WO2006046895A1 - Procede et agencement d'attribution de ressources de puissance - Google Patents

Procede et agencement d'attribution de ressources de puissance Download PDF

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Publication number
WO2006046895A1
WO2006046895A1 PCT/SE2004/001576 SE2004001576W WO2006046895A1 WO 2006046895 A1 WO2006046895 A1 WO 2006046895A1 SE 2004001576 W SE2004001576 W SE 2004001576W WO 2006046895 A1 WO2006046895 A1 WO 2006046895A1
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WO
WIPO (PCT)
Prior art keywords
power
link
links
allocating
transmission power
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Application number
PCT/SE2004/001576
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English (en)
Inventor
Lei Wan
Magnus Almgren
Per Skillermark
Original Assignee
Telefonaktiebolaget Lm Ericsson
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Application filed by Telefonaktiebolaget Lm Ericsson filed Critical Telefonaktiebolaget Lm Ericsson
Priority to PCT/SE2004/001576 priority Critical patent/WO2006046895A1/fr
Publication of WO2006046895A1 publication Critical patent/WO2006046895A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/30—TPC using constraints in the total amount of available transmission power
    • H04W52/34—TPC management, i.e. sharing limited amount of power among users or channels or data types, e.g. cell loading
    • H04W52/346—TPC management, i.e. sharing limited amount of power among users or channels or data types, e.g. cell loading distributing total power among users or channels
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/38—TPC being performed in particular situations
    • H04W52/42—TPC being performed in particular situations in systems with time, space, frequency or polarisation diversity

