The subject disclosure generally relates to delay-sensitive cross layer scheduling for multi-user wireless communication systems that takes channel state information at transmitter (CSIT) error into account.
Cross layer scheduling has been proposed to boost the spectral efficiency of multi-user digital transmission systems, such as multi-user Orthogonal Frequency Division Multiple Access (OFDMA) systems. As an example, OFDMA has been proposed as a way to support demand for high data rates by applications, such as wireless local area network (WLAN) applications and Worldwide Interoperability for Microwave Access (WIMAX) applications, i.e., applications based on the Institute of Electrical & Electronics Engineers (IEEE) wireless broadband standard 802.16.
However, conventional cross layer systems have been predicated upon various assumptions that are impractical in view of the way that multi-user wireless communication systems tend to be implemented and used in practice. First, conventional cross layer systems have assumed that users are delay insensitive. Second, conventional systems have assumed perfect CSIT information is always available.
As an exception to conventional systems that assume delay insensitivity, one cross layer scheduling algorithm, based on combined information theory and queuing theory, has considered delay sensitive real time users while seeking to minimize average system delay in a multi-access channel; however, such cross layer scheduling algorithm has assumed homogenous user delay requirements when it is likely applications will have heterogeneous requirements in reality.
While the problem of heterogeneity of delay constraints imposed by different applications has been considered in the context of OFDMA systems, such systems have assumed the availability of perfect CSIT information per the second assumption. The effect of CSIT error on scheduler design has been considered in certain limited contexts, such as in the context of orthogonal frequency division multiplexing (OFDM) systems and multi-user multiple-input single-output (MISO) systems; however, such proposals have limited their focus to power allocation design with limited CSIT feedback in an OFDM/frequency division duplex (FDD) system, without adequate consideration of the problem of outdated CSIT information.
In this regard, when the CSIT information is outdated, despite the use of strong channel coding, systematic packet errors result whenever the scheduled data rate exceeds the instantaneous mutual information. Due to such potential packet errors, conventional performance measures, such as ergodic capacity, become less meaningful because such measures fail to account for the penalty of packet errors.
Thus, conventional cross layer designs inadequately address the problem of outdated CSIT and ignore heterogeneous user delay requirements and queue dynamics. To the extent any conventional systems have attempted to address one or the other assumption, such treatment has been decoupled, i.e., no system has attempted to address both problematic assumptions together. Accordingly, as part of cross layer scheduling, it would be desirable to take outdated CSIT information into account and further desirable to consider users with heterogeneous delay sensitivities.
The above-described deficiencies of current cross layer designs are merely intended to provide an overview of some of the problems encountered with existing cross layer scheduler designs, and are not intended to be exhaustive. Other problems with the state of the art may become further apparent upon review of the description of various non-limiting embodiments that follows below.
A simplified summary is provided herein to help enable a basic or general understanding of various aspects of exemplary, non-limiting embodiments that follow in the more detailed description and the accompanying drawings. This summary is not intended, however, as an extensive or exhaustive overview. Instead, the sole purpose of this summary is to present some concepts related to some exemplary non-limiting embodiments in a simplified form as a prelude to the more detailed description of the various embodiments that follow.
A CSIT error considerate delay-sensitive cross layer scheduler is provided that takes into account heterogeneous delay requirements in slow fading channels by utilizing queuing theory and information theory to model system dynamics. Various non-limiting embodiments of scheduling implemented by the scheduler account for the impact of outdated CSIT information in digital transmission systems. The scheduling optimizes allocation of power and allocation of subcarriers for multi-user OFDMA systems to maintain delay constraints of heterogeneous users, guarantee a fixed target outage probability, and provide asymptotic multi-user diversity gains over fixed allocation schemes.
In one embodiment, a CSIT error considerate delay-sensitive user access system for a multi-user OFDMA environment is provided that includes a user delay sensitivity tracking component, a CSIT estimating component, a system queue state tracking component and a cross layer scheduling component.
