RESEARCH TOPICS

WiMax Networks

  • Cross-Layer Scheduling-Routing in the Mesh Mode

The mesh mode of the WiMax standard divides the network capacity into two parts, one for Internet traffic the other for Intranet traffic. According to the standard, one type of traffic cannot use the other's reserved capacity in anyway. This results in reduced system utilization where there is congestion in one region while other is not congested. We develop a cross-layer Queue Aware Routing (QAR) scheme for the Mesh mode of IEEE 802.16 with two approaches that utilize the capacity allocated to Intranet traffic to Internet traffic in case the latter suffers from congestion.


  • Reducing the MAC Overhead in the PMP Mode

In the PMP mode of WiMax, the BS schedules the data traffic in the uplink direction via the Uplink MAPs (UL-MAP). We try to increase the system capacity by eliminating redundant UL-MAP entries and allowing uplink data transmission instead. Our method only changes the BS, thus normal PMP mode WiMax user devices can be used without any changes.


  • WiMax Mesh Mode Schedulers

There are two different traffic schedulers in WiMax devices, one in the BS and the other in SSs. The BS scheduler handles the traffic requests of the SSs and backbone network. On the other hand, the SS scheduler decides which traffic can send its packets to the network on the resources allocated by the BS. Both of these two schedulers are not defined in the standard. We develop BS and SS schedulers for both the PMP and Mesh mode of WiMax that conforms the QoS requirements of the connections, give high network capacity and are fair among connections of different SSs.


  • QoS in Mesh Mode of WiMax

Contrary to the PMP mode of WiMax, the Mesh mode does not have an elaborate QoS handling mechanism. In this work we have developed a QoS handling mechanism for the Mesh mode of WiMax based on the PMP mode QoS mechanism. Upon network entry, instead of having a node registering itself to the network four nodes are registered , one for each scheduling service in the PMP mode.

Measurement of 0-6 GHz spectrum utilization at Berkeley Wireless Research Center


  • IPTV support in WiMax
  • Mobility in WiMax networks
  • Increasing the capacity in Mobile WiMax
  • IEEE 802.16j (multimedia multihop relaying) and IEEE 802.16m

We also work on the newly developing substandards of WiMax; IEEE 802.16j allows the usage of Relay Stations (RSs) in the PMP mode, IEEE 802.16m increases data capacity of the whole network to 540 Mbps with the use of MIMO technology. With the allowance of RSs, PMP mode will have similar capabilities with the Mesh mode.

Cognitive Radio

It is commonly accepted that the wireless spectrum is the scarce resource in wireless communications. However, more than 95% of the usage is below 3GHz. The static assignment of the spectrum results in inefficient usage of the spectrum. The utilization of the spectrum can be as low as 10%. Dynamic access to the spectrum can be considered as a method for solving spectrum scarcity. The Federal Communications Commission (FCC) in the U.S.A. is reviewing its policies regarding the usage of licensed bands by unlicensed users. (The use of the spectrum in Turkey is regulated by Telekomunikasyon Kurumu. Information about the spectrum use in Turkey may be retrieved at http://www.tk.gov.tr/Duzenlemeler/teknik/marfl/_marfl1.asp)

Figure: Measurement of 0-6 GHz spectrum utilization at Berkeley Wireless Research Center.

Cognitive Radio (CR) is a paradigm for wireless communication in which either a network or a wireless node changes its transmission or reception parameters to communicate efficiently avoiding interference with licensed or unlicensed users. This alteration of parameters is based on the active monitoring of several factors in the external and internal radio environment, such as radio frequency spectrum, user behavior, and network state. The idea of CR was first proposed by Joseph Mitola III and Gerald Q. Maguire, Jr. It was thought of as an ideal goal towards which a Software-Defined Radio (SDR) platform should evolve: a fully reconfigurable wireless black-box that automatically changes its communication variables in response to network and user demands.


Definitions:

Mitola's definition: A radio driven by a large store of a priory knowledge, searching out by reasoning ways to deliver the services the user wants.

