WO2014082264A1

WO2014082264A1 - Method and apparatus for cognitive radio networks

Info

Publication number: WO2014082264A1
Application number: PCT/CN2012/085576
Authority: WO
Inventors: Chaofeng LI; Ming Lei; Feifei Gao; Zhong Chen
Original assignee: Nec (China) Co., Ltd.
Priority date: 2012-11-29
Filing date: 2012-11-29
Publication date: 2014-06-05
Also published as: CN104904288A; CN104904288B

Abstract

Methods and apparatuses for sensing and power allocation for cognitive radio (CR) networks are provided. The method comprises: receiving a sequence of signals from a primary node with multiple primary transmit powers; sensing a status of the primary node based on the sequence of signals; recognizing at least one feature of the primary node based on the status of the primary node and the sequence of signals; and determining at least one transmission parameter for a secondary node based on the at least one feature.

Description

METHOD AND APPARATUS FOR COGNITIVE RADIO NETWORKS

TECHNICAL FIELD [0001] Embodiments of the present invention generally relate to communication techniques. More particularly, embodiments of the present invention relate to a method, an apparatus, a network node, and a computer program product for cognitive radio networks.

BACKGROUND

[0002] This section introduces aspects that may help facilitate a better understanding of the invention(s). Accordingly, the statements of this section are to be read in this light and are not to be understood as admissions about what is in the prior art or what is not in the prior art.

[0003] Cognitive radio (CR) has been recognized as a potential technology to improve spectrum utilization and to solve the spectrum scarcity problem in the next generation of wireless communications. A secondary user (SU) in a CR network is allowed to access the spectrum licensed to a primary user (PU) if the spectrum is not utilized by the PU or the interference to the PU is below a given level.

[0004] Currently, there exist three main spectrum access approaches for CR networks: i) Underlay or the so called spectrum sharing scheme, where the SU is allowed to coexist with the PU as long as the quality of service (QoS) of the PU is protected; ii) Opportunistic spectrum access, where the SU can only access the primary bands when the PU is detected to be idle; and iii) the combination of the first two, i.e., sensing-based spectrum sharing, where the SU first senses the frequency spectrum to determine the status of the PU (active/idle) and then chooses its transmit power based on the decision.

[0005] Existing spectrum sensing schemes based on the local observation of the SU can be divided into matched filter, energy detection, cyclostationary detection, wavelet detection and covariance detection. An improved approach for spectrum sensing in CR has been suggested by Tao Cui, Feifei Gao, and Arumugam Nallanathan, entitled "Optimization of Cooperative Spectrum Sensing in Cognitive Radio" and published in IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, May 2011. In the suggested approach, multiple SUs are designed to cooperate with each other to address the problem of hidden tenninal and boundary effect, leading to cooperative spectrum sensing. To keep the QoS of PU-Ttransmitter (PU-Tx) and protect it from harmful interference, together with nonlinearity of the power amplifiers and the long-term power budget at the SU, the constraints of peak/average transmit power at the SU and peak/average interference power at the PU are adopted where optimal power allocations are derived to maximize the secondary achievable rate for different combinations of the power constraints due to the practical requirements.

SUMMARY

[0006] The inventors note that, in most of the existing works, one important assumption is that the primary transmit power is unchangeable and constant, and the sensing model is the conventional binary hypothesis testing model. However, in the modern communication systems, adaptive power allocation has been used in order to provide a constant rate due to different channel signal to noise ratio (SNR).

[0007] Therefore, it would be desirable in the art to provide solutions for sensing and/or power allocation for CR with multiple primary transmit powers.

[0008] To better address one or more of the above concerns, in a first aspect of the invention, a method for cognitive radio (CR) networks is provided. The method comprises: receiving a sequence of signals from a primary node with multiple primary transmit powers; sensing a status of the primary node based on the sequence of signals; recognizing at least one feature of the primary node based on the status of the primary node and the sequence of signals, and detem ining at least one transmission parameter for a secondary node based on the at least one feature.