The various embodiments for CSIT error considerate delay-sensitive cross layer scheduling are further described with reference to the accompanying drawings in which:
A simplified overview is provided in the present section to help enable a basic or general understanding of various aspects of exemplary, non-limiting embodiments that follow in the more detailed description and the accompanying drawings. This overview section is not intended, however, to be considered extensive or exhaustive. Instead, the sole purpose of the following of the overview is to present concepts related to some exemplary non-limiting embodiments in a simplified form as a prelude to the more detailed description of these and various other embodiments that follow.
As mentioned in the background, conventional cross layer systems have assumed that users are delay insensitive, and yet, at least some users are likely to have requirements, or sensitivity, when it comes to delay. In this regard, next generation networks are expected to contain real time users of heterogeneous classes with different delay requirements. As a result, in accordance with various embodiments described herein, users are assumed to be delay sensitive with heterogeneous delay requirements consistent with the evolution of wireless communications and disparate applications interacting across different users.
Conventional cross layer systems have also assumed that CSIT information is perfect. However, because a wireless channel is time varying, CSIT at the base station is already outdated when CSIT is estimated, e.g., from an uplink pilot in Time Division Duplexing (TDD) mode. In this regard, when CSIT information is outdated, systematic packet errors result even if powerful channel coding is applied, causing significant degradation of the delay performance of heterogeneous users. Accordingly, in accordance with various embodiments described herein, errors are presumed in CSIT information due to outdated information.
In one embodiment, a CSIT error considerate cross layer scheduling component determines optimal power, data rate, and subcarrier allocation for users of a digital transmission system with heterogeneous delay constraints in the presence of imperfect CSIT information. A user delay sensitivity component can be provided that determines and/or tracks the various heterogeneous users' delay constraints. Such information can then be considered when determining scheduling result(s) for users in a digital transmission system.
A CSIT estimating component can also be provided that estimates the system CSIT. Such information can then also be used for determining scheduling result(s) for users in a digital transmission system.
A system queue state tracking component can also be provided that determines and/or tracks the system queue state. The system queue state depends on such information as the amount of information remaining in each user's buffer in a digital transmission system. The system queue state information can then be used for determining scheduling result(s) in the digital transmission system.
A delay-sensitive cross layer scheduler can also be used to optimize spectral efficiency in the presence of heterogeneous delay requirements and imperfect CSIT simultaneously. To take account of heterogeneous delay requirements, both queuing theory and information theory can be used to model the system dynamics of a digital transmission system, including both the queue dynamics and the physical layer dynamics.
The CSIT error considerate delay-sensitive cross layer scheduler of the present invention can optionally be employed in a multi-user OFDMA system to boost spectral efficiency. In this regard, effective cross layer scheduling in OFDMA systems in accordance with embodiments described herein can be achieved through exploitation of multi-user diversity by carefully assigning multiple users to transmit simultaneously on different subcarriers for each OFDM symbol, along with optimal power and data rate allocations.
Simulated results illustrate that the delay-sensitive CSIT error considerate components and robust methodologies of the various embodiments provide a system performance enhancement over the performance of a naive scheduler, e.g., a scheduler that does not consider CSIT error, while satisfying heterogeneous delay requirements, even in the presence of moderate to relatively high amounts of error in CSIT information.
The user delay sensitivity component 102 determines and/or tracks a user delay sensitivity requirement for one or more users of the digital transmission system. The CSIT estimating component 104 determines and/or tracks an estimated channel state information at the transmitter for the system. The system queue state tracking component 106 determines and/or tracks the system queue state.
The cross layer scheduling result(s) are determined at 108 for at least one user based, at least in part, on the system variables provided, i.e., user delay sensitivity requirement, the estimated channel state information at the transmitter, and the system queue state. Selective user access is then provided at 110 to one or more users of the at least one user by allocating portions of the system power, system data rate, and system subcarriers based, at least in part, on the respective determined cross layer scheduling result(s).
