AU2018102043A4 - Large-scale D2D Communication Method based on HARQ Assisted NOMA - Google Patents

Abstract

Embodiments of the preset application provide a large-scale D2D communication method based on HARQ assisted NOMA. This method firstly analyzes the influence of superimposed interference on the outage probability in the large-scale D2D network using the stochastic 5 geometry, then deriving the specific expression of the spectrum efficiency according to the relationship between the outage probability and spectrum efficiency, and finally constructing an optimization problem of the resource allocation based on these theoretical analysis results: the spectrum efficiency (throughput or spatial spectrum utilization) may be maximized and the reliability of the communication may be ensured via reasonably configuring information 10 transmission rate of different D2D users or even configuring the distribution density of D2D devices occupying the same time-frequency resource. Simulation and numerical results show that compared with the no-cooperative application scheme, the proposed cooperative application scheme decreases the outage probability by up to 23%. Further, the optimized LTAT of proposed scheme outperforms that of the OMA scheme by 17%. Interference user z $SI+ 4 7S2 ... Additive coding In erence .e eB Source device signal user successive interference cancellation+forward error correction coding o1 D2D user 1 Interference user D2D user 2 Interference user Fig. 1

Description

2018102043 10 Dec 2018

Large-scale D2D Communication Method based on HARQ Assisted NOMA

TECHNICAL FIELD [0001] The present application relates to a wireless communication technology filed, and more particularly to a large-scale Device-to-Device (D2D) communication method based on Hybrid Automatic Repeat Request (HARQ) assisted Non-Orthogonal Multiple Access (NOMA).

BACKGROUND [0002] According to ITU-R M.2083-0, the fifth generation (5G) and beyond of cellular networks are not only envisioned to enhance the mobile broadband services, but also to support massive number of machine type connections within the Intemet-of-Things (IoT) paradigm as well as to provide ultra-reliable low-latency communications for some services. Such new requirements impose unprecedented challenges that cannot be fulfilled via the conventional orthogonal multiple-access (OMA) with centralized base station controlled communications.

Instead, the 3 GPP considers more aggressive spectral utilization schemes such as device-to-device (D2D) communication and non-orthogonal multiple access (NOMA) to support such massive number of connections. Despite the increased interference level imposed by D2D communications, it has been shown that D2D can significantly improve the overall network spatial spectral utilization thanks to the low-power short range direct proximity transmissions

2018102043 10 Dec 2018 enabled by D2D communication. The NOMA further improves the spectrum utilization by simultaneous transmission from the same source to multiple devices on the same time-frequency resources. Specifically, NOMA leverages superposition coding (SC) along with successive interference cancellation (SIC) and multi-user diversity to efficiently enhance spectrum 5 utilization. By allocating more transmission power to the user with poorer channel condition,

NOMA can achieve a balanced tradeoff between system throughput and user fairness.

[0003] In order to further improve spectrum utilization, the present application applies the

NOMA to the D2D communication. Since the D2D communication may encounter a fatal technical bottleneck in large-scale application, i.e. a contradiction between limited spectrum 10 resources and excessive spectrum reuse, it results in that the UE has strong network aggregate interference, finally results in sharp degradation of the receiving performance of the receiving device, such as degradation of spectrum efficiency and increase of the outage probability.

However, when discussing the large-scale D2D network, the existing large amount of research does not consider the problem of how to improve the negative effect of the network aggregate 15 interference. In order to ensure the reliability of the transmission and further improve the spectrum efficiency, the present application may improve the reliability of the transmission combining the HARQ technology. It should be noted that the HARQ is a kind of technology which may effectively ensure the reliability of the transmission. The technology core is retransmission scheme and forward error correction coding. Further, the HARQ technology does

2018102043 10 Dec 2018 not necessarily need perfect knowledge of instantaneous CSIs at the source device, the source device only needs to know partial CSI or some statistical characteristics of the channel. This mode may effectively reduce frequent channel measurement and instantaneous SNR reporting, therefore, the system signaling overhead may be greatly reduced. This advantage, in turn, makes 5 the application of the D2D communication in the large-scale network possible. Due to the application of both the NOMA and HARQ, the present application may further improve the reliability of the transmission via cooperative communication, since each receiving device may receive additive coding signal. The additive signal includes the information of all users. Therefore, the user who firstly succeeds in decoding may forward decoded user information to the user.

Based on this consideration, a scheme for applying the HARQ assisted NOMA in the large-scale D2D network is needed.

SUMMARY [0004] The application of the large-scale D2D communication is used to balance load of 15 the mobile cellular network, in which the eNB is configured as the control center. However, due to the contradiction between limited spectrum resources and excessive spectrum reuse, when the D2D communication is applied in large scale, there is strong network aggregate interference between D2D devices, which results in sharp degradation of the receiving performance of the receiving device, such as degradation of spectrum efficiency and increase of the outage

2018102043 10 Dec 2018 probability. An objective of the present application is to solve the above disadvantages in the prior art and provides a large-scale D2D communication method based on HARQ assisted NOMA to improve the spectrum efficiency and reduce outage probability.

[0005] The objective of the present disclosure may be achieved via following technical scheme:

[0006] In order to reduce the interference from the eNB, in the present application, it is assumed that the D2D source device works in an overlay mode, i.e., the eNB and D2D device use the orthogonal spectrum resources. Meanwhile, it is assumed that all D2D source devices obey the Homogeneous Poisson Point Process (HPPP), which is a reasonable assumption, and its 10 effectiveness has be verified via a large amount of experimental measurement. Further, in order to reduce complexity requirement of the hardware, limit the interference level and ensure the low delay, the present application only consider direct communication between the source device and two D2D users. Meanwhile, the HARQ assisted NOMA scheme modifies the spectrum efficiency and outage probability of the large-scale D2D communication application. This kind of 15 performance improvement is based on reasonable modulation, coding selection and optimized resource configuration, the system model is shown in figure 1. The implementation steps of the specific technical scheme are shown in figure 2 and include seven steps. Detailed contents of each step are as follows:

[0007]

