation problem for relay based OFDMA systems is studied. The proportional fairness algorithm is extended to a two-hop scenario to ensure that both direct-link users and relay-link users are fairly allocated capacity; this approach is called the "two-hop proportional fairness scheduling algorithm". The fairness allocation problem is considered both in the first time subslot between direct-link users and relay stations, and the second time subslot among relay-link users. Simulation results show that this algorithm achieves an overwhelming performance on the long-term fairness of the user data rate, although suffering some throughput reduction.

Managing congestion is essential to maximise carried traffic in a mobile network and in this paper a technique is presented that uses learning to cooperatively change antenna patterns across a cluster of cells, so minimising blocking. Moreover, the technique allows prediction of antenna patterns, leading to more efficient operation as the optimum patterns do not have to be recalculated each time.

In this paper, a novel Distributed Cross-Layer QoS (DCLQ) architecture based on node disjoint multipath routing is proposed to provide QoS guarantees for realtime traffic and best-effort traffic in mobile ad hoc networks. Without any extra control overhead, DCLQ can schedule packets of real-time flows according to their perhop QoS requirements. DCLQ implements per-hop delay QoS-aware priority scheduling and QoS consideration of MAC layer to ensure that real-time flows and best-effort flows can achieve their desired service level.

This paper proposes a new method of balancing traffic load in mobile cellular networks by using Case-Based Reasoning (CBR) to learn traffic patterns at periods of congestion, the obtained traffic patterns then being used to control co-operating semi-smart antennas to optimise the radio coverage, hence minimising the effects of the congestion. Unlike previous work, this scheme does not require calculating the optimum patterns each time. The emphasis of this paper is to demonstrate case matching of congestion by CBR with a particular study of the sensitivity to the similarity function.

Future mobile ad hoc networks (MANETs) are expected to be based on all-IP architecture and be capable of carrying multitudinous real-time multimedia applications such as voice, video and data. It is very necessary for MANETs to have a reliable and efficient routing and quality of service (QoS) mechanism to support diverse applications which have varying and stringent requirements for delay, jitter, bandwidth, packets loss. Providing multipath routing is beneficial to avoid traffic congestion and break in communication in MANETs where routes are disconnected frequently due to mobility. Differentiated Services (DiffServ) which have simple, efficient and scalable characteristics can be used to classify network traffic into different priority levels and apply different scheduling and queuing mechanisms to obtain QoS guarantees. In this paper, we propose a practical node-disjoint multipath QoS routing protocol of supporting DiffServ (MQRD), which provides low routing overhead and end-to-end QoS support. Simulation results show that MQRD achieves better performance in terms of packet delivery ratio and average delay.

The paper investigates a new load balancing scheme for mobile networks that changes cellular coverage in real time according to the current geographic traffic distribution. A bubble oscillation algorithm from our previous work is customized to work with WCDMA mobile networks with simple semi-smart antennas. After the algorithm converges, the sector sizes for each cell are re-adjusted using a heuristic method to balance the traffic load within each cell. The results of tests performed on a WCDMA network simulator show that significant capacity improvement can be obtained for uneven traffic by using the intelligent control algorithm and low cost semi-smart antennas.

In current commercial wireless networks the service providers mediate between end users and network operators. The service provider can be a good candidate to integrate the different network technologies in a flexible and expandable platform. This paper presents a framework for a service provider to perform resource management in heterogeneous wireless networks. We analyse the characteristics of the service provider, summarize the required management functions and propose an architecture that allows the service provider to support real time resource management and seamless service handover in heterogeneous wireless networks. Additionally, the resource management functions based on two service level agreements are described, and an algorithm to perform QoS degrades of live connections has been implemented. A computer simulator has been developed to demonstrate the functionality and evaluate the performance of the architecture.

Resource management is one of the most important aspects in 3G network as it controls the system capacity. With the aim of giving the maximum benefit to users, intelligent agents have been introduced to give a more flexible resource management system. Within this work, case-based reasoning is proposed as the method by which the agent monitors and recognises the congestion pattern as it occurs and determines the best policy in order to maintain the system quality of service according to the service level agreement.

This paper investigates a new load balancing scheme for mobile networks that changes cellular coverage according to the geographic traffic distribution in real time. The performance of the whole cellular network is improved by contracting the antenna pattern around a traffic "hot spot" and expanding adjacent cells coverage to fill in the coverage loss. This is essentially a constrained multidimensional optimization problem. A novel bubble oscillation algorithm is proposed to address this problem. Any unserved traffic in the network is absorbed by the geographic load balancing in a similar way that a vacuum between bubbles is filled by bubble oscillations. Simulations have been performed to evaluate the system performance for different traffic scenarios, and the results are presented. Some discussions on this algorithm are also presented. The bubble oscillation algorithm described has the potential of being used in other similar multidimensional resource allocation problems.

An on-demand node-disjoint multipath routing protocol is proposed to overcome the shortcomings of on-demand unipath routing protocols like AODV and DSR. The protocol has two novel aspects compared to the other on-demand multipath protocols: it reduces routing overhead dramatically and achieves multiple node-disjoint routing paths. Simulation results show that the proposed protocol achieves lower data delay and control overhead as well as higher packet delivery ratio.