As mentioned, a delay-sensitive cross layer scheduler for a digital transmission system, such as a multi-user OFDMA system, as described herein, provides an effective balance between maximizing throughput and providing delay differentiation of heterogeneous users with robust performance even for medium to high levels of error in CSIT information. The cross layer scheduler has multi-user diversity gain that grows in a rate of log (K) with the number of users K and decreases proportionally with CSIT error variance σΔII2, while retaining substantial throughput gain over static allocation policy with the maintenance of all users' delay constraints, regardless of the variation of traffic loadings and CSIT error.
Based on the assumptions of heterogeneous users regarding delay, and imperfect CSIT information, the cross layer scheduler problem is formulated herein as an optimization problem that considers the imperfect CSIT information, source statistics and queue dynamics of the OFDMA systems. In this regard, the cross layer scheduling accounts for the heterogeneous delay requirements in slow fading channels as well as the imperfect CSIT simultaneously. The delay sensitive aspect of the cross layer scheduler design is thus coupled to handling the effect of imperfect of CSIT information.
As presented in further detail below, to take account of heterogeneous delay requirements, both queuing theory and information theory can be used to model the system dynamics (involving both the queue dynamics and the physical layer dynamics). A convex optimization problem is then formulated after proper transformation of the delay constraints, and the optimal delay-sensitive rate, power and subcarrier allocation solutions can be derived by incorporating the outdated CSIT accordingly.
The optimal power allocation and subcarrier allocation solutions can thus be obtained based on the optimization framework presented herein. Also, as mentioned, when there is imperfect CSIT, there are systematic packet errors, which have a significant impact on the delay performance of heterogeneous users. In contrast, the delay performance of naive cross layer schedulers, e.g., a CSIT error inconsiderate scheduler, designed under the assumption of perfect CSIT are very sensitive to CSIT errors.
In one non-limiting embodiment, optimal delay-sensitive power allocation employs a multi-level water-filling structure or abstraction where users with stringent delay constraint(s) and/or packet error (outage) requirements are assigned a higher “water-level” than users with fewer constraint(s)/requirements.
The optimal delay-sensitive subcarrier assignment in the presence of CSIT error is decoupled among subcarriers and hence has linear complexity with respect to the number of users. Asymptotic multi-user diversity gain using the delay-sensitive scheduler of the present invention are also analyzed below. In addition, by considering CSIT error statistics in the various cross layer scheduling embodiments, some non-limiting simulated results are presented that show a robust, advantageous performance enhancement and simultaneous satisfaction of heterogeneous delay requirements of users even at moderate to high CSIT error levels.
Referring to
Referring again to
Let i denote the subcarrier index and j denotes the user index. The received symbol Yij at jth mobile user 34j on i subcarrier 33i is:
Y
ij
=h
ij
X
ij
+Z
ij
where Xij is the data symbol from the base station to the jth mobile user 34j on subcarrier i 33i, hij 350 is the complex channel gain of ith subcarrier 33i for the jth mobile user 34j which is independently and identically distributed (i.i.d.) zero mean complex Gaussian with unit variance and Zij is the zero mean complex Gaussian noise with unit variance.
Further, the transmit power allocated at 328 from the base station to user j 34j through subcarrier i 33i is given by pij=E[|Xij|2]. The subcarrier allocation strategy is SN
where PTOT is the available total average power in the base station.
Referring again to
ĥ
ij
=h
ij
+Δh
ij
where {Δhij} are i.i.d. Gaussian random variables with zero mean and variance σΔH2. Assuming minimum mean squared error (MMSE) estimation, the CSIT error Δhij and ĥij are uncorrelated, i.e.:
E[Δhijĥij]=0.