SI, design of an application scheme

2018102043 10 Dec 2018 [0008] in a HARQ assisted NOMA application scheme, a source device firstly generates s s codes for a signal ¹ and a signal ² via forward error correction coding which need to be transmitted to two Device-to-Device users according to the HARQ, a signal ⁺ is transmitted to the D2D users adopting the NOMA supporting multi-users simultaneous transmission, P is a power allocation factor. In order to more reasonably utilize the NOMA, the channel differences between the D2D users need to be utilized to improve the spectrum utilization, a decoding sequence is determined according to path loss of the two D2D users, a path loss model is expressed as ~ , denotes a reference path loss value with a distance of 1 meter, ^a is a path loss metric. It is assumed that the distance between the D2D user 1 and the source device is shorter than that between the user 2 and the source device, the distance between the D2D user 1 and the source device and the distance between the user 2 and the source d d d <d device are respectively defined as ¹ and ², ^{1 2}. According to NOMA, the user 1 firstly decodes the signal of user 2, cancels the interference from the user 2 utilizing the interference cancellation technology, and then decodes the signal of the user 1. However, the user 2 directly decodes its own information without the interference cancellation technology. Once any user fails in decoding, the D2D user feeds a Negative Acknowledgment (NACK) signal to the source device, the source device re-transmits the information until the two D2D users succeed in decoding or transmission number K reaches the maximum allowable transmission number;

[0009]

S2, expressing the spectrum efficiency as the outage probability function

2018102043 10 Dec 2018 [0010] The most important two evaluation performance metrics in the spectrum efficiency are the throughput 7 _and spatial spectrum efficiency Δ _s the former evaluates spectrum efficiency of one piece of information, the latter evaluates the spectrum efficiency of a whole network, the relationship between the two performance metrics is Δ—λη, χ j_s density of D2D users occupying the same time-frequency resource. It can be seen that the throughput is a critical performance metric for evaluating the spectrum efficiency. According to an update process theorem, the throughput 7 i_s expressed as

A (i-Ολα ^{7 1 +} Σ(ο«_λ+ο«_λ-ο.,_λ)’ [0011] meanings of each symbol in the equation are:

[0012] denotes information transmission rate of a D2D user ^z ;

[0013] denotes an outage probability of D2D user ^z after 7 HARQ rounds;

[0014] °i’^o2 denotes an outage probability of two D2D users after -th transmissions.

[0015] S3, decomposition of the outage probability [0016] In the above step, the spectrum efficiency is finally expressed as functions of a lot of outage probabilities, while the outage probability is a critical evaluation metric in performance analysis. Therefore, using a law of total probability, the outage probability ^κ·°^ι, ^K··⁰¹ and is expressed as

O

K,O.

2018102043 10 Dec 2018 κ K K

1=1 k=l 1=1 , °^._O2 = Σ^ρ ΙΑ,ιΑλ/Α, ]+^p [θ,ΑΑ ] ^ι=ι , [0017] [0018] [0019] rounds;

meanings of each symbol in the equation are:

P denotes occurrence probability of an event;

Θ s 7 ⁰¹⁴ J denotes an event that user 1 successfully decodes signal * after » HARQ [0020] κ

denotes a complement of the union ^Z=1 , that is, the user 1 fails to decode the signal [0021] ^S/ after K HARQ rounds;

Θ.

HARQ rounds;

[0022] °^2,fe denotes an event that user 2 succeeds in decoding its own message after κ

θ U®o₂,i ⁰¹ denotes a complement of the union ^k=i , that is, user 2 fails to recover its own message after K HARQ rounds.

[0023] [0024]

S4, accurately calculating the outage probability utilizing stochastic geometry ρΓω 0 θ Ί ρΓω a θ Ί

In order to derive the probability L L o₂,kj , p[e,₄,e„_u>®,]_; ρ[®,_4Λ,®,₄₄,®.] _and p[e„„e„₂,ej _{in step S2>} analysis is carried out from the perspective of information theorem and Shannon theorem. Further, distribution of interfering D2D users is accurately simulated via a two dimensional Homogeneous

2018102043 10 Dec 2018

Poisson Point Process (HPPP), and an expression of the outage probability is derived via theorem of the stochastic geometry:

’ /-1 k-l K-k k-l Λ

Σ Σ Σ Σ (->)§'' ci^ci^ x fj =0 τ₂ =0 τ₃ =0 τ₄ =0 ^Ψ[^υ“’^τ”^;(1-2«.^)¹ _<(</_!)’¹⁴ λ

r₄ + l -Ψ ϋ„,τ_Α;

)

-|+ ( n A

I „ . 2^-1

-«’Άλ ~ft. z,2\ z/ , \ Ά ⁺¹ k

(1_2^β^²)φ₂)

JJ p [©,.„©,. ₂,©^.,] - Σ Σ Σ(-')ΰ ci__tc_t'ci_, x ίϊ=0τ₂=0τ₃=0

2^ _j -1 (C „ _Β χ j 2^r* -1 ζ χ 2*²-1 ’^’^’(1_2V²)4<Z₂) χ

,τ₃ + 1 )

^Τ1⁼θ ^Τ2⁼θ ^Γ3⁼θ f ί

Ψ U₆,t_c;

Λ k

-Ψ U₆,T_rf;

k κ κ

ΕΣΣί-Ά'^εί'ρ

A (i-zVVW’J,

X

2^R1-1 ' 2^-1 Tl· -1

Ψ ?j=0 r₂=0

P[®„l._t.®„_U.®J =

ΣΣ £(-')«'' c?iC,x ij=0 τ₂=0 τ₃=0

7/ 2*2-1	r ί\ λ 2^-! 2^-1 z x
qi-2*>Js2)4</1)’ ( 2R1 -1 2 |((i-2V2)<(</2)’4A	Ri -i Ί MK) r2,ri) J

k = l ’*2 Γ<^τ4 k-l-V-'k ^K-k k>l [0025] meanings of each symbol in the equation are

2018102043 10 Dec 2018 = (W₄) τ_γ. =(η + l,r₂ + 1) τ_§=(η,Γ₂+2)

5 υ_Ω

U_c

2«2_i 2r*-1 2r' -1^	U6 =	2*2-l 2S1-1'
[(1-2^)44)^(4 )’fM J	[(i-2>/?2)44)’/?244)J

( (

2*² -1

2^/<2-1 ((1-2^)44)^) + 44)]