Definitions

  • the present invention relates to communication systems in general, specifically to power allocation in such systems.
  • the total transmission power of a base station is a resource that is shared by multiple users as well as multiple links. As there is a limit in the total transmission power of the base station, the power assigned to each channel or link and the number of channels or links that can be accommodated are limited. Therefore, power resource allocation is crucial to the capacity of communication systems.
  • the first strategy is to maintain a constant demodulated quality at the receiver, i.e. reaching the required decoding performance with a certain averaged demodulated Signal to Interference Ratio (SIR), such as the power control strategy in Wireless Code Division Multiple Access (WCDMA) systems.
  • SIR Signal to Interference Ratio
  • WCDMA Wireless Code Division Multiple Access
  • the second strategy is to transmit higher power during good channel conditions than in bad channel conditions in order to maximize the channel capacity for a certain total transmitted power, such as the so called water-filling principle applied in systems such as Multiple-Input Multiple- Output (MIMO) systems and Orthogonal Frequency Division Multiplex (OFDM) systems.
  • MIMO Multiple-Input Multiple- Output
  • OFDM Orthogonal Frequency Division Multiplex
  • the third strategy is to keep the transmit power fixed and adapt modulation and coding based on channel quality (like in HSDPA).
  • the traditional water-filling principle is widely used in capacity analyses, wliich is to maximize the channel capacity based on the normalized Shannon channel capacity with AWGN inputs.
  • the data cannot be modulated to Gaussian distributed transmitted signals in real systems; therefore, the traditional water-filling principle is not an optimal power allocation method for discrete or digital modulation.
  • power resources are usually allocated to meet the bit-rate requirement of a certain service, but not to maximize the channel capacity.
  • maximizing the channel capacity does not mean maximizing the system capacity. Therefore, it is important to allocate the power to meet the bit-rate requirement of the service with the highest power efficiency, i.e. with causing the lowest interference to other users in the system.
  • An object of the present invention is to enable improved power allocation in a communication system
  • Another object is to enable improved power allocation for digital modulation.
  • a specific object is to enable improved power allocation based on the traditional water-filling principle.
  • the present invention provides a method for enabling improved power allocation based on the traditional water-filling principle, wherein transmission power is allocated to a plurality of links based on the mutual-information expression for digital modulation.
  • the present invention enables improved power allocation with a power constraint, whereby the channel capacity is maximized.
  • the present invention enables improved power allocation with an information requirement, whereby the power is minimized.
  • Fig. 1 is a schematic illustrating a telecommunication system
  • Fig. 2 is a graph illustrating the relationship between the symbol information and the signal to interference ration for different modulations
  • Fig. 3 is a graph illustrating the logarithm-scale of the symbol information of Fig. 2;
  • Fig. 4 is a schematic illustration of a modulation and coding model
  • Fig. 5A is a schematic illustration of a telecommunication system in which an embodiment of the invention can be utilized
  • FIG. 5B is a schematic illustration of another telecommunication system in which an embodiment of the invention can be utilized;
  • Fig. 6 is a flow diagram illustrating embodiments of methods according to the invention.
  • Fig. 7 is a schematic block diagram of an embodiment of a method of the present invention.
  • Fig. 8 is a schematic block diagram of another embodiment of a. method according to the invention.
  • Fig. 9 is a schematic illustration of an embodiment of an arrangement axcording to the invention.
  • Power allocation according to the so called water-filling principle allocates the available transmission power among different links to maximize the channel capacity.
  • the traditional water-filling principle is based on the normalized Shannon channel capacity with Additive White Gaussian Noise (AWGN) inputs, which does not present a very accurate information description of the digital modulation in the real system; therefore, the traditional water- filling principle is not optimal for digital modulation.
  • AWGN Additive White Gaussian Noise
  • the present invention presents an optimal power allocation method and a corresponding simplified suboptimal method for discrete or digital modulation, i.e. the water-filling principle based on the mutual information (MI) or its approximate expressions for digital modulation.
  • MI mutual information
  • the invention is based on the recognition that the Link-to-system interface for a telecommunication system can be modeled more accurately directly based on the so- called mutual information (MI) expression. Also, the MI can be mapped directly to the Block Error Rate (BLER) to make the quality model simpler.
  • MI Block Error Rate
  • L2S interface studies by the inventors show that the mapping from a multi-state cJiannel to the decoding quality can be described very well by the mutual information (MI) concept.
  • MI Mutual information
  • MI Exponential Effective SNR Mapping
  • cut-off rate cut-off rate
  • logarithmic ESM logarithmic ESM
  • a schematic telecommunication system illustrated in Fig. 1, comprising a transmitter Tx comprising a source node, a coder and a modulator, a channel, and a receiver Rx comprising a demodulator, a decoder and a destination node. It is understood that the receiver and the transmitter can be located at a same node or at different nodes in a telecommunication system; examples of such nodes are mobile stations MS and base stations BS.
  • the information from the source node is carried by the soft outputs of the demodulator.
  • the classical information value from information theory is the so called mutual information MI between channel input and output, i.e. between encoder-output bit and decoder-input soft bit.
  • the channel coding theorem states that an ideal codec is capable of transmitting reliably at a coding rate equal to thte mutual information of the channel.
  • the information measure based on the channel capacity can be expressed as the modulated Symbol-level mutual Information (SI) value. With the symbol SIR of ⁇ ⁇ defined as
  • SI is denoted by I( ⁇ ⁇ ) :
  • P(X) is the a-priori probability of X
  • P(Y ⁇ x, ⁇ ⁇ ) is the probability density function of Y conditioned on transmit symbol X and parameterized by channel state ⁇ y . .
  • the behavior of a certain codec can be expressed as the mutual information per coding block.
  • the channel capacity is the accumulation of the S/:s -within the block. Assuming the received coding block experiences multiple channel state ⁇ Y ⁇ , ⁇ 2 '- ⁇ > Y j ⁇ > me mutual information is further defined in different levels:
  • Block error rate i.e. the ratio of the error blocks over the total transmitted blocks.
  • Frame information i.e. received decoded bit information within one coding block
  • Block success rate i.e. normalized FI
  • R mfoblts is the transmission rate of the information bits
  • T codmgblock is the period of one coding block.
  • the modulation model only deals with the symbol-level mutual information SI, as defined in Equations (1) and (2) for different modulation constellations.
  • the channel capacity for an AWGN channel without bandwidth limit is:
  • Figure 2 and Figure 3 illustrates the mutual information SI:s of different modulations, e.g. BPSK 5 QPSK, 8PSK, 16QAM and 64QAM, as well as the Shannon channel capacity.
  • SI the capacity of an M-order constellation cannot be higher than log 2 M, but it can be quite close to Shannon channel capacity at very low SIR values in case of a perfect knowledge of ⁇ ,-.
  • SI is larger for a higher-order modulation in case of a perfect knowledge of the channel.
  • ⁇ j it can be expected in case of imperfect channel estimation that the information content will be limited by the estimation of ⁇ j .
  • the coding quality model for a multi-state channel includes 4 steps as follows:
  • Step 1 For a set of soft outputs of the demodulator with the multiple channel states ⁇ /], ⁇ 2 , ..., TJ), ⁇ SI J , SI 2 , ..., SIj] are calculated by checking the look-up table of mutual information for a certain constellation, as described by the Modulation Model described earlier.
  • Step 2 Select the look-up tables for a codec. It is generated based on AWGN simulation results, which should not be influenced by the modulation modes.
  • the look-up tables of RBI to FI and RBIR to BLER are used.