Information theoretical capacity is used as the abstraction of the multi-user physical layer model in order to decouple the problem from specific implementation of coding and modulation schemes. Shannon's capacity can be achieved by random codebook and Gaussian constellation at the base station. Hence, again with respect to
where I(Xij;Yij|hij) denotes the conditional mutual information. This maximal achievable rate is a function of the CSIT hij which is unknown to the base station. Hence, given any estimated CSIT ĥij, some uncertainty remains on actual capacity cij, and packet transmission outage is possible when the scheduled data rate rij (bits/s/Hz) 322 exceed actual capacity. Accounting packet outage, instantaneous goodput (which measures the total instantaneous bits/s/Hz successfully delivered to user j) of jth user 34j is defined as:
Hence, average goodput of user j
where Pout,i=1−Pr(rij≦cij|Ĥ) is the packet outage probability conditioned on the CSIT realization Ĥ.
Referring again to
With further reference to
Referring again to
as the optimization objective to account for potential packet outage, the cross layer problem can be formulated as follows.
Find optimal rate, subcarrier, and power allocation policies (RN
where expectation E[.] is taken over all system state χ=(ĤN
In the optimization problem above, constraints (C1) and (C2) are used to ensure only one user 34j can occupy a subcarrier i 33i at one time. Constraint (C3) is used to ensure transmit power would only take positive value, (C4) is the average total power constraint, (C5) is to ensure the outage probability ε specified by applications requirements and (C6) is the average delay constraint where E[{tilde over (W)}j] is the system time (including waiting time and service time) of user j 34j.
Before the optimization problem above can be solved, the delay constraint (C6) is expressed in terms of physical layer parameters according to the following lemma from queuing analysis:
Lemma 1: A necessary and sufficient condition for the constraint (C6) is
where Xj is the service time of the packet of user j 34j, Δj is the arrival rate 31j of user j 34j, Tj is the average delay requirement of user j 34j, ts is the duration of the scheduling slot. Sj and
From Lemma 1, the constraint (C5) can be transformed to an equivalent rate constraint that directly relates scheduled data rate Rj of user j 34j to the user characteristic tuple [λj, Tj], and also the packet size F.
Corollary 1: A necessary and sufficient condition for the constraint (C6) when Tj→∞ is E[SjRj](1−Pout,i)≧Fλj.
This corollary shows that average effective scheduled data rate E[SjRj](1−ε) of user j 34j (with Pout,i=ε accounted) should be at least the same as bits arrival rate to user j's queue at 31j (regardless of the delay concerned) in order to guarantee stability of the queue.
Corollary 2: A necessary and sufficient condition for the constraint (C6), called the equivalent rate constraint, is given by E(SjRj)(1−Pout,i)≧ρj(λj,Tj,F) where
ρj(λn,Tj,F)=((2Tjλj+2)+√{square root over ((2Tjλj+2)2+8Tjλj)})(F/4Tj)
Lemma 1 differs from standard Pollaczek-Khinchin formula for delay modeling in fixed line system in two ways. Specifically, in the present invention, the effects of packet errors (and retransmission) as well as the effect of users not being selected in the current time slot have to be addressed in the framework.
The optimization problem is a mixed combinatorial (in {sij}) 320 and convex (in {pij}) optimization problem. One possible solution to the optimization problem is to first fix each sij 320 and solve convex sub-problem in {pij}, and then exhaustively search through {sij} 320 for the one that gives largest goodput
However, the total search space in this way is NfK which is computationally very inefficient even for moderate Nf. The search for optimal {sij} 320 can be decoupled between the Nf subcarriers 331, . . . , 33Nf and hence, only with complexity Nf×K only.