Haykin's definition: Radios that improve spectral efficiency by sensing the environment and then filling the discovered gaps of unused licensed spectrum with their own transmissions.

Consciousness: This term refers to awareness of one's own existence, sensations, thoughts, surroundings, etc., including emotions and free will.

Cognitiveness: This term refers to mental processes of perception (sensing), memory, judgment, and reasoning.


This group focuses on Cognitive Radio Networks (CRN) and addresses the following issues in CRN:

  • Cognitive Radio Physical Platform

Cognitive radio is considered as the key enabling technology of Next Generation Wireless Systems (NGWS) and dynamic spectrum access systems. Cognitive Radio Mobile Terminal (CogMT) is defined as an intelligent wireless communication device that works on Software Defined Radio (SDR) physical platform. It has the capabilities of knowing and understanding the spectral environment it is operating in, adapting its physical radio parameters to the changing spectral conditions and learning from its radio environment. An SDR system is a radio communication system that can potentially tune to different frequency bands and receive any modulation across a large frequency spectrum by means of as little hardware as possible, processing the digitized signals in software. In the context of NGWS, cognitive radio enables mobile users to dynamically access and to fairly share the spectrum with other users while benefiting from the advantages of available subsystems in NGWS. In the literature the cognitive radio users are called Secondary Users (SUs) and the licensed users are called Primary Users (PUs) of those bands. SUs access the spectrum dynamically for underutilized bands without causing harm to PUs, as a result, spectrum utilization increases. The cognitive radio is, therefore, an accelerating trend of the current wireless technology research.

The ideal receiver scheme would be to attach an analog to digital converter to an antenna. A digital signal processor would read the converter, and then its software would transform the stream of data from the converter to any other form the application requires. An ideal transmitter would be similar. A digital signal processor would generate a stream of numbers. These would be sent to a digital to analog converter connected to a radio antenna. The ideal scheme is, due to the actual technology progress limits, not completely realizable, however. The actual practical solution is to let the software processing stage be preceded by a front-end that preconditions the input signals to give them characteristics that enable the subsequent stage to elaborate them. Current (2007-2008) digital electronics are not sufficient to receive directly typical radio signals over approximately 40MHz. An ideal software radio has to collect and process samples at more than twice the maximum frequency at which it is to operate. Actual software radios, for frequencies below 40MHz, use a direct-conversion hardware solution. In this solution an analog-to-digital converter (ADC) is connected almost directly to the antenna (some preamplifier and impedance adapting circuitry is present to ensure that the input of the ADC is correctly matched to the antenna). The output stream of digital data obtained from the ADC is then passed to the software defined processing stages.

Our focus on this subject is the software architecture design of handheld devices that works on SDR physical platform. CogMT device design also includes the artificial intelligence capabilities. Regardless of operating frequency range, a wideband front-end for a cognitive radio could have architecture as depicted in the following figure. The wideband RF signal presented at the antenna of a cognitive radio includes signals from close and widely separated transmitters and from transmitters operating at widely different power levels and channel bandwidths. As a result, detection of weak signals must frequently be performed in the presence of very strong signals. Thus, there will be extremely stringent requirements placed on the linearity of the RF analog circuits as well as their ability to operate over wide bandwidths. In order to keep the requirements on the final analog to digital (A/D) converter at a reasonable level in a mostly digital architecture, front-end design needs a tunable notch analog processing block that would provide a dynamic range control.

Figure: Physical architecture of CR: (a) CR transceiver and (b) wideband RF/analog front-end architecture.

In this architecture, a wideband signal is received through the RF front-end, sampled by the high speed analog-to-digital (A/D) converter, and measurements are performed for the detection of the licensed user signal. However, there exist some limitations on developing the cognitive radio front-end. The wideband RF antenna receives signals from various transmitters operating at different power levels, bandwidths, and locations. As a result, the RF front-end should have the capability to detect a weak signal in a large dynamic range.