U,=

2*²-l 2^ft| -1 [0026] function Ψ(ϋ, τ, U, τ) (ut^t+Ut )-zI^(U,t;U,t) is defined as^ψ<^υ·^τ;^υ>^τ* ^{= ε} ' h_ereU (6^,---,6^,), τ (^,---,7^),

U (ϋ_1; ,U_M), τ (fj, ,τ_Μ} , φ(υ,τ;ϋ,τ) is expressed as a double integral du [0027] S5, performing outage probability approximate calculation on an assumption of short distance communication [0028] As mentioned in step S4, all probability calculation finally needs to calculate a corresponding τ,ϋ, τ) function, while the calculation process relates to a double integral with high calculation complexity, in order to reduce the calculation complexity and for the convenience of optimization design, it is very necessary to provide an approximate calculation method. In a consideration of that a distance D between two D2D users is very short and due to

2018102043 10 Dec 2018 the sake of cooperative communication, this assumption is very reasonable. Let 2) » 0, the double integral is approximately expressed as ^(U, τ; IT, τ) ¢9(11, r; 0,0) / p N+M _ = πΒ 1 —, y ?_r+i κυΰ f

OC k

² 2_i a

,=1

N-M y

fc K.

X7=l

N+M i=l.^n ’ Σ 1=1

N+M [0029]

Wherein (ΛΆ) Φ₁₅ , ^τ (^τ,^τ) (fi> ^_N+M) , defines a

Dirac function, (^a,^’^x) defines a fourth kind of Lauricella function, defines a

Beta function, if N + M — 1, the above approximation becomes an equation. The approximate result not only has low calculation complexity, but also has excellent approximate performance in value analysis.

[0030] S6, maximizing the spectrum efficiency, wherein while reliability of a service is ensured, the throughput is maximized via reasonably selecting information transmission rates R R, ¹ and N. _of the user, a mathematical expression of an optimized problem is maximize η subjectto O_{K 0} < ,z = 1,2 < β¹ < 2^/ύ’, [0031] meanings of each symbol in the equation are g

[0032] ⁱ denotes the maximal allowable outage probability for the D2D user ¹, [0033] denotes an outage probability of the user ^z after HARQ rounds;

2018102043 10 Dec 2018

Λ² [0034] r denotes a preset power allocation factor;

[0035] The above optimization problem may be decomposed using an interior-point algorithm. Further, in order to further optimize the distribution density of the D2D users, while the quality of the service is ensured, the spatial spectrum efficiency Δ is maximized, hence the 5 mathematical expression of the optimized problem is:

maximize Δ ,J?2 subjectto CQ₀ < ε_ι,i = 1,2

0<^²<2“*², λ >0, [0036] meanings of each symbol in the equation are [0037] ^λ denotes distribution density of interfering users, £ · [0038] ' denotes the maximal allowable outage probability for the D2D user ¹, [0039] denotes an outage probability of the user i after HARQ rounds;

Λ² [0040] denotes a preset power allocation factor.

[0041] S7, configuring a modulation mode, coding scheme and wireless resources

2? * R * [0042] The wireless resources are configured using transmission rates ¹ , ² and distribution density of the D2D users obtained by optimization. Specifically, a reasonable modulation mode and coding scheme are configured at the source device via the optimized transmission rates A and ^² , wireless resource allocation is directed via the optimal , and a spectrum reusability for the spectrum resources is configured.

2018102043 10 Dec 2018 [0043] Compared with the prior art, the present application has following merits and advantages:

[0044] Simulation and numerical results show that compared with the no-cooperative application scheme, the proposed cooperative application scheme decreases the outage probability by up to 23%. Further, the optimized LTAT of proposed scheme outperforms that of the OMA scheme by 17%. In the large-scale D2D network application, the present application provides a very meaningful application direction and reference value for the configuration of the D2D device modulation mode and coding scheme and resource configuration of the whole network.

BRIEF DESCRIPTION OF THE DRAWINGS [0045] Figure 1 is a schematic diagram illustrating an application model of a communication method in accordance with various embodiments of the present application; and [0046] Figure 2 is a flow chart illustrating a large-scale Device-to-Device (D2D) 15 communication method based on Hybrid Automatic Repeat Request (HARQ) assisted Non-Orthogonal Multiple Access (NOMA) in accordance with various embodiments of the present disclosure.

DETAILED DESCRIPTION

2018102043 10 Dec 2018 [0047] Embodiments of the present application will be described in detail hereinafter with reference to accompanying drawings and embodiments to make the objective, technical solutions and merits therein clearer. Apparently, the described embodiments are part of, rather than all of the present application. Based on the embodiments of the present application, all other 5 embodiments obtained by those skilled in the art of the present application without creative work should be covered by the protection scope of the present invention.

[0048] Embodiment [0049] NOMA has recently been conceived as an important technology for the next generation mobile communication. For example, a multi-user superposition transmission (MUST) 10 of NOMA has been proposed for 3rd Generation Partnership Project (3GPP) long-term evolution advanced (3GPP-LTE-A) downlink transmission. In such scenarios, some D2D users can act as relays to help the base station forward the messages so as to extend the coverage of wireless networks. Moreover, in order to alleviate severe interference from base stations, we assume that the D2D network operates in overlay mode, in which the dedicated spectrum resources are 15 utilized. In the D2D network, locations of all D2D devices follow a random distribution.

Particularly, the present application considers a D2D communication network, where the active D2D sources are modeled as a homogeneous Φ ^c (HPPP) with intensity . All D2D devices have backlogged buffers and are always transmitting over a shared frequency channel, which is dedicated to D2D communication. Without loss of generality, embodiments of the

2018102043 10 Dec 2018 present application focus on a typical source D2D device that is serving two nearby users via cooperative HARQ assisted NOMA scheme, as shown in Figure 1. It is assumed that only two D2D receiving UEs are based on the following consideration: limiting multiuser interference, reducing hardware cost and reducing processing delay. This assumption is also widely adopted in 5 research and actual application.