[0009] In some embodiments, the at least one feature comprises at least one of a primary transmit power and a modulation and coding scheme (MCS).

[0010] In some embodiments, the step of sensing may comprise: calculating accumulated energy of the sequence of signals; and deciding the presence of the primary node by comparing the accumulated energy to a predefined threshold.

[0011] In some embodiments, the step of recognizing may comprise: defining a plurality of subspaces corresponding to the multiple primary transmit powers; and estimating which primary transmit power of the multiple primary transmit powers the primary node is using by comparing the accumulated energy to that of the plurality of subspaces.

[0012] In some embodiments, the step of determining may comprise: allocating a secondary transmit power for the secondary node based on the at least one feature by using at least one predetermined criterion. The at least one predetermined criterion may comprise one or more of the following: maximizing an average achievable rate of the secondary node; an average transmit power constraint under a predefined power; and an average interference power constraint under a maximum interference to the primary node.

[0013] In a second aspect of the invention, an apparatus is provided to implement various embodiments of the method of the first aspect of the invention. Specifically, an apparatus for cognitive radio (CR) networks is provided. The apparatus comprises: a receiving unit configured for receiving a sequence of signals from a primary node with multiple primary transmit powers; a sensing unit configured for sensing a status of the primary node based on the sequence of signals; a recognization unit configured for recognizing at least one feature of the primary node based on the status of the primary node and the sequence of signals; and a determination unit configured for determining at least one transmission parameter for a secondary node based on the at least one feature.

[0014] In a third aspect of the invention, a secondary node is provided, which comprises at least one processor and at least one memory including computer program code. The memory and the computer program code are configured to cause the apparatus to perform embodiments of the method of the first aspect of the invention.

[0015] In a fourth aspect of the invention, a computer program product is provided, which, comprises at least one computer readable storage medium having a computer readable program code portion stored thereon. The computer readable program code portion comprises program code instructions for perform embodiments of the method of the first aspect of the invention.

[0016] Particular embodiments of the subject matter described in this specification can be implemented so as to realize one or more of the following advantages.

[0017] With particular embodiments of the techniques described in this specification, schemes have been proposed for the scenario where the PU transmits with multiple primary transmit powers. The proposed schemes better suit the practical cases.

[0018] Other features and advantages of the embodiments of the present invention will also be understood from the following description of specific embodiments when read in conjunction with the accompanying drawings, which illustrate, by way of example, the principles of embodiments of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and other aspects, features, and benefits of various embodiments of the invention will become more fully apparent, by way of example, from the following detailed description and the accompanying drawings, in which:

[0020] FIG. 1 shows an example system model for the cognitive radio network;

[0021] FIG. 2 illustrates a flow chart of a method for cognitive radio networks according to embodiments of the present invention;

[0022] FIG. 3 is a schematic block diagram of an apparatus 300 that may be configured to practice exemplary embodiments of the present invention; and

[0023] Fig. 4 is a schematic block diagram of a network node that is suitable for use in practicing the exemplary embodiments of the present invention.

[0024] Like reference numbers and designations in the various drawings indicate like elements.

DETAILED DESCRIPTION

[0025] Hereinafter, the principle and spirit of the present invention will be described with reference to the illustrative embodiments. It should be understood, all these embodiments are given merely for the skilled in the art to better understand and further practice the present invention, but not for limiting the scope of the present invention. For example, features illustrated or described as part of one embodiment may be used with another embodiment to yield still a further embodiment. In the interest of clarity, not all features of an actual implementation are described in this specification. It will of course be appreciated that in the development of any such actual embodiment, numerous implementation- specific decisions should be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which will vary from one implementation to another. Moreover, it will be appreciated that such a development effort might be complex and time-consuming, but would nevertheless be a routine undertaking for those of ordinary skill in the art having the benefit of this disclosure.

