From cognitive radio to cellular networks - IEEE Xplore

2013 IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications: Workshop on Cognitive Radio Medium Access Control and Network Solutions

From cognitive radio to cellular networks: summary and future research on routing protocols Michał Szydełko, Member, IEEE, Luca De Nardis, Sapienza University of Rome, Member, IEEE operator case. The aim is to identify potential development directions with the overall goal to integrate in cellular networks future networks concepts, based on the existing work on the cognitive network routing protocols. The document is structured as follow: in Section II we shortly summarize existing routing protocols for cognitive networks. In Section III, energy efficient routing protocols for CRN are discussed. Section IV covers cognitive radio aspects in cellular networks. In Section V, standardisation work is addressed, indicating the industry point of view. Finally in Section VI, we identify potential future research areas, which are followed by conclusions.

Abstract— In this work authors are analyzing mobile ad-hoc networks (MANET) and cognitive radio ad-hoc networks (CRAHN) solutions from routing protocols point of view, in order to identify promising directions of the future research, which could be developed towards energy efficient routing protocols for future cellular networks. Literature studies are covering cognitive solutions implementation in cellular environment. Standardization developments were studied, in order to identify industry’s views on the energy efficiency aspects in networks, as well as on the alternative offloading solutions. Based on the compilation of the research and industry overviews, various deployment scenarios are considered, including inter-UE, intra-operator, as well as inter-operator case. Number of concepts was identified, including radio resource management solutions, proposals related to the introduction of energy efficiency related performance indicators in networks, or cooperative schemes in inter-operator networks, which could be studied from the energy efficiency point of view. Proposed ideas are basis for further research work.

II. STATE OF THE ART Cognitive Radio Networks (CRN) can be deployed in one of two architectures. It could be either the infrastructure-based CRN, which is equipped with central network element, i.e. base station, which is coordination communication in the network, or it could be Ad-hoc CRN networks (also called CRAHN), where a mobile CR user can communicate with other users via ad-hoc communication links, with no additional network infrastructure. An overview of several routing protocols for CRN was presented in [1], covering multiple variant of L3 protocols [2] - [11]. Those protocols could be classified into the following categories: • Primary User activity aware routing: designed to create the routing path, which avoids areas of the Primary User (PU) activity, to make the route less impacted by PU activity, while the Secondary User (SU) data transmission is active. • Location-based routing: these protocols use nodes location information to transfer routing messages to selected network areas (instead of the entire network broadcast), with the aim to relay the message as close as possible to the destination node with minimum overhead; they typically require all network nodes to share their locations with all other nodes. • Cluster-based routing: in this case, network is divided into number of clusters. The goal is to increase network scalability, to introduce resources distribution balancing and to make the bandwidth usage more efficient. Two variants of the clustering algorithms exist: clusters with and without cluster heads. Cluster head role is to manage data transmission and to maintain information on the cluster membership. • Multipath routing: relies on the establishment of multiple different routing paths between the source and destination

Index Terms— cellular networks, cognitive radio, future networks, protocols, routing, standardization

I. INTRODUCTION

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HE purpose of this work is to shortly summarize recent developments in the area of MANET and CRAHN networks, additionally focusing on the L3 routing protocols and Energy Efficiency (EE) aspects. EE solutions are necessary for the mobile devices in various network classes, to prevent service availability for end users. Main observation behind this paper is that the EE focus routing solutions for MANET and CRAHN networks are based on self-organized mechanisms. Based on the literature studies, we attempt to identify mainstream concepts for the EE routing mechanisms implementation in the above network classes and to formulate potential development direction for cellular networks, for which self-organization solutions (SON) are currently under development. Standardization developments were studied, in order to identify industry’s views on the energy efficiency aspects in networks, as well as on the alternative offloading solutions. Based on the compilation of the research and industry overviews, various deployment scenarios are considered, including inter-UE, intra-operator, as well as inter-

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III. ENERGY EFFICIENT ROUTING PROTOCOLS FOR CRN

In [15] a QoS routing protocol was proposed for CRAHN networks, which was EE QoS routing (EQR), using TDMA access scheme. Guaranteed bandwidth on the per-flow basis was assigned based on the QoS requirements in CRAHN network which is characterized by the low to medium topology modifications. For each flow, the proposed protocol will allocate both route and the channel/timeslot resources. The protocol improves network throughput by distributing the network load over different channels and timeslots. In the overview of the routing protocols for CR in [16], Spectrum And Energy Aware Routing (SER) was covered, an on-demand protocol for CRAHN networks and energy limited devices, which aims to provide high throughput and robust routing [17]. The protocol relies on channel access scheduling to avoid conflicting data transmissions among secondary users. The protocol is balancing the network load by using channel-timeslot resources assignment scheduling.