[0050] Let ^z be the location of the source device, then the distance between the source device and user ^z (the user at °‘) is denoted by ^O/H, where ^ze{k2} Exploiting the stationary of the PPP, we assume that user 1 is located at ^Ογ ~ (θ’ θ) and user 2 is located at °^{2 _}(D,0) This assumption does not affect the analysis result. Different from the traditional 10 TDMA, the core concept of NOMA is utilizing difference between fading channels. Therefore, without loss of generality, we stipulate that user 1 is closer to the source device than user 2, that is, di<d2. Note that HARQ can realize the reliable transmissions to combat the channel uncertainties or errors in channel measurement, the proposed cooperative HARQ assisted NOMA scheme does not necessarily need perfect knowledge of instantaneous CSIs at the source. It should be noted 15 that information decoding sequence of NOMA users is determined according to the average fading gains (path loss). Moreover, the average channel gains/path loss generally does not vary fast or dramatically in a short period compared to the small-scale fading. Therefore, frequent channel measurement and instantaneous SNR reporting is no longer necessary. Since the transmission distance determines the average fading gain/path loss, the two NOMA users are

2018102043 10 Dec 2018 essentially sorted according to the distance information between the NOMA users and the source device. For the convenience of description, the advanced solution may be divided into two phases in an application process, namely Phase I and Phase II. In Phase I, the source utilizes s s superposition coding with power domain multiplexing to encode the two signals ¹ and ² that are intended to the two users 1 and 2, respectively. Based on the received superposition message, the nearer user 1 first decodes the interfering signal ^§2 (since more transmit power is allocated £

to the signal of the user 2, therefore the SNR of the transmission of ² is much bigger, and s s probability for successfully decoding ² is much bigger). The signal ² of the user 2 is a kind £

of interference to the signal ¹ of the user 1, which is denoted hereafter as NOMA interference.

£ £

Once ² is successfully decoded, the nearer user can decode its intended signal ¹ by £

subtracting ² via SIC in the current and subsequent transmissions. Unlike the nearer user 1, the £ farther user 2 directly decodes ² while treating the NOMA interference si as noise. The transmission of the superposition messages is repeated until either user 1 or 2 acknowledges successful reception or the maximum number of retransmission K is reached. If either of the two devices acknowledges successful reception, Phase II starts in which the source node only transmits the remaining (i.e., not acknowledged) signal. Furthermore, if user 1 was the acknowledging receiver, it cooperates with the source device and relays s2 to user 2. When both users 1 and 2 acknowledge successful reception, the next two signals in the source queue are transmitted via the same aforementioned operation. If the maximum number of transmission K is

2018102043 10 Dec 2018 reached without decoding the intended signals, the signals are dropped from the queue and outage event is declared. For simplicity, we assume that the feedback channel is error-free and delay-free, which can be justified by the low transmission rate and the short length of acknowledgement message.

[0051] A. Signal transmission model [0052] In the present application, we assume a block Rayleigh fading channel (i.e., channel coefficient remains constant during each HARQ transmission) with known statistical CSI at the source device. However, the channel gain randomly and independently changes from one transmission to another. However, it is important to note that the locations of the interfering 10 devices do not change dramatically over the short HARQ time interval, especially for interferers with low-to-medium mobility. Thus it is reasonable to assume that the interferer locations are fixed during HARQ transmissions, i.e., follow Stationary Interferer Model (SIM), which is valid because of the limited maximal allowable number of transmissions for HARQ in practice, e.g., the maximal number of transmissions is usually chosen up to 5 and each HARQ round consumes 15 around 8ms. The received signal at each of the devices in each transmission phase can be represented as follows.

[0053] Phase I: The signal received by user i in the k-th HARQ round is written as y,·,* = + ^-^82) + Σ_ιεΦΧ{ζ} ^(ΙΙ^χ_°/ΙΙ)^Ρ^Αλ ^{+ n}>,*’ (1) [0054]

P denotes the transmit power, P denotes the power allocation coefficient. The

2018102043 10 Dec 2018

s. . § signal ¹ is intended for user ¹ and is Gaussian distributed with unit variance. ' is encoded and modulated independently first at the source device, multiplexed via the power domain and is ^=- . b transmitted with a fixed transmission rate L for user ¹, where ' is the number of

S' s information bits conveyed by signal ' . L defines the number of conveyed symbols, ^x’^k denotes a Gaussian signal with unit variance and delivered by an interfering device in the -th fi/r\ _'K/f^-0

HARQ round. Y ' represents the path loss, ^a denotes a path loss index, K denotes the path loss of a unit distance reference, the value of K depends on the carrier frequency and antenna characteristics, denotes the set of interfering devices, ^n,i denotes a complex additive white Gaussian noise (AWGN) vector with zero mean and variance matrix of ^0-2, that is ^η,Λ ON(0, cr²)^ d_enotes channel coefficient from the interfering device ^x to the user * in the k -th HARQ round, both and are complex Gaussian h h ~ (N (0 1) distributed with zero mean and unit variance, i.e.

[0055]

Following the NOMA protocol, after receiving the signal at both user 1 and user 2, no matter the user is the user 1 or user 2, the message intended for user 2 is decoded first with

SINR (2) [0056]

Where denotes the total interference at user ^z from a set of interfering

2018102043 10 Dec 2018 devices ® 44 ₅ it follows [0057] £

When the user 1 successfully decodes the message of user 2 ², the user 1 uses the

Successive Interference Cancellation (SIC) to recover its own message ¹ through subtracting the decoded signal s2 with SINR [0058] (4) £

Phase II: Following the proposed scheme, if ² is successfully decoded prior to the -th HARQ round, the signal received by the user 1 in the -th HARQ round is therefore given by [0059] y(⁷⁷) = [0060] (5)

The corresponding SINR can be expressed as (6)

Conversely, if ^S1 is successfully decoded prior to the ^-th HARQ round, the received signal at user 2 with cooperation from user 1 in the -th HARQ round is therefore given by

Ϊ2Λ = 74ⁿ)^P/W^S2 +-\l^{d₂'jPh_Zo_ikS₂ +Σ_χεφ\(_ζ| (| |^{X —} °2 11) ,k^&x,k +ⁿ2,k’ (7) [0061]

Where denotes the channel coefficient between two users in the k -th

2018102043 10 Dec 2018 transmission. Similar to (6), the received SINR of user 2 can be written as [0062]

Where

(8) _; , I W , ije(D)+£(d₂) denotes the equivalent channel coefficient in the ^-th transmission, and follows a complex Gaussian distribution with zero a : . £(D) + £(d₂) ., . . _{+ +}, .

mean and unit variance, i.e., ^e<i’^K , and ^{v 7 7} is the equivalent path loss.