[0026] The disclosed subject matter will now be described with reference to the attached figures. Various structures, systems and devices are schematically depicted in the drawings for purposes of explanation only and so as to not obscure the description with details that are well known to those skilled in the art. Nevertheless, the attached drawings are included to describe and explain illustrative examples of the disclosed subject matter. The words and phrases used herein should be understood and interpreted to have a meaning consistent with the understanding of those words and phrases by those skilled in the relevant art. No special definition of a term or phrase, i.e., a definition that is different from the ordinary and customary meaning as understood by those skilled in the art, is intended to be implied by consistent usage of the term or phrase herein. To the extent that a term or phrase is intended to have a special meaning, i.e., a meaning other than that understood by skilled artisans, such a special definition will be expressly set forth in the specification in a definitional manner that directly and unequivocally provides the special definition for the term or phrase.

[0027] FIG. 1 shows an example system model for the cognitive radio network. As shown in FIG. 1 , a CR network is considered with a pair of primary transmitter (PU-Tx) and receiver (PU-Rx), and a pair of secondary transmitter (SU-Tx) and receiver (SU-Rx) which share the spectrum with the primary band under a given interference limit. Let γ_1} γ₂, h and g denote the instantaneous channel power gains from the PU-Tx to the SU-Tx, from the PU-Tx to the SU-Rx, from the SU-Tx to the PU-Rx and from the SU-Tx to the SU-Rx, respectively. The channel gains are assumed to be ergodic, stationary and known at the SU. In practice, the SU can be provided with the channel gains of the PU, or the SU may detect the channel gains by monitoring training symbols of the PU.

[0028] FIG. 2 illustrates a flow chart of a method for cognitive radio networks according to embodiments of the present invention. The method of FIG. 2 may be performed at a secondary node (i.e, a secondary user) of a cognitive radio network.

[0029] The method begins at step S201 and proceeds to step S202, where the SU receives a sequence of signals from a PU. In the considered scenario, the PU may transmit with multiple primary transmit powers.

[0030] Then, at step S203, the SU senses a status of the PU based on the sequence of signals. The status of the PU may be present or absent. In one embodiment, the sensing is performed based on energy detection. The skilled person should appreciate that other techniques may be used to sense the status of the PU.

[0031] At step S204, the SU recognizes at least one feature of the PU based on the sensed status of the PU and the sequence of signals. The at least one feature may comprise at least one of a primary transmit power and a modulation and coding scheme (MCS). Of course, other features relating to the transmission parameters of the PU may be recognized if needed.

[0032] Then, at step S205, the SU can determine at least one transmission parameter for itself based on the at least one feature of the PU. In one embodiment, if the transmission parameter is the transmit power, the determining may comprise allocating a secondary transmit power for the SU based on at least feature (e.g., the primary transmit power) of the PU by using at least one predetermined criterion. The at least one predetermined criterion may comprise one or more of the following: maximizing an average achievable rate of the SU; an average secondary transmit power constraint under a predefined power; and an average interference power constraint under a maximum interference to the primary node.

[0033] At last, the SU can use the determined transmission parameter(s) for communication and the method ends at step S206.

[0034] Below will describe the spectrum sensing and feature recognization in detail.

The optimal sensing rule is derived based on the likelihood ratio which shows that the rule is equivalent to the energy detection rule. The feature is the primary transmit power as an example. Based on the optimal detection theory, the optimal primary transmit power is estimated and the total detection probability is derived. Then, for the case where the PU transmits with multiple primary transmit powers, a multiple-level power allocation strategy is proposed, and specifically, one secondary transmit power according to one primary transmit power.

[0035] The received si nal at the th sample at step S202, is modelled as

Where Ho an H_\ denote the hypothesis that the PU-Tx is absent and present respectively; P _i,i - l,..., N is the primary discrete transmit power satisfying O < P_{p i} < P_p,M, Vi ; s_j is the jt symbol transmitted from the PU-Tx which is assumed to follow Gaussian distribution with zero mean and unit variance, i.e., Sj ~ N(0,1) ; and tij is the additive noise assumed to follow

N(0, JV₀ ) for all cases. Assume that _j and rt_j are independent of each other.