  • Software Defined Radio

A Software Defined Radio (SDR) is a radio communication system which can tune to any frequency band and receive any modulation across a large frequency spectrum by using the same hardware as possible and process the signals through software. From mobile communication perspective it means user access to multiple systems from a single terminal. The logic behind a software radio is based on replacing the radio hardware components (Analog to digital converters, digital to analog converters, modulators, filters…) with the equivalent piece of software. In order to handle performance issues related to fast signal processing, FPGA (Field Programmable Gate Array) and DSP (Digital Signal Processor) based processing hardware is used instead of GPP (General Purpose Processor).

Figure: SDR infrastructure.

The opportunities that the SDR offer makes it a candidate platform to solve the problems related to dynamic spectrum management. Capabilities of an SDR allow the handset to operate in heterogeneous wireless networks. In other words, an ideal SDR handset can dynamically change its running software and can tune to required frequency and modulation type at runtime.


  • Cognitive Radio Network Architecture

According to FCC, several parts of the fixed spectrum are under-utilized while some spectrum bands are heavily used and subject to high interference. Temporarily unused spectrum bands (a.k.a. spectrum holes or white spaces) can be used by opportunistic radios to improve the overall spectrum utilization. Hence, new spectrum allocation methods and technologies are necessary to maximize the benefits of the limited spectrum resource by learning the unused spectrum bands in given time and location. Dynamic Spectrum Access (DSA) technique aims to solve spectrum allocation problems. The overall system that learns the operating environment and adapts its operating parameters according to its surrounding and uses DSA technique for efficient spectrum usage is called Cognitive Radio Network (CRN). In the following figure, spectrum holes are employed by CRN in an example scenario. In different areas the usage of the spectrum differs, so spectrum hole locations and their durations vary. CRN uses these spectrum holes for providing service to its users without causing harm to other users. Therefore, the change of parameters are observed by active monitoring of several factors in the external and internal radio environment, such as radio frequency spectrum, user behavior and network state.

Figure: CRN frequency usage example.

In the architectural foundation, we define some network agents to manage and support DSA nature of cognitive networks. The following terms are necessary for our proposed architecture:

Frequency Holder (FH): FH represents the institution that has the right of using a spectrum band in a particular region by a long term leasing agreement with the governmental agencies.

Spectrum Broker (SB): SB is a network agent that interconnects wireless spectrum holder and the CR users.

Cognitive Radio Service Provider (CRSP): CRSP is an entity that provides cognitive radio services.

Cognitive Radio Service Provider Network (CRSPN): CRSPN is a cellular network which covers a broad geographical area and provides communication service for cognitive radios. A CRSPN can be owned by a CRSP or may be shared between some CRSPs. Moreover, establishment of these networks by some third party institutions is also possible. These institutions provide leasing of their networks by CRSPs.

Cognitive Radio Mobile Terminal (CogMT): Defined as an intelligent wireless communication device that works on Software Defined Radio (SDR) physical platform.

Cognitive Base Station (CogBS): CogBS works as a connection point that ties CogMTs to CRSPN and responsible for handling traffic and signaling between a CogMT and the CRN.

Advantages of Establishing CRSPN:

  1. CRSPN forms a cellular network architecture which helps to organize cellular frequency reuse pattern.
  2. CRSPN architecture provides a new adaptive communication protocol rather than connecting various systems.
  3. Support for infrastructure aided security and authentication mechanisms.
  4. Allows making use of frequency bands allocated for broadcast communication.
  5. CRSPN architecture supports network agents to advertise frequencies to cognitive radios.
  6. Handoff is easier and more manageable.
  7. Handoff latency is shorter.

Disadvantages of Establishing CRSPN:

  1. Establishing CRSPN agents cause additional deployment costs.
  2. High power necessity due to long distance communication.
  3. High interference due to long distance communication.

We propose a network architecture for CRN that establishes CRSPN. Nodes in CRN have capabilities of transmitting and receiving at different frequency bands. CogMTs use frequencies as long as they don’t cause harm to primary users of the frequencies. Broker systems are introduced in the network architecture for learning and leasing the frequency holes in the channel. Entities and the interconnections of them are summarized in the following figure.

Figure: Architecture of CRN.

We focus on architectural design of CRN and define the messages within interactions between entities.