With the underlying W-CDMA technique in 3G networks, resource management is a very significant issue as it can directly influence the system capacity and also lead to system QoS. However, the resource can be dynamically managed in order to maintain the QoS according to the SLA. In this paper, CBR is used as part of an intelligent-based agent management system. It uses information from previously managed situations to maintain the QoS in order to meet the SLA. The results illustrate the performance of an agent in traffic pattern recognition in order to identify the specific type of problem and finally propose the right solution.

Wireless ad hoc networks are characterized by the use of wireless links with limited bandwidth, dynamically varying network topology and multi-hop connectivity. AODV and DSR are the two most widely studied on-demand ad hoc routing protocols. Previous work has shown some limitations of the two protocols: whenever there is a link break on the active route, each of the two routing protocols has to invoke a route discovery process. This leads to increase in both delay and control overhead as well as decrease in packet delivery ratio. To alleviate these problems, we modify and extend AODV to include the path accumulation feature of DSR in route request/reply packets so that much lower route overhead is employed to discover multiple node-disjoint routing paths. The extended AODV is called Reliable Node-Disjoint Multipath Routing Protocol (NDMR), which has two novel aspects compared to the other on-demand multipath protocols: it reduces routing overhead dramatically and achieves multiple node-disjoint routing paths. Simulation results show that performance of NDMR is much better than that of AODV and DSR.

Managing resources to meet service level agreements is more complex in 3G networks because of the underlying W-CDMA technology. This paper introduces the use of CBR in part of the intelligent agent management system managing resources. CBR uses information from previously managed situations to maintain the QoS in order to meet the SLAs. The results demonstrate a useful technique in this context.

IEEE 802.11 based WLANs have been widely deployed. Currently research is concentrating on how to find the best location for these access points plus tuning their antennas in order to seamlessly cover large areas. With more and more WLAN users, the air interface acts as bottleneck even in high-speed WLAN systems such as IEEE 802.11a. To improve the overall performance of IEEE 802.11 WLAN systems under congestion conditions, an agent-based radio resource management system is proposed that can dynamically change an AP's radio coverage pattern in cooperation with surrounding APs. A low-cost four sector semismart antenna array is used for access points. In this paper we present results from a simulation showing system performance. The use of intelligent agents and negotiations for indoor radio resource management is presented and discussed.

This paper proposes a new power control strategy during soft handover in WCDMA systems. According to the link qualities of the down link channels involved in soft handover, the transmit powers of the base stations in the active set are dynamically allocated. This new optimized power control scheme reduces the additional interference caused by the multiple site transmission during soft handover. Compared with the unbalanced and balanced power control scheme adopted by 3GPP, the proposed scheme shows better performance. It increases the downlink capacity and makes the whole system more robust to the fluctuating attenuation of the radio environment.

In this paper, we investigate a novel distributed load balance scheme for cellular networks, which intelligently changes cellular coverage according to the geographic traffic distribution in real time. The performance of the whole cellular network can be improved by contracting the base station antenna pattern around a traffic "hot spot" and expanding adjacent cells' coverage to fill in the loss. A cooperative negotiation approach with semi-smart antennas for cellular network coverage control is described in this paper. By the use of negotiations between adjacent base stations, optimum local coverage agreements can be achieved in the context of the whole cellular network. Results showing the advantage of this technique are also presented.

The performance of CDMA cellular networks can be improved by contracting the base station antenna pattern around the source of peak traffic and expanding adjacent cells coverage loss. A novel distributed load-balancing scheme for cellular networks, which intelligently changes cellular coverage according to the geographic traffic distribution in real time has been investigated. A cooperative negotiation approach with semi-smart antennas for the real-time control of cellular network coverage is used. By the use of real time negotiations between adjacent base stations, optimum local coverage agreements can be reached in the context of the whole cellular network. In this paper we concentrate on the description of how the desired cell shaping can be achieved by using antenna pattern synthesis techniques. Results showing the advantage of such a distributed load-balancing scheme are also presented.

We investigate a novel geographic load-balancing scheme for cellular networks that intelligently changes cellular coverage according to the geographic traffic distribution in real time. A cooperative negotiation approach for the real-time control of cellular network coverage is described. The performance of the whole cellular network is improved by contracting and shaping the antenna radiation pattern around a traffic "hot spot" and expanding adjacent cells coverage to fill in the coverage loss. By the use of real time cooperative negotiations between base stations and associated antennas, a near optimal local coverage agreement is reached in the context of the whole cellular network. Results showing the advantage of this technique are presented. Global optimization using constrained real-coded genetic algorithms (RCGA) provides a benchmark. Convergence using penalty functions to manage the constraints was first investigated but gave poor results. A transformation of the problem space is used to remove the constraints, and a criterion that is necessary for successful transformations is explained.