Given any CSIT estimate ĥij, the actual CSIT ĥij is Gaussian distributed with mean and variance given by Eh|ĥ[hij|ĥij]=ĥij and Eh|ĥ[(hij−hij)*(hij−ĥij)|ĥij]=σΔII2, respectively. Hence, |hij|2/σΔII is a non-central chi-square random variable with two degrees of freedom and non-central parameter θ=|ĥij|2/σΔH2 having c.d.f Fχ
r
ij=log2(1+pijφij|ĥij|2), where φij=Fχ
From corollary 2 and the above equation, the optimization problem can be reformulated as follows:
where σ′j(λj,Tj,F)=σj(λj,Tj,F)/(BW/NF), and BW is the total bandwidth of the OFDM system.
This optimization problem is also a mixed integer and convex optimization problem. In order to make the problem more traceable, constraint (C1) is replaced to let the integer sij be further relaxed to be a sharing factor sij∈[0,1] (indicating the fraction of time that the user j 34j would have to occupy the subcarrier i 33i) and set {tilde over (p)}ij=pijsij, so optimization the problem above is reformulated as a convex optimization problem. Using Lagrange Multiplier techniques, the following Lagrangian is obtained:
where μ≧0, γj≧0, φi are Lagrange multipliers. After finding KKT conditions through this Lagrangian, the following optimal power and subcarrier allocation is stated in Theorem 1.
Theorem 1: Given the CSIT realization Ĥ=[ĥij], the optimal subcarrier allocation Sopt(Ĥ)=[sij] can be decoupled between Nf subcarriers 331, . . . , 33Nf and is given by:
The corresponding optimal power allocation Popt(Ĥ)=[pij]
where cj=(1+γj)(1−ε)/μ is called the water-level of user j 34j and where (x)+ max(0,x).
In Theorem 1, the subcarrier allocation strategy above can be implemented by a greedy algorithm with linear complexity of K, and the optimal power allocation Popt(Ĥ)=[pij] can be interpreted as a multi-level water-filling strategy. This means that those users 341, . . . , 34K with urgent packets have to transmit at a higher power level (depending on the urgency), while non-urgent users, i.e., those users with average delay strictly less than a delay deadline, are allocated with the same power level. A more stringent target outage probability requirement can also lead to a higher water-level.
It is noted that some user requirement specifications may not lead to a feasible solution to the above derived reformulated optimization problem. The minimum required power Pmin to support delay constraints for all users specified in the above reformulated optimization problem is given by:
where cj is the solution to:
i.e., all users' equivalent rate requirements ρ′j are barely satisfied.
Supposing PTOT≧Pmin, the Lagrange multipliers μ, γj can be found iteratively by first fixing μ, then finding the corresponding γj for all j 34j based on known algorithms, and then μ is updated based on the power consumption using γj. The process iterates until the following systems of equations are satisfied:
Asymptotic Multiuser Diversity Gain
As mentioned, multi-user diversity gain of cross layer OFDMA schedulers have been studied without delay constraints and having assumed availability of perfect CSI. The order of growth of multi-user diversity gain is indicated as Θ(ln(K)) as K→∞. The multi-user diversity gain using scheduler in accordance with embodiments described herein under heterogeneous delay constraints and imperfect CSIT is shown below, in connection with an OFDMA system with K users 341, . . . , 34K is considered (K1 delay sensitive Class 1 users and K2 delay insensitive Class 2 users).
Given PTOT≧Pmin, with large number of users K (=K1+K2), the following lemma summarizes the multi-user diversity gain by the scheduler of the present invention for an OFDMA system.
Lemma 2: For large number of users K1 and K2, with fixed equivalent rate requirements ρ′1 and ρ′2, the conditional multi-user diversity gain for both class 1 and 2 (represented as a function of σΔII2<1) is given by:
The effect of the scheduler of the present invention upon multi-user diversity gain (for the case of K2=MK1,K1→∞ where M is a constant) is clear from the intuition brought by Lemma 2, noting the impact of the two practical factors addressed (e.g., the heterogeneous delay requirements and imperfect CSIT).