[0063]

Based on the above signal transmission model, the analysis of spectrum efficiency (throughput and spatial spectrum efficiency) and outage probability may be specifically described hereinafter.

[0064]

B. Analysis of average throughput and outage probability [0065] LTAT is a widely adopted metric to characterize the performance of HARQ system.

For simplicity, let denote the number of slots and be the number of information bits, which are intended for user ¹ and successfully decoded by user ¹, up to slot ^t. The total LTAT is defined as tL (9) [0066] Where k ^{1 L} denotes the corresponding information bits per second per hertz successfully decoded by user ¹. The event that user ¹ stops the transmission of the current message is treated as a recurrent event. The recurrent event occurs with two random

2018102043 10 Dec 2018

R R rewards ⁰¹ and ^¾ gained by the two users, respectively. Thus by using renewal-reward theorem, the LTAT of the advanced solution is given by , ,^E(^RJ^+E(^RJ ^E<^T) ’ (10) [0067]

Where T is the random number of transmissions (inter-renewal time) between

R = R two consecutive occurrences of the recurrent event. Therefore, ^{Oi 7} bps/HZ if user ^z

R =0 successfully recovers its own message, otherwise bps/Hz, ε(λ,) = 0χΟ_Ιλ +Λ,(1-Ο_Ιλ) = Λ,(1-Ο,_λ), [0068]

Where denotes the outage probability of a D2D user ^z after k HARQ rounds. Moreover, T is a discrete random variable with the sample space {1’2»···,^} _anc[ obeys the probability distribution as p [τ =£] = <

C> , _Λ -O ic < K k = K’ (12) [0069]

Where ^°¹¹¾ denotes the probability of the outage event occurring at either user or user 2 after κ transmissions. By using inclusion-exclusion identity, it follows that

C) .. .. -C) +C) , -O, xr,Oi|o₂ ¹ ^k,o₂ ^κ,ο^^⁹ (13) [0070]

Where represents the probability that both two users fail to decode their e(t ) own messages after ^K HARQ rounds. As such, the average number of transmissions ' ’ is obtained by using (12) and (13) as

2018102043 10 Dec 2018 e(t )=Σ>ρ [τ = q=ι+Σ (o.„ +ο,_Λ ), r=l κ·=1 (14) [0071] [0072]

Accordingly, substituting (11) and (14) into (10) leads to i+LL(o«„+o«„-O„„J' (15)

Thus the LTAT is expressed as a function of outage probabilities, which are the fundamental performance metrics. It should be mentioned that the expression of the outage probabilities depend on the advanced solution. Hence, the cooperative HARQ assisted NOMA scheme determines the explicit expressions of the outage probabilities , θ^®² and .

To proceed with our analysis, they are individually derived as follows.

[0073] B.l The outage probability θ^£>°>

G [0074] According to the above system model, the decoding performance of ¹ depends on the number of HARQ rounds consumed by user 1 to successfully decode and subtract ^Sz as G well as the number of HARQ rounds consumed by user 2 to decode ². To facilitate our analysis, we define the following event.

Θ · s 7 [0075] °i’M denotes the event that user 1 successfully decodes signal ' after ¹

HARQ rounds;

κ [0076] °d denotes the complement of the union ^l=i , that is, the user 1 fails to g

decode the signal * after K HARQ rounds;

2018102043 10 Dec 2018 [0077]

Θ 7°^2,k denotes the event that user 2 succeeds in decoding its own message after ^k

HARQ rounds;

[0078] κ

θ U®O2.* °² denotes the complement of the union , that is, user 2 fails to recover its own message after K HARQ rounds.

[0079]

With the above definitions, the outage probability of user 1, i.e., θ^ ⁰¹, can be obtained by using a law of total probability as [0080]

Θ.

Κ,Ογ

X./=1 *=1 (16) © ,1 © ₀ (A ~

Notice that ^01A1, ..., and are mutually exclusive events. Similarly, ,

Θ (wk ί i Θ ^o2’^K and are also mutually exclusive events. In addition, if * > «, °i’²’¹ and i- S °²’^k are also exclusive events. Since the source device only sends ¹ after the acknowledgement of user 2, and hence, SIC is not required. Therefore, ®^K>°> can be simplified as

Κ,Ογ (17) [0081]

The terms at the right hand side of (17) will be derived one by one as follows:

[0082]

P Γ Ο ₉ O y Θ |

1) L °i’¹’ °^¹’ °2-*J _: From information-theoretical perspective, an outage event happens when the mutual information is less than the transmission rate. Herein,

2018102043 10 Dec 2018

represents the outage probability of user 1 after SIC given that decoding

S 7 S L· ² by user 1 consumed ¹ HARQ rounds and decoding ² by user 2 consumed ^K HARQ rounds. Note that / £ should be satisfied in this case. With the above signal model,

can be expressed as

[0083]

Where, = + denotes the mutual information given SINR .

Utilizing the stochastic geometry, (18) can be derived in closed-form :

[0084]

2¾ (1-2^r‘Z?²)€(<7₂)

Where,

2¾

7- +1 _ψ u τ ·______________ p’^T‘’(i-2V²)4U

U4 +1 (19)

2· -1

2¾ ]3 lfyl-2V)W/?Wi)’ £(dd J

τ. =(^+1¾.¾) _and t — (t t -η 1 τ 1 1—> 0 b v p 2 ’32 Herein, it should be mentioned that ^M , otherwise user 1 is unable to mitigate the NOMA interference ⁸³. In addition, the function of ^ψ(^υ’Τ,ϋ,τ) j_ef[_ne(j _as [0085]

Where, (ifyi^,...,//^), τ (η,...,Γ_Ύ), U —(^,...,(7^) , τ - (τ_γ,...,τ_Μ) _anj (20)

2018102043 10 Dec 2018 'l dii

J (21) ρΓθ θ θ 1 _e , [0086] 2) L ° ’¹’ ^{ο 2}’ Once user 2 succeeds in decoding ² after * HARQ