[0036] In one embodiment, at step S203, the sensing may comprise calculating accumulated energy of the received sequence of signals. The detection statistic y using the accumulated received energy of the samples can be written as

Where M is the total number of samples received at the SU-Tx in one frame. Then the probability density functions df) of y conditioned on Ho, P_{p i} and Hi are given by:

respectively, where Γ(.) denotes the gamma function; ?τ(Ρ_ρ ,) denotes the prior probability that the PU transmits with power P_{p i} satisfying ∑"_=l ?r(P_{p i}) = Pr(H,) ; Pr(H₀) and Pr(H₁ ) are probabilities that the PU is idle and busy respectively.

[0037] The optimal detector using the likelihood ratio test can be written as:

[0038] Hence, the sensing of step S203 may further comprise deciding the presence of the PU by comparing the accumulated energy to a predefined threshold.

[0039] Since L(y) is a strictly increasing function over y , the hard decision rule where ?/ is the decision threshold, is equivalent as ^H« where Θ is the new equivalent threshold. Thus the optimal detector is the energy detector.

[0040] Then, the probabilities of false alarm and detection can be calculated as

and

Ρ_άψ) = PriHUH = (8)

Where γ(.) is the lower incomplete Gamma function.

[0041] One important mission of spectrum sensing is to detect the status (idle or busy, i.e., absent or present) of the PU. However, in the case of multiple primary transmit powers, it is also significant to estimate the primary transmit power which can be used to decide the transmit power of the SU and protect the primary transmission.

[0042] Thus, in one embodiment where the at least one feature is the primary transmit power of the PU, the recognizing of step S204 may further comprise defining a plurality of subspaces corresponding to the multiple primary transmit powers and estimating which primary transmit power of the multiple primary transmit powers the PU is using by comparing the accumulated energy to that of the plurality of subspaces.

[0043] It is a typical multiple hypotheses testing problem and the decision rule is that, if

AP_p,i \ y) > f(P_P,k \ y),vk≠i, (9) holds, the decision is P_{p i} . Substituting f{P_pJ \ y = ^P'f^^F''^j) and (4) into (9), we get the decision space for P_{p i} as S(P_P = , (10)

where d_(k

[0044] Note that, in (10), if Pr(P .) is very small, max d(k,f) can be bigger than

l≤i<(

m d(k,i) and the decision space for ^~Pr(P_pi) becomes empty. Let A_jfi = l,...K + \ be the break point and β ΐ = 1,...Κ be the corresponding power estimation in the interval [A,,/L_i+1). Obviously, we have K <N . Define = 0 and λ_κ+ι = +co , then the estimation of the primary transmit power can be written as

Pp = ft, if y e [λ,-, A_i+i), i = 1, K. (12)

[0045] The problem turns to how to decide the optimal and β_ί . The following lemma is used to solve this problem.

[0046] Lemma 1: For any constants y_l and y₂ , if y_} < y₂ , i<k and f(P_pj \ < f(P_p,_k I , we have f{P_pJ | y₂) < f{P_p<k \ y₂) .

47] Proof. First, we have

a

r with ( _/J,| _!)</(P^!^₁),from(13),wegetthat |_½) < | holds.

[0048] It follows from (11) that, d(k,i) represents the point y that/(P _Λ \y) = f(P_Pit \y)- Together with lemma 1, we can get the optimal solution of A₍. and β_ι as follows. First, at the point = 0, calculate f(P_pk\0),ke[l,N], choose the largest one denoted by i = argmax (P_{p t} [0) and set

The interation stops when i=N. The details of the algorithm are as table I. TABLE I

Optimal solution for the threshold and the power estimation.

!<κ<Λ Κίτ<Λ

- ¾^■ = Ρρ,_ί, j— j + 1.

3) X_j— -hoo, K = j— 1. stop and output.