Energy Efficient (EE) routing protocols and their applicability was investigated for various application areas. In [12] authors presented survey and classification on various EE routing protocols for Mobile Ad-Hoc Networks (MANET), as mobile nodes operation in such networks is time limited due to power shortage. Two main groups were identified: • Active mode: Energy consumption limitation during packet transmission/reception. These protocols contain transmission power control schemes, as well as load distribution techniques, which are used to determine optimal routing paths, to minimize the overall transmission power for fruitful data delivery to the destination node. • Inactive mode: Energy consumption limitation during idle mode, when a device is just listening to the network for possible connection establishment requests. In this mode, network nodes can save the energy by switching to sleep mode, or turning off for certain time periods, depending on the device configuration and traffic load in the network. Such approach requires well-designed implementation of protocols, capable of guaranteeing data delivery even when a given percentage of network nodes are in idle mode. In [13] power-aware routing protocols for ad-hoc networks were proposed based on the shortest cost routing algorithm, by usage of the traffic load balancing within the network, in order to extend the battery lifetime of network elements. Such approach alleviates the problem of the overload of the shortest path, and subsequent batteries draining along that shortest route, leading as a consequence to network disconnections. Based on the introduction of the opportunistic spectrum policy of the CR to the MANET applications, Cognitive Radio Ad-Hoc Networks (CRAHN) were discussed in [14]. In those networks, mobile users have limitation on the available energy capacity. Efficient routing protocols are required in order to efficiently use the available resources of the mobile devices, avoiding unnecessary spectrum sensing, packet retransmissions, etc. EE routing mechanisms from MANET were proposed to be implemented in CRAHN networks, where CR users sense spectrum in order to identify unoccupied radio channels, and opportunistically access those sensed radio channels without causing interference to licensed users.

Based on the overview of the routing protocols for cognitive networks, it was observed, that various aspects of those networks are based on automation. Self-configuration of MANET and CRAHN networks was considered as the silent assumption on all above referred papers. Self-organization and self-configuration of the networks is not limited to CRN networks. Self-Organizing Network (SON) has been considered as one of the main pillars during LTE-A standardisation in 3GPP. Therefore, authors of this study were attracted by possible exploitation of the cognition in the cellular networks and their future evolutions. While analysing the CR routing protocols developments, it has to be noticed, that the prerequisite for such solutions is the interoperability with the primary system, as the secondary users are forced to respect the priority of the PU in the access to the radio resources in CRN. For that reason, SU needs to respect specific routing algorithms of the primary system. One could think of direct implementation of some of the cognition engines into the cellular networks and their resource allocation mechanisms. Such mechanisms were studied e.g. in the form of the spectrum broker entity implementation for spectrum sharing purposes, being the policy watch-dog for the execution of the CR in the cellular environment. Another argument to look into this particular direction is that the CR has been considered as the technology for the 5G networks deployment [19], where CR terminal and cognition in the network elements has been studied. Below, we are shortly presenting related work, which has been already covered for potential inclusion of CR concepts into the cellular networks. In [20] performance and suitability of the Cognitive Resource Management (CRM) implementation within the LTE platform were analysed, presenting how system parameters could be modified in order to achieve improved resource utilization and transmission efficiency, based on the network status information and subsequent radio resources parameters configuration (i.e. LTE bandwidth, MCS adaptation). Authors claimed that the approach, although the targeting LTE networks, is flexible enough to be used for

nodes. Reasoning behind such approach is the ability to transmit multiple data streams at the same time, or to use alternative routing paths for backup purposes. • Reinforcement learning based routing: reinforcement learning is applied to create routing path for data delivery. Learning is introduced in the network, with the aim to map the observation in the network into the actions, creating certain control policy. Aim of this protocol is to effectively address challenges driven by the spectrum resources availability uncertainty in the cognitive networks. • Mobility aware routing: designed to address mobile CRN networks, where mobile nodes locations change over time, potentially causing link breakages. Protocols capable of preventing these events by selecting stable routes or providing route recovery mechanisms were proposed.