Impact of heterogeneous class: Embodiments of the scheduler can still retain the same order of multi-user diversity gain Θ(ln(K)) as K→∞, even after the heterogeneous delay constraints are imposed. This is because advantageously, each subcarrier 331, . . . , 33Nf is assigned to the best user from Class 1 and Class 2. Since the best user within class g is chosen according to a purely opportunistic scheduler, the conditional multi-user diversity gain over a static scheduler (conditioned on class g) is given by ln(Kg) as is shown for single class scheduling.
Impact of imperfectness of CSIT: Since the factor Fχ
Simulated results of the above embodiments can be shown using Monte Carlo simulation to illustrate the performance of the cross layer scheduler for OFDMA systems with heterogeneous applications in the presence of CSIT error. The CSIT error considerate scheduler of the present invention is compared with the performance the CSIT error inconsiderate scheduler, e.g., the ideal scheduler assuming availability of perfect CSIT, which treats the outdated CSIT estimate as perfect CSIT, otherwise referred to as a naive scheduler, and the conventional baseline reference—static power and subcarrier assignment.
An OFDMA system is considered with total system bandwidth of 1.024 MHz consisting of 64 subcarriers 331, . . . , 33Nf and 5 users 341, . . . , 34K having 5 independent paths. The duration of a scheduling slot is assumed to be 2 ms an all mobile users 341, . . . , 34K suffer the same the path loss from the base station. The target outage probability of each subcarrier 331, . . . , 33Nf is set to Pout, i=0.01. Two classes of users 341, . . . , 34K are considered in the system 300, with arrival rates 311, . . . , 31K and delay requirements of each class being specified by:
(λ,T)={(λ1,T1),(λ2,T2)} (packets per time slot, time slots).
The system also contains some unclassed users having no delay constraint (with requirements of 1000 time slots). Each packet consists of 1.024 kbits and each point in
Referring to
Furthermore,
Next, at 730, the scheduling results are formed based on the user delay sensitivity requirements specified by users, estimated CSIT information for the users, and the system queue state information for the applications. At 740, optimal power, data rate, and at least one subcarrier are allocated for a transmitter transmitting to the users based, at least in part, on the cross layer scheduling result. At 750, data is transmitted according to the allocation of step 740.
The optimal allocation includes optimizing average total throughput of the wireless communication system subject to the users delay sensitivity requirement. Diversity gain of the users increases at a rate of log(K) with the K users and decreases proportionally with CSIT error variance of the estimated CSIT information.
A system that implements the above process in an OFDMA system includes a cross layer scheduler component that allocates system subcarriers and power to form a transmission schedule for user devices based on CSIT error information and based on delay requirements specified by user devices. The system can include a broadcasting component that transmits to one or more users based, at least in part, on the transmission schedule. The cross layer scheduler component allocates power and system subcarriers to satisfy the delay requirements. The cross layer scheduler component allocates power and system subcarriers to satisfy a data rate imposed by the delay requirements. The cross layer scheduler component thus can guarantee a fixed target outage probability for the heterogeneous user devices.
In this regard, the allocation of subcarriers, power, and data rate resources is based on the at least one delay requirement and based on an estimate of the current CSIT information. As a result of the allocation, the data is received according to an optimal average total throughput of the wireless communication system subject to the users delay requirement.
Although not required, the claimed subject matter can partly be implemented via an operating system, for use by a developer of services for a device or object, and/or included within application software that operates in connection with one or more components of the claimed subject matter. Software may be described in the general context of computer-executable instructions, such as program modules, being executed by one or more computers, such as clients, servers, mobile devices, or other devices. Those skilled in the art will appreciate that the claimed subject matter can also be practiced with other computer system configurations and protocols, where non-limiting implementation details are given.
With reference to
Computer 910 can include a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer 910. By way of example, and not limitation, computer readable media can comprise computer storage media and communication media. Computer storage media includes volatile and nonvolatile as well as removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CDROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by computer 910. Communication media can embody computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and can include any suitable information delivery media.