Oj ,2 ’ rounds, the source device will deliver only ¹ in subsequent retransmissions, which will be p Γθ _? Θ , Θ Ί straightforward decoded at user 2 without the use of SIC. Accordingly, L ^01,1 ’ °^1,2’ °^1,k -1 can be expressed as:

A i (A)< vA‘ (/%)<*=>

J=4+l 7=1

Al (A)<*4 (Cuhv

7=· [0087] With the same approach, (22) can be derived as:

p Γθ θ ^{r 2} ’

2^r' -1

2^fi2-l

2*² -1 ,r₃ + (22) ⁷ (23) [0088]

3) P [θοι,ΐ’θο,Λ/Ό^ ]. when jhg _user | successfully decodes ^S2 after ¹ HARQ rounds, it means that user 1 can fully eliminate the NOMA interference in the current and c

subsequent HARQ round utilized to decode ¹, which improves the outage probability. Therefore,

Θ

0,,2,/5

can be expressed as

(24)

2018102043 10 Dec 2018 [0089] With the same approach, (24) can be derived as

-| + [0090] [0091] ^=0^2=0^3=0

Ψ υ_Α,τ„;

_k k

(1-2¾ p²)t(d₂y^T\ „ . 2*²-l ~i’ ‘c’ k

-Ψ υ,,τ,;

k

2^-1

Where ^t==(5+U₂), ^=(^+1) _aM ^U‘ ⁼ (25)

2*¹ -1 >

c

JIJ p Γθ Θ Θ Ί

L i·¹’ »1,2’ o₂_|. After K transmissions, if user 1 fails to mitigate the

NOMA interference and user 2 fails to decode its own message, user 1 necessarily occurs the

outage, the outage probability can be written as
	K K	η
P[®,.l,®,.2.®,]=P	η1 («,2)<Α,η	(C,2)<a	•
	L./=i 7=1		(26)
p Γθ θ θ [0092] Therefore, L °>’2’	can be derived as
		( „	λ
ρ[θ,.„θ,.2,®^]=ΣΣ(-1)§’' QCJ'P Τγ =0 τ2 “θ	2R1 -1	-. 22-l ~
	(27)
10 [0093] B.2 The outage probability °κ,υ2
[0094] Similar to (17), the probability of outage event at user 2 can be obtained by using

law of total probability as

(28)

2018102043 10 Dec 2018 [0095]

Wherein the last step holds because of θοι-ΐΛΠθοι,ζ,ζ ® if k<l _anc[

the sequel.

[0096]

S 7 S

Suppose that user 1 successfully decodes ² after ¹ HARQ rounds and ¹ in the

-th HARQ round with SIC, where k>l Thereupon, user 1 and the source device cooperate to deliver the message to user 2 in the subsequent transmissions. In this case, the outage probability p Γθ Θ θ Ί of user 2 after & HARQ rounds, i.e., L °¹’^1Λ’ °²-l is obtained explicitly by considering the two cases of whether or not. Firstly, if , it means that user 1 successfully subtracts NOMA interference and decodes ¹ at the same HARQ round,

(29) [0097]

Therewith, using Stochastic Geometry, following may be obtained:

2018102043 10 Dec 2018 [0098]

P [®O! ,1,1 ’ ®oj ,2,1 ’®o₂ ]=ΣΣΣ(-ι) § ¹ P'l-lP'^P'K-l ^x zj=0 r₂=0 r₃=0 </

2¾

-,----------r------.max $ ((1-2^)4^) { 2^R1 — 1 2^R1 —1 [(1-2^)4^4/1)+4^ λ

(1-2^^(4)^(4)^ 2¾ !

2^-1 2*¹-!

Ki,¹);

(30)

On the other hand, if £ > /, that is, the events of the successful message decoding and NOMA interference cancellation at user 1 occur in two different HARQ rounds,

can be expressed as

Ρ[θ_ΟΪ,ΐΛ’®ο₁ΛΖ’®<_>2] ^{= Ρ} ήι fs,2)<-^r _!. n¹ (^)<^.h’ (c.2 )<*>.

7=1 7=4+1 7=1 i i.chf· (.<’,,)<-«,·¹ λ . j=^l (31) [0099] ρΓ© Θ © 1

Therefore, L °^1,1Λ’ ^01,2,1 ’ °²-l can be expressed as:

-1+ ^P ΙΧ,ιλΑλ/’®^ ’*2 k-l-V'-'k ^K-k ,k>l, (32) [00100] Where U = (η+l,r₂+1)

U ^=(^1^2+2), ^c

i 2R2-1 2Rz-1	U =	' 2R2 _! 2-¾ _i
^1-2^ fi2t(d2 Y£(D)+t(d2) J	d	[(1-2^)4,/,)^4,/,))

[00101] B.3 The outage probability °^km [00102] Analogous to (17) and (28), it follows by using law of total probability θ^χ>°ι>^ο2 that (33)

2018102043 10 Dec 2018 [00103]

		( K	λ
°κ,Οι,ο2 =ρ[Θ0|ιι,Θ02] = ρ		LA	,1	l 1® .,0 / ¢7] ,2 ’ <?2
		w=t	7

ζ=ι

Where

have been given by ( 25 ) and (27) respectively. Therefore, the outage probabilities ^κ’^υ> , ^K’°² and can be calculated by using (17) , (28) and (33) . Substituting them into (15) yields the LTAT of the proposed scheme. In order to evaluate the outage probabilities, it essentially resorts to the calculation of the double integral of j_n (21). Unfortunately, the double integral representation of (21) entails a high computational complexity on the performance evaluation.

Therefore, it is necessary to provide an algorithm with low complexity. Since it is usually expected that NOMA users are not far away from each other due to exploitation of cooperative communications, the calculation of ’ ^τ’^’^τ> may be simplified via following theorem.

[00104] Theorem 1: In a condition of short distance τ,U,τ) _can approximately expressed as k-=1 [00105] (a;b;x)

N-M

N-M y-L=l,i^u ^? Z-i t=l (34)

U (U,U) (U^ ?U_N+M) > τ (τ,τ) (ή, > <$_s j_enot_es Dirac function,

B f όζ b\ denotes the fourth kind of Lauricella function, ' ’ ⁷ defines the Beta function.