Abstract Soft handover is analysed and optimized in the downlink direction of a WCDMA system in this paper. Downlink is chosen because the asymmetric nature of most new services supported by the next generation of mobile networks requires more capacity in that direction, and so this is likely to be the limiting factor. The study also sets out to resolve the often controversial opinions about the system level performance with soft handover in the downlink direction. Here, the performance of soft handover is investigated on the link level and on the system level separately. Apart from power control, the cell‐selection scheme and power limits (which are ignored by most of the previous work in the literature) are also included. Results show that from the point of view of link quality, soft handover can prevent the downlink traffic channel power going beyond the power limit. From the system level point of view, the downlink capacity can be increased by choosing a proper soft handover overhead. The optimum value of the overhead depends closely on the cell‐selection threshold and the radio environment. The paper proves that soft handover is an effective way for interference‐reduction and radio resource optimization in the downlink direction for WCDMA systems. Copyright © 2003 John Wiley & Sons, Ltd.

In this paper, we investigate a novel geographic load balance scheme, which intelligently changes cellular coverage according to the geographic traffic distribution in real time. The performance of the whole cellular network can be improved by contracting the antenna pattern around the source of peak traffic and expanding adjacent cells coverage to fill in the coverage loss. Our previous global optimization work based on scenarios with non-uniformly distributed traffic scenarios has shown the improvement of system capacity of such a dynamical cellular coverage planning scheme exceeds 20%. A cooperative negotiation approach for the real-time control of cellular network coverage is described in this paper. By the use of real time negotiations between base stations and associated antennas, some optimum local coverage agreements can be reached in the context of the whole cellular network.The simulation results using 200 continuous traffic snapshots are presented and followed by some conclusions finally.

In this paper the potential of a smart antenna based dynamic cell size and shape control scheme is assessed. By intelligent control of antenna pattern, the whole cellular network performance can be improved by contracting the antenna pattern around the source of peak traffic and expanding adjacent cells coverage to fill in the coverage loss. We perform a constrained optimization of antenna patterns by using real-coded genetic algorithms (RCGA), and develop a CDMA cellular system simulator to evaluate the overall improvement of the system performance. A transformation of the problem space is used to remove the principal power constraint. A problem with the intuitive transformation is shown and a revised one is presented. This highlights a problem with transformation-based methods in genetic algorithms. While the aim of transformation is to speed convergence, a bad transformation can be counter-productive. Optimization results for two scenarios show potential capacity improvement exceeding 20%.

As the demand for mobile services has increased, the need for an efficient allocation of channels is essential to ensure good performance, given the limited spectrum available. Techniques for increasing flexibility in radio resource acquisition are needed to handle the heterogeneity of services and bit rates to be supported in the forthcoming generations of mobile communications. To improve the performance and efficiency of the channel allocation, we propose the use of a particular agent architecture that allows base stations to be more flexible and intelligent, including planning to attempt to balance the load in advance of reactive requests. The simulation results prove that the use of intelligent agents controlling the allocation of channels is feasible and the agent negotiation is an important feature of the system in order to improve perceived quality of service and to improve the load balancing of the traffic.

Resource flexibility is one of the most important requirements in the next generation of mobile communications. Techniques are required to increase the flexibility of the network to deal with new services and the consequent new traffic profiles and characteristics. This paper investigates some of the drawbacks of fully reactive channel allocation schemes and proposes a more flexible scheme using intelligent agents that will lead to an efficient solution under moderate and heavy loads. The agent architecture adopted provides greater autonomy to the base stations and a method for allowing cooperation and negotiation between them; this autonomy and cooperation allows an increase in flexibility to deal with new traffic situations and an increase of the robustness of the network as a whole.

This paper proposes a new application of neural networks in telecommunications network simulation. A high-level abstracted analytical model, based on intensive investigation of packet queuing behaviour substantially speeds up the basic simulation. Comparing the results from the model against the behaviour of a testbed leads to some difference between the model results and the experimental validation, an expected result given the level of abstraction. A neural network is applied to learn the relation between the model parameters and the output difference, and neural network prediction is used to 'fine-tune' the model accordingly. Results indicate that the proposed hybrid method (using the neural network to tune the abstracted model) achieves fast simulation and also remains accurate. This approach is particularly useful in the area of large-scale network designing and planning, where concern is more about the overall performance of the network than the detailed structure of a network node.

The economic evaluation of a mature ATM network is presented. The authors discuss the issues involved and present two examples. Four customer categories are taken into account, namely residential, small business, medium business, and large business customers. The aim is to introduce a simple meaningful model, which incorporates the most important factors that influence the economic viability of an asynchronous transfer mode (ATM) network, and to present the limits and limitations of the area of economic evaluation. The revenue, cost, and net income (of the network operator) are calculated for two different scenarios, that is with and without residential customers.>

Parallel processing techniques that may enhance the performance of simulation methods for telecommunications networks are reviewed. The assumption that each processor runs a single network component process is avoided, such a premise being unrealistic when simulating large networks. Performance issues arising from implementing distributed simulation strategies on message-passing processor architectures are discussed. Nontrivial network models are separated into domains, each sited on a distinct transputer. Problems arising from the limited connectivity of the transputer are also addressed.>