The system memory 930 can include computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM) and/or random access memory (RAM). A basic input/output system (BIOS), containing the basic routines that help to transfer information between elements within computer 910, such as during start-up, can be stored in memory 930. Memory 930 can also contain data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit 920. By way of non-limiting example, memory 930 can also include an operating system, application programs, other program modules, and program data.
The computer 910 can also include other removable/non-removable, volatile/nonvolatile computer storage media. For example, computer 910 can include a hard disk drive that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive that reads from or writes to a removable, nonvolatile magnetic disk, and/or an optical disk drive that reads from or writes to a removable, nonvolatile optical disk, such as a CD-ROM or other optical media. Other removable/non-removable, volatile/nonvolatile computer storage media that can be used in the exemplary operating environment include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM and the like. A hard disk drive can be connected to the system bus 921 through a non-removable memory interface such as an interface, and a magnetic disk drive or optical disk drive can be connected to the system bus 921 by a removable memory interface, such as an interface.
A user can enter commands and information into the computer 910 through input devices such as a keyboard or a pointing device such as a mouse, trackball, touch pad, and/or other pointing device. Other input devices can include a microphone, joystick, game pad, satellite dish, scanner, or the like. These and/or other input devices can be connected to the processing unit 920 through user input 940 and associated interface(s) that are coupled to the system bus 921, but can be connected by other interface and bus structures, such as a parallel port, game port or a universal serial bus (USB). A graphics subsystem can also be connected to the system bus 921. In addition, a monitor or other type of display device can be connected to the system bus 921 via an interface, such as output interface 950, which can in turn communicate with video memory. In addition to a monitor, computers can also include other peripheral output devices, such as speakers and/or a printer, which can also be connected through output interface 950.
The computer 910 can operate in a networked or distributed environment using logical connections to one or more other remote computers, such as remote computer 970, which can in turn have media capabilities different from device 910. The remote computer 970 can be a personal computer, a server, a router, a network PC, a peer device or other common network node, and/or any other remote media consumption or transmission device, and can include any or all of the elements described above relative to the computer 910. The logical connections depicted in
When used in a LAN networking environment, the computer 910 is connected to the LAN 971 through a network interface or adapter. When used in a WAN networking environment, the computer 910 can include a communications component, such as a modem, or other means for establishing communications over the WAN, such as the Internet. A communications component, such as a modem, which can be internal or external, can be connected to the system bus 921 via the user input interface at input 940 and/or other appropriate mechanism. In a networked environment, program modules depicted relative to the computer 910, or portions thereof, can be stored in a remote memory storage device. It should be appreciated that the network connections shown and described are exemplary and other means of establishing a communications link between the computers can be used.
Turning now to
As one of ordinary skill in the art can appreciate, the exemplary GSM/GPRS environment and services described herein can also be extended to 3G services, such as Universal Mobile Telephone System (“UMTS”), Frequency Division Duplexing (“FDD”) and Time Division Duplexing (“TDD”), High Speed Packet Data Access (“HSPDA”), cdma2000 1x Evolution Data Optimized (“EVDO”), Code Division Multiple Access-2000 (“cdma2000 3x”), Time Division Synchronous Code Division Multiple Access (“TD-SCDMA”), Wideband Code Division Multiple Access (“WCDMA”), Enhanced Data GSM Environment (“EDGE”), International Mobile Telecommunications-2000 (“IMT-2000”), Digital Enhanced Cordless Telecommunications (“DECT”), etc., as well as to other network services that shall become available in time. In this regard, the timing synchronization techniques described herein may be applied independently of the method of data transport, and does not depend on any particular network architecture or underlying protocols.