[0049] Specially, for the case that Pr^ _f ) = Pr(P ), Vi,k, first we have, dd(k,i) _ M(N₀ + P_p,,7i) JVb + P_P,.7i _{ln +} U4)

Ppjk - PpA Pp.kll - ΡρΛΊΐ

[0050] We can easily prove that, V >0 , ^ln(l + x)<l holds and VJC<0 , (l + x) > 1 holds. Thus if k>i, ¾r^->0 holds, and d(k,i) is an increasing function over.P_pi, otherwise, d(k,i) is a decreasing function over P _k . Then for this case, (10) can be further written as

S(P_p ) = {y\d{i -l,i) <y< d(i + 1, ί)} , (15) and _j = d{i~\,i), .=P_PtJ.

[0051] Performance of the primary transmit power estimation is analyzed as follows. First, we have

Pr(i¾>,_j]Pp,i) = <( ⁱV^-) HTJ (16)

0. otherwise.

[0052] Then the total detection probability can be written as

I⁼¹

[0053] Having estimated the primary transmit power of the PU, i.e., recognizing the feature of transmit power of the PU, at step S205, the SU can determine its transmission parameter(s) based on the recognized feature of the PU.

[0054] In the conventional power allocation scheme, for the constant primary transmit power case, SU-Tx will adapt its transmit power based on the decision made during the sensing slot. When the PU is sensed as absence, the SU-Tx will transmit with higher power, otherwise, with lower power in order to reduce the interference caused to the PU.

[0055] In the embodiments of the present invention where the PU transmits with multiple primary transmit powers, to a given estimation of the primary transmit power of the PU, the SU will use one specified secondary transmit power. In other words, a multiple-level power allocation is proposed. Specifically, if the PU is sensed to be absent H₀, the SU-Tx will transmit with a power P_{s 0} , otherwise if the PU is sensed to be present with a transmit power P_p , the SU-Tx will transmit with a power P_s . The secondary transmit power can be allocated based on the estimated/recognized primary transmit power by using at least one predetermined criterion.

[0056] The at least one predetermined criterion may comprise one or more of the following: maximizing an average achievable rate of the SU; an average secondary transmit power constraint under a predefined power; and an average interference power constraint under a maximum interference to the PU. Below will describe one example for determining the optimal secondary transmit power.

[0057] Due to the limitations of the spectrum sensing techniques, the PU could be miss-detected or a false alarm could occur. Note that, the case that the PU is absent equals that the PU transmits with the power 0. Define ^_i0 = 0 as the case that the PU is absent. Then, the instantaneous transmission rate of the SU is given by

¾ = i° ₂ ( i + T ) ' ⁽¹⁸⁾ where the first index means the actual status and the second index means the decision result, while i = 0,...,N , j = 0,..., N . The subscript 0 means the status that the PU is absent, thus Ρ _Ο = 0 and Pr(/^₀) = Pr(H₀) .

[0058] Thus, the average achievable rate of the SU can be modelled as

[0059] The average secondary transmit power constraint under the parameter P_av can be written as

[0060] The SU causes interference to the PU under Hi where the primary transmit power is P_{p j},i = \,...,N and the SU transmits with any power in the set P_s ,j = 0,...,N .

Thus the average interference power constraint under maximum interference I_av is modelled as

[0061] Under the constraints discussed in the above, an optimization problem maximizing the achievable transmission rate of the SU can be formulated as

max B

p'<> (22) s.l. (20), (21). P_S;j > 0, ¾,

[0062] The following lemma will be used.

[0063] Lemma 2: Problem (22) is convex with respect to the transmit power P_{s j} under the constraints of (20) and (21).

[0064] Proof. The proof is trivial since an^ _=Q iP^HN^P^yo > »P.,< 3P.^{j ■ U}' ^V^ ^J" And the constraints (20) and (21) are both linear functions over P_s . , thus problem (22) is convex over P_{s j} .

[0065] First, we can build the lagrangian L(P_{S J}, ^) referring to problem (22) under the constraints (20) and (21) as

L{P_s , a, ,,)

where α,μ≥0 are dual variables corresponding to (20) and (21).