IV. COGNITIVE RADIO ASPECTS IN CELLULAR NETWORKS

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future directions of Software Defined Radio (SDR) and CR standards. CR principles were concentrated on two issues: Cognitive Pilot Channel (CPC) and Functional Architecture for Management and control of reconfigurable radio systems. The latter one covers dynamic self-organizing planning and management (DSONPM), dynamic spectrum management, as well as Joint RRM (JRRM). DSONPM provides decision mechanisms for traffic distribution, network performance optimisation, RAT activation, and configuration of radio parameters. The overall goal of JRRM is one joint management of radio resources, which potentially covers few RATs in the hetnet scenario. JRRM is mainly responsible for the radio access selection, which reflects certain optimisation function, as well as QoS and bandwidth allocation and control of the admission. From the algorithms point of view, mechanisms for autonomous RAT selection were investigated, using game theory, stochastic analysis, or decentralized resource allocation methodologies. Cognitive concepts were introduced to obtain dynamic spectrum assignment using learning techniques, in order to achieve efficient spectrum utilisation for future mobile networks.

inter-RAT scenarios (e.g. LTE and Wi-Fi). Game theoretic approach to the secondary spectrum access in LTE network by HeNB femtocells under the primary macro cell coverage was presented in [21]. In this work, femto access nodes were equipped with cognitive capabilities, introducing a secondary BS, whose aim was to maximize the spectrum utility of the unoccupied frequencies, at the same time minimizing the interference to the primary macro BS. The competition amongst secondary spectrum users for spectrum access was formulated as a non-cooperative game-theoretic learning problem of selfish agents. Global utility function was defined to evaluate the overall network performance. In [22] a framework for enhanced RRM in LTE networks was proposed, using cognitive functionality to provide system with knowledge derived from the past interactions, to provide resource allocation and management solution to the future issues, based on database stored reference cases. Such approach would allow system to apply the known solutions to the problems identified in the network, based on the knowledge from similar problems in the past, using context matching techniques. Solution identified in the past will be provided faster, by avoiding complex optimisation procedures. Simulation results presented were showing that proposed mechanism provides significant efficiency. Benefits of the cognitive radio BS development for LTE networks were presented in [23], considering macro and femto BS classes, with the aim to meet stringent LTE efficiency targets by incorporation of the CR. Cognition was introduced in form of spectrum sensing and dynamic resource access. The overall goal of this work was the Co-Channel Interference mitigation, based on the game-theoretic mechanisms. In [24] implementation of CR concept in the Unlicensed Wide Area Network (UWAN) was discussed my means of RF Control Channel (RCC) and Available Resources Map (ARM). RCC has been introduced to coordinate the spectrum access of all mobile devices in the system (including UE-BS and UE-UE communication), ensuring that radio links are not generating interference and avoiding the hidden node problem. Coordination is executed by appropriate signalling of the connection request via RCC, before the radio data transfer channel is established. All nodes are monitoring the RCC, ensuring that no conflicts arise. On network side, ARM database was introduced for resources management and radio activity monitoring in the system. Despite of the interesting ideas and promising simulation results, it has to be noted, that there is clear trade-off between the performance of cooperative schemes in networks and the required signalling overhead introduced by those cooperation mechanisms, as well as subsequent delays.

B. 3GPP standardisation Energy efficiency was also considered within 3GPP standardisation work. Technical Report TR32.826 [28] covers study on Energy Savings Management (ESM) looking at various aspects of the energy savings in cellular LTE networks being combined with SON. Objective of this study was to identify energy consumption optimisation mechanisms for E-UTRAN networks. Based on the numerical study, potential energy saving was evaluated in case of switching off BSs and/or spectrum carriers during off peak hours. Based on various parameter settings of the power consumption balance among HSDPA network elements, distinct planning targets and typical daily traffic load, it was presented that switching off certain base stations and/or transceivers could lead to energy saving in range of 18% to 38%. In shall be noted, that those values do not consider many practical aspects and impairments. Non-linear relation between the power consumption and the load traffic was not considered in this analysis. Furthermore, the evaluation was performed in heterogeneous cells grid, not considering any irregular access nodes deployments, of het-net scenarios. ESM concept was described in [28], covering procedures and configuration management. Two applicability use cases were identified for the described power saving concept, covering inter-frequency and inter-RAT coverage case. In both cases, service coverage needs to be doubled in order to avoid service quality and availability degradation from the end user point of view. This observation leads to the conclusion, that the inter-operator concept as discussed in further part has great potential in terms of the energy efficiency improvement in future networks, based on the CR principles. In another report [29], potential solutions for energy saving for E-UTRAN were further elaborated. Three use cases were defined for potential solutions classification:

V. STANDARDISATION WORK STATUS In order to review progress in this field on global level, standardisation bodies’ developments were considered, focusing on relevant ETSI and 3GPP [26] working groups. A. ETSI Reconfigurable Radio Systems In [27] ETSI RRS has captured their work status on the

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VI. IDENTIFICATION OF FUTURE RESEARCH AREAS Based on the analysis of the literature above, conclusions for the future research were formulated, listing potential areas for future work in the field of cognitive radio application in future mobile networks. Discussions presented in this work leads to the conclusion, that future work could be structured into the following 3-level analysis of the proposed solutions:

1) Inter-RAT energy savings In this scenario, multiple RAT technologies are considered, where E-UTRAN hot-spot cells (cells C-G) are located within coverage areas of the legacy cells (i.e. cells A, B), which were initially deployed for the coverage purposes in the considered area. E-UTRAN cells are not providing continuous coverage, as they were deployed just as, so called, capacity boosters.