In one example, packet traffic originating from mobile subscriber 1050 is transported over the air interface to a BTS 1004, and from the BTS 1004 to the BSC 1002. Base station subsystems, such as BSS 1000, are a part of internal frame relay network 1010 that can include Service GPRS Support Nodes (“SGSN”) such as SGSN 1012 and 1014. Each SGSN is in turn connected to an internal packet network 1020 through which a SGSN 1012, 1014, etc., can route data packets to and from a plurality of gateway GPRS support nodes (GGSN) 1022, 1024, 1026, etc. As illustrated, SGSN 1014 and GGSNs 1022, 1024, and 1026 are part of internal packet network 1020. Gateway GPRS serving nodes 1022, 1024 and 1026 can provide an interface to external Internet Protocol (“IP”) networks such as Public Land Mobile Network (“PLMN”) 1045, corporate intranets 1040, or Fixed-End System (“FES”) or the public Internet 1030. As illustrated, subscriber corporate network 1040 can be connected to GGSN 1022 via firewall 1032; and PLMN 1045 can be connected to GGSN 1024 via boarder gateway router 1034. The Remote Authentication Dial-In User Service (“RADIUS”) server 1042 may also be used for caller authentication when a user of a mobile subscriber device 1050 calls corporate network 1040.
Generally, there can be four different cell sizes in a GSM network—macro, micro, pico, and umbrella cells. The coverage area of each cell is different in different environments. Macro cells can be regarded as cells where the base station antenna is installed in a mast or a building above average roof top level. Micro cells are cells whose antenna height is under average roof top level; they are typically used in urban areas. Pico cells are small cells having a diameter is a few dozen meters; they are mainly used indoors. On the other hand, umbrella cells are used to cover shadowed regions of smaller cells and fill in gaps in coverage between those cells.
The word “exemplary” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, for the avoidance of doubt, such terms are intended to be inclusive in a manner similar to the term “comprising” as an open transition word without precluding any additional or other elements.
The aforementioned systems have been described with respect to interaction between several components. It can be appreciated that such systems and components can include those components or specified sub-components, some of the specified components or sub-components, and/or additional components, and according to various permutations and combinations of the foregoing. Sub-components can also be implemented as components communicatively coupled to other components rather than included within parent components (hierarchical). Additionally, it should be noted that one or more components may be combined into a single component providing aggregate functionality or divided into several separate sub-components, and that any one or more middle layers, such as a management layer, may be provided to communicatively couple to such sub-components in order to provide integrated functionality. Any components described herein may also interact with one or more other components not specifically described herein but generally known by those of skill in the art.
In view of the exemplary systems described supra, methodologies that may be implemented in accordance with the described subject matter will be better appreciated with reference to the flowcharts of the various figures. While for purposes of simplicity of explanation, the methodologies are shown and described as a series of blocks, it is to be understood and appreciated that the claimed subject matter is not limited by the order of the blocks, as some blocks may occur in different orders and/or concurrently with other blocks from what is depicted and described herein. Where non-sequential, or branched, flow is illustrated via flowchart, it can be appreciated that various other branches, flow paths, and orders of the blocks, may be implemented which achieve the same or a similar result. Moreover, not all illustrated blocks may be required to implement the methodologies described hereinafter.
In addition to the various embodiments described herein, it is to be understood that other similar embodiments can be used or modifications and additions can be made to the described embodiment(s) for performing the same or equivalent function of the corresponding embodiment(s) without deviating therefrom. Still further, multiple processing chips or multiple devices can share the performance of one or more functions described herein, and similarly, storage can be effected across a plurality of devices. Accordingly, no single embodiment shall be considered limiting, but rather the various embodiments and their equivalents should be construed consistently with the breadth, spirit and scope in accordance with the appended claims.
This application claims priority to U.S. Provisional Application Ser. No. 60/894,123, filed on Mar. 9, 2007, entitled “DELAY-SENSITIVE CROSS LAYER SCHEDULER SYSTEM AND METHOD”, the entirety of which is incorporated herein by reference.
Number | Date | Country | |
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60894123 | Mar 2007 | US |