2018102043 10 Dec 2018

If N+M-l, _ab_Ove approximation would become an equation. The above approximate result not only has low computation complexity, but also has excellent approximation performance in value analysis.

[00106] According to theorem analysis of throughout and outage probability, how to perform optimal design of the application solution using these results may be analyzed hereinafter to effectively improve the throughput of the system or utilization of the space spectrum.

[00107] C. Spectrum efficiency optimization [00108] Two key performance metrics are used to evaluate the spectrum efficiency, i.e., throughput and spatial spectrum efficiency Δ. The former evaluates the spectrum efficiency of transmission of one piece of information, while the latter evaluates the spectrum efficiency of the whole network, the relationship of the two performance metrics is Δ-Λ-7 where, is the distribution density of D2D users occupying the same time-frequency resource.

[00109] C. 1 Maximization of LTAT [00110] The increase of the maximal number of HARQ transmissions may decrease the

LTAT. In order to combat the negative impact of co-channel interference and fully exploit the benefit of cooperative HARQ, an interference aware optimal design is proposed herein. Particularly, the LTAT is maximized through properly choosing system parameters while maintaining the quality of service. By taking the optimal rate selection as an example, the LTAT is maximized by optimally selecting transmission rates given the predetermined power allocation coefficient^ , while guaranteeing outage constraints and the implementation of NOMA protocol. Mathematically, the optimization problem can be formulated as maximize η ^R\>^R2 subjectto O_{K 0} < ,i = 1,2

g .

[00111] Where ' denotes the maximal allowable outage probability for user ¹. It is worth highlighting that (35) can not be solved in closed-form due to the complicated expressions of the outage probabilities and the non-convexity of the problem. Fortunately, interior-point algorithm can be exploited to numerically solve it with sub-optimal solution.

[00112] C.2 Maximization of ASE [00113] Aside from the LTAT, the Area Spectral Efficiency (ASE) is another useful metric to characterize the performance of the whole D2D network. Specifically, the ASE of the D2D network is given by ^{Δ = λ}ν· (36) [00114] Inspired by (35), the spatial spectrum efficiency Δ may be maximized while the quality of the service is ensured to further optimize the distribution density of the D2D users, hence the mathematical expression of the optimized problem is:

maximize Δ subj ectto O_{K o} < ,i = 1,2

0</?²<2”\ (37)

2018102043 10 Dec 2018 [00115] Similarly to (35), (37) can also be effectively solved with interior-point algorithm. [00116] To sum up, since the spectrum resources are limited, the large-scale D2D application results in excessive frequency reuse, which causes severe superimposed interference to the mobile terminal occupying the same time-frequency resource. Severe interference may cause a dramatic deterioration in the performance of communication system, such as degradation of spectrum efficiency and increase of the outage probability. In order to improve the spectrum efficiency while ensuring reliable transmission, embodiments of the present disclosure provide an application scheme of NOMA with high joint spectrum efficiency and co-operative HARQ for ensuring transmission reliability in the large-scale D2D network [00117] The foregoing is only preferred examples of the present disclosure, which is not used for limiting the protection scope of the present disclosure. Any modifications, decoration, equivalent substitutions, combination and simplification made within the spirit and principle of the present disclosure, should be covered by the protection scope of the present disclosure.

Claims (5)

What is claimed is:
1. ,(1-2·/?^!)ί(4)7(Ο) + «(4)

   [(1-2^)44)

   ^^(1-2^)/(½)

   7ζ

   (1-2*·^)7(</,) J

   1=1 k=l 1=1 , °xa._O2 = Σ^ρ ΙΑ,ιΑα/Α, ]+^p [θ,ΑΑ ] ^ι=ι , meanings of each symbol in the equation are:

   P denotes occurrence probability of an event;

   Θ s 7 denotes an event that user 1 successfully decodes signal ' after ^z HARQ rounds;

   κ

   0 . U®<V,Z ⁰¹⁷ denotes a complement of the union ^Z=1 , that is, the user 1 fails to decode the g

   signal ‘ after & HARQ rounds;

   2018102043 10 Dec 2018

   Θ 1°²’^k denotes an event that user 2 succeeds in decoding its own message after ^k HARQ rounds;

   κ θ υ®ο₂Λ °² denotes a complement of the union ^=¹ , that is, user 2 fails to recover its own message after K HARQ rounds;

   5 S4, accurately calculating the outage probability utilizing stochastic geometry, accurately simulating distribution of interfering D2D users via a two dimensional Homogeneous Poisson

   Point Process (HPPP), and deriving an expression of the outage probability via theorem of the stochastic geometry, /-1 k-l K-k k-lΛ £ Σ Σ Σ (->)§''χ

   71 =0 7₂ =0 7₃ =0 7₄ =0

   Ψ υ,,τ · ~α>

   k λ

   / r ,\ ζ χ>^Γ4 ^{+ 1} “^ψ υ„,τ_Α;

   1. A large-scale Device-to-Device (D2D) communication method based on Hybrid Automatic Repeat Request (HARQ) assisted Non-Orthogonal Multiple Access (NOMA), comprising:

   5 SI, designing a HARQ assisted NOMA application scheme, wherein a source device firstly s s generates codes for a signal ¹ and a signal ² via forward error correction coding which need to be transmitted to two Device-to-Device users according to the HARQ, a signal β\ + λ/Ϊ ^~^s2 i_s transmitted to the D2D users adopting the NOMA supporting multi-users simultaneous transmission, P is a power allocation factor; the D2D users respectively decode 10 signal, if decoding of any D2D user fails, the D2D user feeds a Negative ACKnowledgment (NACK) signal to the source device, the source device re-transmits the information until the two

   D2D users succeed in decoding or transmission number K reaches the maximum allowable transmission number;

   S2, expressing throughput 7 and spatial spectrum efficiency Δ as an outage probability

   15 function, wherein the throughput evaluates spectrum efficiency of one piece of information, the spatial spectrum efficiency evaluates the spectrum efficiency of a whole network, is distribution density of D2D users occupying the same time-frequency resource, according to an update process theorem, the throughput 7 j_s expressed as