[0066] Then, we can build the lagrange dual optimization problem as

JPk_n Λ ^{< α}· ν-) ^{~ SU}P 24 :>0, μ>0 £Ί.^≥^ϋ

[0067] With Lemma 2, we can conclude that, the optimal value of problem (24) is equal to the problem (22). Thus we can solve the dual optimization problem (24) instead of solving (22). From (24), we have to obtain the supremum of L{P_{S }},α,μ) . To find the optimal P_{s j} , we take the derivative of L(P_{S J},a^) with respect to P_s , which can be obtained as

N

- μ∑ ιΡτίΡ_ρΛ)?ν{Ρ_Ρ Ρ_Ρ . [0068] From (25), we can see that, L£ is a decreasing function over P . . Thus if there is a unique P_{s j} > 0 that satisfies ^%^ = 0 , i.e., if

the optimal power allocation for given a and / is P_{s j}≥ 0 , otherwise, P . = 0 .

[0069] Then the optimal values of the Lagrange multipliers a and μ need to be found to obtain the optimal power allocation strategy P_{s j} . Subgradient based method are used here to find the optimal solution, where the subgradient is given by the following proposition, e.g., ellipsoid method and Newton's method.

[0070] Proposition 1: The subgradient of the Lagrange dual function g(a, /) is [ C,D] , where

P . is the optimal power allocation for fixed a and μ .

[0071] Proof. Denote ≥ 0 and μ > 0 as any feasible values of the dual function g(a^) , and P_{s j} be the corresponding optimal power allocation. To prove

Proposition 1 equals to prove that, g( , μ)≥ g(a, μ) + ([ , μ] ~[ , μ])[€, Df holds for any and μ . Then, we have

g(a, μ) = sup L(P_s,j, a, (1) = L(P_Bj, a, μ)

= L{P,_j, o, μ) + ([α, μ] - [a, μ))[ D)^T

=≤τ(α, μ) + ([ά, μ] - [ , μ})[0,Ό}^τ.

[0072] Having determined the transmission parameter(s) (e.g., the secondary transmit power) of the SU, the SU can communicate with the determined transmission parameter(s).

[0073] Simulation results show that, when the maximum interference I_BV is low, the performance of the proposed scheme is a little better than the conventional scheme. However, when the maximum interference I_a is large, the performance of the proposed scheme is significantly superior to the conventional one. Simulation results also shows that, in the practical system, the SU should first detect the primary signal and recognize the feature(s) of the PU, then allocate different transmit power or modulation and coding scheme (MCS) due to the recognized feature(s). Through this, the SU can protect the primary transmission and improve its achievable rate. The skilled in the art should appreciate that, the proposed scheme can be expended to other cases where the SU can detect the feature(s) of the PU and decide its own transmission parameters to protect the QoS of the PU and improve its throughput. For example, the SU can detect the operating frequency, modulation and coding scheme, and/or primary transmit power of the PU, and then decide its own transmission parameters. The proposed scheme may be used in an environment where multiple communication system coexist, in order to reduce interference among users. For example, a femtocell can detect the LTE system and decide its appropriate transmission parameters.

[0074] FIG. 3 is a schematic block diagram of an apparatus 300 that may be configured to practice exemplary embodiments according to embodiments of the present invention. The apparatus 300 may be incorporated in a secondary node in a CR network and be configured to perform methods of the exemplary embodiments of the present invention as illustrated with reference to FIG.2.

[0075] As shown in Fig. 3, the apparatus 300 may comprise a receiving unit 310, a sensing unit 320, a recognizing unit 330 and a determination unit 340.

[0076] The receiving unit 310 is configured to receive a sequence of signals from a PU. For example, the receiving unit 310 may receive M symbols within a frame with a sensing slot. In the considered scenario, the PU may transmit with multiple primary transmit powers.