  • Spectrum Sensing and Primary User Detection

Physical layer of Cognitive Radio observes the accessible spectrum resources and acquires spectrum information via spectrum sensing techniques. Spectrum sensing is necessary to avoid inducing interference to primary users.

Spectrum sensing, which is one of the primary functions of the Cognitive Radio, can be performed by two different approaches, primary transceiver detection and primary receiver detection. PU existence detection techniques can be investigated in three classes:

  1. energy detector
  2. matched filter detector
  3. cyclostationary feature detector

Each detection technique has its advantages and disadvantages and applied according to the required precision of sensing information. Energy detector technique is preferred when there is no information about the PU, however, this technique is insufficient in terms of false detection and low SNR ratio. In the cases, when sensitivity of detection and reliability of the results become important, cyclostationary feature detector can result in a higher detective capability than energy detector technique. On the other hand, cyclostationary feature detector technique requires more observation time and has a more complex structure compared to energy detector technique.

Last but not least, matched filter detector technique is a recommended detection technique when Cognitive Radio has the knowledge of physical and MAC layer of PU’s communication protocol. This technique provides high performance since it improves the SNR ratio. However, it is quite difficult to have a complete knowledge of primary user communication and the inaccurate information causes performance decrease or incorrect results in spectrum sensing.

These three techniques are insufficient to solve receiver uncertainty and shadowing problems. Cooperative detection techniques are proposed to solve this problems. In non-cooperative detection each secondary user aims to detect primary users by its spectrum detection results. On the other hand, in cooperative detection, SUs can share spectrum sensing results. Cooperative detection techniques can also be used to decrease sensing time along with solving receiver uncertainty and shadowing problems.


  • Spectrum Sharing and Mobility

Spectrum sharing and mobility are main functions of CR. Providing the fair spectrum scheduling method, one of the major challenges in open spectrum usage is the spectrum sharing. It can be regarded to be similar to generic media access control MAC problems in existing systems.

Spectrum mobility is the process of maintaining the connection while changing the frequency of the operation. Traditional frequency hopping protocols are designed according to the signaling, packet routing and mobility standards established for homogeneous systems. In those systems, frequency hopping operation is fulfilled regarding to signal power and spectrum resource availability. However, Cognitive Radio also evaluates other factors such as primary user arrival statistics, pricing mechanisms, congestion, expected latency and user preferences.

Spectrum mobility can be classified in three classes according to the reason of the frequency hopping.

  1. Frequency hopping triggered by primary user detection
  2. Frequency hopping according to changes in signal quality
  3. Frequency hopping resulted by the mobility of the user

The goal of all frequency hopping processes is to perform spectrum resource changes with minimum performance degradation.


  • Resource Management

In CRNs, resource could refer to different spectrum parameteres such as a range of frequency band, SNR in the target band, a multiple access element like CDMA code, TDMA time slot, and OFDMA subband.

So as to manage these resources fairly and effectively, secondary users must make their transmissions limited by time, power level, frequency range.

SUs can perform their transmissions in two different modes:

  1. Ad hoc mode
  2. Centralized mode

Advantages and disadvantages of these communication modes are explained above. In ad hoc mode resource management can be performed in a cooperative manner. On the other hand, in centralized mode several network architectures can handle partial or full management on spectrum resources. In CRNs brokers communicates with spectrum holders and CRN entities and CRN entities communicate with SUs. The communication protocols in between must be suitable to achieve requirements of these network entities such as time, communication overhead, and complexity.


  • Game Theoretical Approach for Frequency Brokerage

Game theory mathematically models strategical moves of one or more individuals profits or losses and applied to several fields from finance to computer science. Most of the proposed resource management models in cognitive radio networks based on game theory models. Games that can be used in telecommunication can be classified into two branches such as:

  1. Cooperative games
  2. Non-cooperative games

Games can be further divided according to the end time of the game and other playing strategies or to the other that change the set of game conditions. A game has the following properties:

  1. Set of players
  2. Set of rules
  3. Set of strategies
  4. Set of outcomes
  5. Pay off function for each player and for each outcome

  • Security in Cognitive Radio

Authentication and authorization methods developed for roaming in regular wireless networks are not applicable to cognitive radio systems. In cognitive radio networks, the cognitive user, CRSP, and FH need not trust each other. Thus, repudiation problems between user and CRSP as well as between CRSP and FH should be solved in an efficient manner.