  • Step 3 Collect RBI or RBIR by Equation (3) or (4).
  • a modification is needed in Equation (3) by introducing a correctness for RBI, named as JRBI adjusting factor RBI cod , as follows:
  • Step 4 Get the quality indicators by checking the AWGN look-up tables.
  • Figure 4 illustrates the previously described modulation model and coding model based on the mutual information expression.
  • modulation/demodulation behaviour and coding/decoding behaviour are independent of each other; therefore they can be modelled individually.
  • the modulation model is quite accurate and simple for different constellations, without any adjusting factor.
  • the coding correctness is still needed for those non-optimal decoding algorithms.
  • the optimal power allocation method can be classified into two categories:
  • the power constraint is set by the hardware limitation.
  • link-adaptation helps to allocate resource among users or link/channels according to the channel conditions and the QoS requirement of the service as well. This method tries to allocate the lowest power that can meet the information requirements by link-adaptation. Above two methods are adaptable to different systems. Generally, the method based on the power constraint is suitable (but not limited to) MIMO, and the other one based on the information constraint is better for the time-domain, frequency domain, code- domain and space-domain channel allocation in a system, such as OFDM.
  • FIG. 5A is a schematic illustrating a telecommunication system comprising a base station BS communicating with a mobile station MS over a link comprising a plurality of sub-links or sub ⁇ channels or sub-carriers L l, L2, L3, or equivalent orthogonal sub-links Ll, L2, L3.
  • Fig. 5B which comprises a base station BS communicating over a plurality of links, or equivalent orthogonal sub-links Ll, L2 L3 with a plurality of mobile stations MSl, MS2, MS3. It is understood that similar scenario could include one mobile station MS communicating with a plurality of base stations BS, or a base station BS communicating with a plurality of mobile stations MS.
  • a transmitting unit is capable of transmitting over a plurality of links and consequently needs to have some strategy for allocating transmission power to at least some of the plurality of links.
  • SIR signal to interference ratio
  • Equation (1) the symbol-level mutual information (SI) is denoted by 1((EJN Q ) 1 ).
  • SI symbol-level mutual information
  • the received block information (RBI) of a total of N links/carriers can be expressed as:
  • the power constraint is set by the hardware limitation, i.e. there is an upper limit to the available transmission power.
  • the water filling expression based on the power constraint will be described in the context of a MIMO system, but Is equally adaptable to similar systems.
  • Equation (14-) the water- filling principle based on mutual information allocates power to maximize the following Lagrange function:
  • step SlO the available links/carriers Ll, L2, L3 are sorted, since the channel or link with better quality will be allocated more power, according to decreasing predicted quality ⁇ j ⁇ 2 , i. e.
  • ⁇ is the path gain of the z-th channel or link and cf t is the corresponding noise variance.
  • step SI l the power of the i -th link/carrier can be expressed according to:
  • K denote the number of links/carriers with transmitted power larger than zero, i.e. Pi,i ⁇ ⁇ >0, K ⁇ N. No power will be allocated to the links with worse channel conditions, i.e.
  • step S 12 the SIR of the best link/carrier, i.e. (EJN Q ⁇ , can be obtained by Equation (21), and the individual transmission power of all the links/carriers can be further calculated by Equation (11) and (19).
  • dI((E/N 0 )i) can be further derived by Equation (21), which relates to K.
  • Equation (21) relates to K.
  • step S 14 the available total transmission power is allocated to the selected links/carriers based on the calculated quality target and the link predictions.
  • the above described embodiment uses the ⁇ S7R as the quality target; it is however equally possible to utilize some other quality target such as RBI.
  • MI Exponential Effective SIR Mapping
  • the RBI for an M-order modulation based on EESM can be expressed as:
  • I EESM ⁇ (EJ N 0 )J ⁇ (l - exp - - log 2 M (24)
  • ⁇ c is an adjusting factor for a certain modulation and coding scheme (MCS).
  • Equation (19) can be rewritten as:
  • Equation (27) can then be rewritten according to:
  • the constraint for this embodiment is the RBF requirement, denoted as RBI ⁇ a ⁇ get according to:
  • step S20 the water-filling principle according to the embodiment of the invention tries to minimize the total transmitted power, i.e. to minimize the Lagrange function:
  • Equation (3 1) and Equation (33) are used to decide the power P 1 . It can also be expressed as Equation (19), and the corresponding K, i.e. number of links/channels with transmitted power larger than zero, is determined by Equation (23 ). The main difference from the previously described embodiment with power constraint is P 1 .
  • the power of the best link/channel P 1 is, in step S22, determined by:
  • Equation (21) should be used instead of Equation (27) to determine the power of the best link/channel Ll, L2, L3, and link-adaptation should adjust the modulation mode, the coding mode or the transmitted bit-rate accordingly.
  • K The number of links/channels Ll, L2, L3 that will be allocated power larger than zero, K is determined by:
  • Equation (28) should be used instead, and link-adaptation should adjust the modulation mode, the coding mode or the transmitted bit-rate accordingly.
  • Power allocation among different channels can be performed along frequency domains (the term channels represent different carriers), along space domain (channels represent different Rx and Tx antenna links); and along time domain (channels correspond to different time slots).
  • the arrangement according to the invention comprises an input/output unit I/O, a sorting unit 11, a calculating unit 12 and a selecting unit 13.
  • the sorting unit 11 is adapted to sort the plurality of links according to decreasing predicted quality. It is equally possible to sort according to some other criteria.
  • the calculating unit 12 is adapted to calculate a respective quality target based on the individual mutual information for eacli link, for the case of a power constraint.
  • this quality target is the signal to interference ration of the link.
  • the selecting unit 13 is adapted to select which links should be allocated transmission power based on the link predictions and the SIR target.
  • the power allocation arrangement 10 is then adapted to allocate power to tlxe selected links.
  • the arrangement 10 is adapted to allocate power to at least one of a plurality of links Ll, L2, L3 based on an information constraint; this will also be described with reference to Fig. 6.
  • links Ll, L2, 1-3 can be orthogonal links or sub-links to a common link.
  • the calculating unit 12 is adapted to calculate the power of the strongest channel or link Ll, L2, L3.
  • the selecting unit 13 is then adapted to select which links should be allocated transmission power, based on the link predictions and the power, and how also much power each selected links should receive.
  • the power allocation unit 10 is adapted to enable allocation of the calculated power to the selected links.
  • the power allocation arrangement 10 can be configured as one unit and located in a receiving unit in a mobile station MS or a base station BS; or as separated units distributed at the receiving unit and the transmitting unit. For the later case, measurements are preferably performed at the receiving unit and reported to the transmitting unit where the power allocation algorithm is performed. Also other locations are possible.
  • the power allocation method is based on the mutual information of the discrete or digital modulation or its approximate expressions, the method is better than the traditional water-filling method based on the Shannon normalized channel capacity, which is for AWGN modulated signals.
  • this invention proposes the allocation strategy with information constraint as well, which is more suitable to be combined with link-adaptation, and hence to maximize the system capacity.
  • maximizing a single link/channel capacity is not equivalent to maximizing the system capacity, because the transmitted power in one link/channel causes the interference to other link/channels.
  • Combining link-adaptation with the power allocation unit will use both the channel resource and the radio resource more efficiently than link-adaptation itself or single power allocation itself.
  • the telecommunication system in which the invention can be implemented belongs to one of a MIMO 5 OFDM, Multi-slot-TTI (one coding block consists of multiple time slots), multi-code (one coding block is transmitted by multiple codes).