1. Mobile device level a. Traffic offloading solution among terminals (e.g. Device to Device communication), b. Reuse on the MANET techniques in the 3GPP compliant environment. 2. Intra-operator network level a. EE analysis of the potential CR solution in hetnets among macro BS and small cells, focusing on EE routing protocols development in cellular networks, based on the pre-defined scenarios; b. Analysis of the hetnet performance, with the aim to define optimisation function for the EE, based on the available RAT’s and traffic demands. This line will move from solutions based on switching-off the network elements, looking into potential solutions for power settings and RAT selection; c. Cognitive RRM mechanisms with additional intelligence, provided from cognition of the network performance and network elements. Cognitive RRM would be able to use this information to provide time- and location-specific estimates of the traffic requirements in the networks, allowing for EE services provision, as well as improved resources utilisation (including improved spectrum utilisation, thanks to cooperation); d. Mechanisms for energy efficiency driven handover, adding energy efficiency to the various hand-over triggers that are considered in current cellular networks, e.g. overload, quality, etc; e. Introduction of a network performance KPI taking into account energy efficiency; f. Formulation of improved energy consumption model for the reference network, considering multi-RAT capabilities, as well as cognitive radio aspects, such as spectrum sensing, in order to quantitatively evaluate the EE related mechanisms and routing protocols; g. Identification of future network infrastructure development directions (e.g. relay nodes, P&P hotspots).

E-UTRAN Cells

Cell C Cell E Cell D

Cell G Cell F

Legacy Cell A

Legacy Cell B

Fig. 1. Inter-RAT energy saving scenario [29].

Energy saving in inter-RAT scenario is based on the possibility to switch-off the capacity boosting cells. Decision whether certain cell shall become turned on/off, could be based on the statistical information like load, traffic requirements etc. In case when particular hot-spot changes its mode (active/idle), it shall inform its neighbours about this decision, to allow them to consider this status in their decision processes. 2) Inter-eNB energy saving This case could be employed in situation, where separate cells were deployed for coverage and for capacity boosting purposes. In such case, depending on the traffic requirement in the network, some of hot-spots could be turned off during low traffic to reduce energy consumption in network, while other cells are serving traffic requests by appropriate load routing. E-UTRAN Cells

Cell C Cell E Cell D

E-UTRAN Cell A

Cell G Cell F

E-UTRAN Cell B

Fig. 2. Inter-eNB scenario for energy saving [29].

3) Intra-eNB energy saving In case of single cell, energy saving mechanisms could be used only in case of sufficiently low resource utilization at the cell level. Mechanism enabling has to be based on the traffic monitoring and coverage assurance. Energy saving solutions at the single cell level are mainly related to the Power Amplifier (PA) power reductions. Finally it should be highlighted, that RRM protocols were decided by 3GPP to be out of scope of the technical specifications, in order to allow implementation of the vendor specific protocols and scheduling mechanisms, allowing performance diversification of the networks, depending on vendor solutions.

3. Inter-operator network level a. Routing mechanisms with exploitation of the potential in the multiplied infrastructure, b. Definition of the compensation mechanisms to keep fairness of the solutions and to stimulate market players to join the coalitions, c. Analysis of technical requirements for the inter-operator scenario implementation: In order obtain the potential EE gains from the inter-operator scenarios, it is required to perform analysis of the technical pre-requisites as well as on the potential signalling overheads caused by such cooperation model.

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VII. CONCLUSIONS

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In this work we shortly summarized the state of the art on the routing protocols for MANET and CRAHN networks, focusing on energy efficiency–aware protocols. The analysis of the literature studies, it was found that the main argumentation for the EE routing mechanisms implementation in the above described networks is the limited batter capacity of the devices participating in the above scenarios. Therefore, EE solutions are necessary for the mobile devices to ensure service availability for those users. Furthermore, it was observed, that the above discussed networks and EE routing approaches are based on selforganized mechanisms. This led to the analysis of the ongoing standardisation work on cognitive radio and cellular networks. Based on the previous work, several open research areas were identified at mobile devices level, intra-operator level, as well as inter-operator level, in order to potentially introduce of cognitive radio mechanisms into cellular networks. The analysis carried out in this works will form the basis for further research work. ACKNOWLEDGMENT This work was partially funded by COST Action IC0905 TERRA, COST Action IC0902, and by the FP7 Network of Excellence ACROPOLIS, Grant n. 257626. REFERENCES [1]

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