Next Generation Wireless Systems

  • NGWS Architecture

NGWS will provide high bandwidth access anytime, anywhere for services including multimedia with QoS requirements. Existing systems fail to satisfy all NGWS objectives simultaneously due to constraints like global coverage, indoor/outdoor communications, and frequent handoffs. Therefore, NGWS will combine the existing technologies and the new technologies to come to provide high bandwidth access everywhere. PCS, WLAN, satellite, and new wireless systems like 4G Mobile will serve as subsystems in NGWS. The basic properties of NGWS can be summarized as follows:

  • Completely packet-based, including the air interface.
  • Support for voice, multimedia, and data traffic with QoS provisioning.
  • The backbone traffic carried over the Internet.

  • Testbed

Designing a testbed for NGWS is a significant challenge due to the presence of several subsystems with different air interfaces. Besides the high cost of the purchase, deployment, configuration, and maintenance of all the equipment, the licenses required for the frequencies constitute the major challenges.

We propose a testbed for NGWS using only WLAN access points. The proposed testbed emulates several subsystems simultaneously at the network layer, allowing network and higher level research. Since WLAN systems use ISM bands, frequency licensing does not constitute a problem.


  • Location Registration

Overlapping coverage areas of the systems in next generation networks cause high signaling overhead if the users are tracked in multiple systems independently. Selecting the system over which paging will be done is yet another problem. We propose a location registration scheme that updates the location information only in the relevant subsystems. We also propose an efficient paging scheme that exploits the location information in multiple subsystems. User preferences, network availability, and connection history are considered while determining the subsystems to be used for location registration and paging.

Since a Mobile Terminal (MT) has access to multiple subsystems in NGWS, it can cross more registration area boundaries with respect to the single subsystem case. Therefore, MT must send more location registration messages. More location registration messages implies more signaling overhead in the system, and more power consumption at the mobile terminal. With NGLR, we propose sending location registration messages selectively only in the subsystems that are relevant for the user. The location registration messages for the non-relevant subsystems are suppressed. Thus, both the signaling cost and the power consumption are reduced at the cost of reduced precision of the location information in the subsystems that are non-relevant.


  • Paging

The network’s knowledge about the location of an inactive user is in registration area level. When an incoming connection request for a mobile user is received, the network has to locate the user in the cell level to set up the connection. In order to locate the user, the network broadcasts a polling message in all cells in the user’s last known registration area. This widely used scheme is known as blanket paging.

In NGWS, paging over all subsystems is not feasible since it implies that all mobile terminals are paged over all subsystems. Paging signaling cost can be reduced by choosing only one subsystem to broadcast paging messages. It is possible to reduce even further by leveraging the existence of multiple subsystems in the same service area. With NGP, we propose to broadcast paging messages in a smaller number of cells subject to paging delay constraints.


  • Connection Admission Control and Handoff

In a wireless network, it is connection admission control scheme that decides whether connection and handoff requests will be accepted. For new connection requests, the NGWS must select the appropriate subsystem for connection establishment. Furthermore, the mobility of a user may require change in the use of wireless resources, resulting in a handoff attempt for the user. It is the duty of NGCAC to manage the connection requests and handoff attempts in a way that maximizes network utilization, minimizes outage, and distributes the load between subsystems.

Since MT has access to multiple subsystems simultaneously, the NGWS must select one of the subsystems for connection. Among the accessible subsystems, one subsystem that can accommodate the connection request will be selected subject to connection class and user preferences.

In the analysis of wireless systems, the service area is typically split into cells since the partitioning criteria is the access node that controls the area. However, in the case of NGWS, cellular granularity is too coarse to define a partition since there are multiple subsystems serving the same service area. Therefore, in our model, the service area is partitioned into smaller regions we call physical areas. This is the first analytical model for NGWS in the literature.