[0077] The sensing unit 320 is configured to sense a status of the PU based on the received sequence of signals. The status of the PU may be present or absent. In one embodiment, the sensing is performed based on energy detection. In such embodiment, the sensing unit 320 further comprises a calculation unit 321 and a decision unit 322. The calculation unit 321 is configured to calculate accumulated energy of the received sequence of signals, as shown in the equation (2). The decision unit 322 is configured to make decision of the presence of the PU by comparing the accumulated energy to a predefined threshold, as described with reference to the equation (6).

[0078] The recognizing unit 330 is configured to recognize at least one feature of the

PU based on the sensed status of the PU and the sequence of signals. The at least one feature may comprise at least one of a primary transmit power and a modulation and coding scheme (MCS). Of course, other features relating to the transmission parameters of the PU may be recognized if needed, for example the operating frequency of the PU, the communication protocol of the PU, etc.

[0079] In one embodiment where the feature of the PU is the primary transmit power, the recognizing unit 330 may further comprise a definition unit 331 and a estimation unit 332. The definition unit 331 is configured to define a plurality of subspaces corresponding to the multiple primary transmit powers, as described by the equation (10). The estimation unit 332 is configured to estimate which primary transmit power of the multiple primary transmit powers the PU is using by comparing the accumulated energy to that of the plurality of subspaces.

[0080] The determination unit 340 is configured to determine at least one transmission parameter for the SU based on the at least one feature of the PU. In one embodiment, the at least one transmission parameter is the secondary transmit power of the SU. Then, the determination unit 340 may further comprise an allocation unit 341, which is configured to allocate a secondary transmit power for the SU based on the estimated primary transmit power of the PU by using at least one predetermined criterion.

[0081] To a given estimation of the primary transmit power of the PU, one specified secondary transmit power will be allocated to the SU.

[0082] The at least one predetermined criterion may comprise one or more of the following: maximizing an average achievable rate of the SU; an average secondary transmit power constraint under a predefined power; and an average interference power constraint under a maximum interference to the primary node.

[0083] Then, the SU can use the determined transmission parameter(s) for communication.

[0084] It should be understood, the units contained in the apparatus 300 are configured for practicing exemplary embodiments of the present invention. Thus, the operations and features described above with respect to FIG. 2 also apply to the apparatus 300 and the units therein, and the detailed description thereof is omitted here.

[0085] FIG 4 illustrates a simplified block diagram of a network node 400 (e.g., a secondary node) in a CR network that is suitable for use in practicing the exemplary embodiments of the present invention.

[0086] As shown in FIG. 4, the network node 400 includes a data processor (DP) 401 , a memory (MEM) 402 coupled to the DP 401 , and a suitable RF transmitter TX and receiver RX 404 coupled to the DP 401. The MEM 402 stores a program (PROG) 403. The TX/RX 404 is for bidirectional wireless communications with other network nodes. For example, the TX/RX 404 can embody the receiving unit 310 of FIG. 3 to receive a sequence of signals from a primary node (i.e., PU). [0087] The PROG 403 is assumed to include program instructions that, when executed by the associated DP 401, enable the network node 400 to operate in accordance with the exemplary embodiments of this invention, as discussed herein with the method shown in FIG 2. For example, the PROG 403 and the DP 401 may embody the sensing unit 320, the recognizing unit 330 and the determination unit 340 to perform the respective functions.

[0088J The embodiments of the present invention may be implemented by computer software executable by the DP 401 of the network node 400, or by hardware, or by a combination of software and hardware.

[0089] The MEM 402 may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as semiconductor based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory and removable memory, as non-limiting examples. While only one MEM is shown in the network node 400, there may be several physically distinct memory units in the network node 400. The DP 401 may be of any type suitable to the local technical environment, and may include one or more of general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on multicore processor architecture, as non limiting examples. The network node 400 may have multiple processors, such as for example an application specific integrated circuit chip that is slaved in time to a clock which synchronizes the main processor.

[0090] Exemplary embodiments of the present invention have been described above with reference to block diagrams and flowchart illustrations of methods, apparatuses (i.e., systems). It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by various means including computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks.