   2018102043 10 Dec 2018 ⁷’ι+Σ«(ο«_Λ+θ^-θ._ΛΛ)’ meanings of each symbol in the equation are:

   denotes information transmission rate of a D2D user ^z;

   denotes an outage probability of D2D user ^z after k HARQ rounds;

   θ^_!θ1,_θ2 d_enot_es an outage probability of two D2D users after * -th transmissions;

   S3, decomposing the outage probability, using a law of total probability, the outage probability κ,_Ο1 , θχ,_{θ2 an}d θχ,οι,»₂ i_s expressed as

   K,_Ol ®Κ,₀₁

   K K K =ΣΣ^ρ[®^,.Α.«Α,]+Σ^ρ[®νΑ.2.ΥΕ^ρ[®^Α.!·Α]
2. 2. The method according to claim 1, wherein in the step SI, in the application scheme of designing the HARQ assisted NOMA, a decoding sequence is determined according to path loss

   15 of the two D2D users, a path loss model is expressed as , K= denotes a reference path loss value with a distance of 1 meter, ^a is a path loss metric and d is the distance.

   2018102043 10 Dec 2018

   2? * R * wireless resources are configured using transmission rates ¹ , ² and distribution density of the D2D user obtained by optimization.

   2*² -1 ((12^R' -1

   Ji-2‘//²)<(4)’Z?7«) function ^(^ί,τ,υ,τ) j_{s 3e}Q_{ne4 38}Ψ(υ,τ;υ,τ)-ο τ = (^,---,^), υ = (ΰ,·.·ΰ_Μ)_; τ = (ή,---,^), ^(υ,^υ,τ) ¢7(11, τ:1,τ) |\ 1-J]

   Η=1 υ = (ί/„··Λ) is expressed as a double integral du

   S5, performing outage probability approximate calculation on an assumption of short

   2018102043 10 Dec 2018 distance communication, assuming T) « 0 j_{n a} consideration of that a distance D between two

   D2D users is very short and due to the sake of cooperative communication, the double integral

   Αϋ,τ;ϋ,τ) j_{s a}pp_roxi_mately expressed as y?(U, t; U, t) «<p(U, τ; 0,0) ( 2 N+M \ 2_ = *B 1--,£f,+l Κ.°ΰ_μ ί=1

   2___γ N-M ^a y T U

   I / J K fC jt=l

   N+M

   N+M -?=1 wherein^{10 11} Ολ^υ) (ΰρ· ·,ϋΝ_Μ), ^τ (^τ,^τ) ' ,?ν+μ), β defmes a Dirac function, v^a’^’^x) defines a fourth kind of Lauricella function, defines a Beta function, if N + M = 1, ^e above approximation becomes an equation;

   S6, maximizing the spectrum efficiency, wherein while reliability of a service is ensured, the throughput is maximized via reasonably selecting information transmission rates ¹ and

   10 of the user, a mathematical expression of an optimized problem is maximize η

   R_x ,R₂ subjectto O_{K o} < ε_ί,i = 1,2

   0 < β¹ < 2~^R1, meanings of each symbol in the equation are ‘ denotes the maximal allowable outage probability for the D2D user ^z, denotes an outage probability of the user ^z after k HARQ rounds;

   denotes a preset power allocation factor;

   2018102043 10 Dec 2018 wherein while the quality of the service is ensured, the spatial spectrum efficiency Δ is maximized via optimizing distribution density of the D2D users, hence the mathematical expression of the optimized problem is:

   maximize Δ ,J?2 subjectto O_{K o} < ,i = 1,2

   0<^²<2“*², λ >0,

   5 meanings of each symbol in the equation are

   2^ -1

   2*²-1

   U,=

   U₆ =

   2*²-1 ^λ \\ meanings of each symbol in the equation are:

   τ_ζ. = (η +1,γ₂ +1) T_g=(zj,r₂+2)

   9 9

   U_a =

   U_c = >(V);

   k>l

   U=(w₂ ⁺¹) ₂λ₂_ι 2^λ>-1 2^Λ|-Ρ

   Jl-2«²., ί

   2·-1 (ι-2’·/?^!)<(4)7(^β)+44),

   Μ k-l-\ k K-k Λ

   Σ Σ Σ Σ ί-¹)»'' c^c^c-’ci, ^=0 r₂-0 r₃=0r₄=0 χ(ψ(υ„τ_γ;υ₂,τ,)-ψ(υ„τ₈;υ₂,τ,)) (1-2^7(4)^7(4)(,

   2*²-1 2*¹-I

   -,-----------r-------, max <

   2*² -1

   2*²-1 2^ -1

   2018102043 10 Dec 2018

   2*²-l (1-2’· R²)e(d₂)’^T\

   K K

   P [0,.,,0,.,,©J = £ £ (-1) QQT

   71=0 7₂=0

   2¾

   K-k k-l ,τ₃+1

   ΣΣΣ(-^'ΜΛχ

   7_t=0 ^Γ2⁼θ ^Γ3⁼θ ( (

   Ψ U₆,_Trf;

   k

   2^-1 ___________ %(</,)’(1-2«·/?)/(</,)J

   2^-1 ,τ₄ + 1

   -|+

   JJ\

   Ρ [©,.,,©,.„©..,]=£ £ Σ(-ι)ξ^Γ' χ

   7ι=0 7₂=07₃=0 λ

   2¾
3. 3. The method according to claim 1, wherein the step S6, in the maximization of the spectrum efficiency, the optimized problem is optimized and decomposed using an interior-point

   R* R * i* algorithm to obtain the transmission rates ¹ and ² , and distribution density of the

   D2D user.
4. 4- denotes distribution density of interfering users, ε ’ ‘ denotes the maximal allowable outage probability for the D2D user ¹, ^^K’°> denotes an outage probability of the user ^z after HARQ rounds;

   a^{2 H} denotes a preset power allocation factor;

   10 S7, configuring a modulation mode, coding scheme and wireless resources, wherein the
5. 5 4. The method according to claim 1, wherein in the step S7, wherein a process for configuring the modulation mode, coding scheme and wireless resources comprises: configuring a reasonable modulation mode, coding scheme at the source device via the optimized

   R* R * « * transmission rates ¹ and ² , directing wireless resource allocation via the optimal ^ζ , and configuring a spectrum reusability for the spectrum resources.