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

Dans un procédé et un agencent d'attribution de puissance dans un système de télécommunication utilisant le principe de remplissage d'eau, la puissance de transmission est attribuée à une pluralité de liaisons ou de canaux d'après l'expression au moins d'information mutuelle pour une modulation numérique. Selon une variante, la puissance est attribuée par contrainte de puissance et selon une autre variante, la puissance est attribuée selon une contrainte ou une condition requise d'information.
PCT/SE2004/001576 2004-10-29 2004-10-29 Procede et agencement d'attribution de ressources de puissance WO2006046895A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101110808B (zh) * 2006-07-19 2010-05-12 上海无线通信研究中心 Ofdma系统中结合自适应调制编码的功率分配方法

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
BROMERG M.C. ET AL: "Using information theory to optimize wireless networks.", IEEE WIRELESS COMMUNICATIONS AND NERWORKING CONFERENCE., vol. 3, 16 March 2003 (2003-03-16) - 20 March 2003 (2003-03-20), pages 1709 - 1715, XP010640028 *
YOO T. ET AL: "Capacity of fading MIMO channels with channel stimation error.", IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS., vol. 2, 20 June 2004 (2004-06-20) - 24 June 2004 (2004-06-24), pages 808 - 813, XP010710433 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101110808B (zh) * 2006-07-19 2010-05-12 上海无线通信研究中心 Ofdma系统中结合自适应调制编码的功率分配方法

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