[0091] The foregoing computer program instructions can be, for example, sub-routines and/or functions. A computer program product in one embodiment of the invention comprises at least one computer readable storage medium, on which the foregoing computer program instructions are stored. The computer readable storage medium can be, for example, an optical compact disk or an electronic memory device like a RAM (random access memory) or a ROM (read only memory).

[0092] While this specification contains many specific implementation details, these should not be construed as limitations on the scope of any implementation or of what may be claimed, but rather as descriptions of features that may be specific to particular embodiments of particular implementations. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub- combination.

[0093] It should also be noted that the above described embodiments are given for describing rather than limiting the invention, and it is to be understood that modifications and variations may be resorted to without departing from the spirit and scope of the invention as those skilled in the art readily understand. Such modifications and variations are considered to be within the scope of the invention and the appended claims. The protection scope of the invention is defined by the accompanying claims. In addition, any of the reference numerals in the claims should not be interpreted as a limitation to the claims. Use of the verb "comprise" and its conjugations does not exclude the presence of elements or steps other than those stated in a claim. The indefinite article "a" or "an" preceding an element or step does not exclude the presence of a plurality of such elements or steps.

Claims

WHAT IS CLAIMED IS:

1. A method for cognitive radio (CR) networks, comprising:

receiving a sequence of signals from a primary node with multiple primary transmit powers;

sensing a status of the primary node based on the sequence of signals;

recognizing at least one feature of the primary node based on the status of the primary node and the sequence of signals; and

determining at least one transmission parameter for a secondary node based on the at least one feature.

2. The method of claim 1, wherein the at least one feature comprises at least one of a primary transmit power and a modulation and coding scheme (MCS).

3. The method of claim 1 or 2, wherein said determining comprises:

allocating a secondary transmit power for the secondary node based on the at least one feature by using at least one predetermined criterion.

4. The method of claim 3, wherein said at least one predetermined criterion comprises one or more of:

maximizing an average achievable rate of the secondary node;

an average secondary transmit power constraint under a predefined power; and an average interference power constraint under a maximum interference to the primary node.

5. The method of any of claims 1-4, wherein said recognizing comprises:

defining a plurality of subspaces corresponding to the multiple primary transmit powers; and

estimating which primary transmit power of the multiple primary transmit powers the primary node is using by comparing accumulated energy of the sequence of signals to that of the plurality of subspaces.

6. The method of any of claims 1-5, wherein said sensing comprises:

calculating accumulated energy of the sequence of signals; and deciding the presence of the primary node by comparing the accumulated energy to a predefined threshold.

7. An apparatus for cognitive radio (C ) networks, comprising:

a receiving unit configured for receiving a sequence of signals from a primary node with multiple primary transmit powers;

a sensing unit configured for sensing a status of the primary node based on the sequence of signals;

a recognization unit configured for recognizing at least one feature of the primary node based on the status of the primary node and the sequence of signals; and

a determination unit configured for determining at least one transmission parameter for a secondary node based on the at least one feature.

8. The apparatus of claim 7, wherein the at least one feature comprises at least one of a primary transmit power and a modulation and coding scheme (MCS).

9. The apparatus of claim 7 or 8, wherein said determination unit comprises:

an allocation unit configured for allocating a secondary transmit power for the secondary node based on the at least one feature by using at least one predetermined criterion.

10. The apparatus of claim 9, wherein said at least one predetermined criterion comprises one or more of:

maximizing an average achievable rate of the secondary node;

11. The apparatus of any of claims 7-10, wherein said recognization unit comprises: a definition unit configured for defining a plurality of subspaces corresponding to the multiple primary transmit powers; and

an estimation unit configured for estimating which primary transmit power of the multiple primary transmit powers the primary node is using by comparing accumulated energy of the sequence of signals to that of the plurality of subspaces.

12. The apparatus of any of claims 7-10, wherein said sensing unit comprises:

a calculation unit configured for calculating accumulated energy of the sequence of signals; and

a decision unit configured for deciding the presence of the primary node by comparing the accumulated energy to a predefined threshold.