Ijctt v7p146

International Journal of Computer Trends and Technology (IJCTT) – volume 7 number 3– Jan 2014

Energy Based Optimal Relaying in Heterogeneous Radio Access Networks Ravi Gunaseelan¹, V.Bharathi², R. Sambath kumar³ 1,3

2

PG Scholars, Assistant Professor, Sri Manakula Vinayagar Engineering College, Puducherry.

ABSTRACT: Due to recent trends in mobile communication system, much attention has be given to heterogeneous networks in which a mobile equipment is able to access multiple networks that are present in a locality. Here each random access networks (RANs) operates at different carrier frequency having different transmission bandwidth whose selection is based on the Quality Of Service (QOS) of each network. In this paper, we examine the efficient use of multiple radio access technologies (RATs) in cooperative network. By taking into account the circuit power consumption of each relay nodes, an optimal relaying scheme is introduced which outclasses the direct communication as well as the traditional best select relaying schemes producing effective packet transfer with reduced packet loss and increased throughput.

and power usage by the components present in the system.

An energy efficient cooperate relaying was studied in [7] and a best selected switching technique using a single RAT was proposed. While considering a realistic battery model in [8], an energy efficient relay selection using multiple relay nodes and power allocation strategies for each node was studied. In this work, we gathered information how a best selected energy efficient relaying is carried out in cooperative heterogeneous radio access network which contains relay nodes that is capable of using multiple RATs. We take into account the optimal relaying and RAT selection problem so as to maximize the energy efficiency considering the adaptive modulation schemes to further improve the efficiency.

II. Keywords: RANs-random access networks, QOSquality of service, RATs-radio access technologies, RM-radio mode, PL-path loss

I.

INTRODUCTION

In current day system, various radio access technologies (RATs) like WLAN, WCDMA and LTE are accessible by a single mobile device which is called as multi-radio access (MRA) system [1][2]. Using this system a mobile device is able to communicate through ant of the RATs that coexist in a network. Resource allocation for a MRA system was studied using various RATs simultaneously to manage the spectral efficiency [3]-[4]. Instead of considering various RATs at the same time [5], a RAT is taken to increase the network capacity based on the QOS constraints.

The energy consumed for the circuit operation is not considered in previous works while considering the energy consumption during network operation was given greater importance. Various works are been conducted [6] in designing an energy efficient wireless communication system which includes consideration of system-wide energy consumption.

The circuits are well designed to reduce the size

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DESIGN MODEL

A heterogeneous cooperative radio access network is illustrated in Fig.1 which contains source, relay and destination node which is equipped with multiple radio modes (RMs) that uses different RATs. Her we assume that each RM operates at different carrier frequency and using a different transmission bandwidth. A best-select relaying schemes is considered where a single best relay is selected among the various available relay nodes which is selected to forward a message from source to destination in decode and forward method.

Consider a relay i which uses RM j with a nominal transmit power

, is given by

(i, j) =

˜(i, j)

(1)

Where, ˜ (i, j) = H(i, j) / PN( j). (j) = B( j) is the noise power in RM j, noise power spectral density is denoted by and B( j) is the bandwidth of RM j. The channel power gain from the source to relay i using RM j is denoted by H(i, j).

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International Journal of Computer Trends and Technology (IJCTT) – volume 7 number 3– Jan 2014

Fig.1. Cooperative networks with multi-radio equipped relay nodes A path loss component is considered which takes into account the distance between the two nodes and the channel gain given by, PL(d) =

(

)+10β

(2)

where (

) = −10

(3)

where is the reference distance, is the wavelength ( = c / f, where c is the speed of light and f is the carrier frequency) and β is the path-loss exponent. Since each radio modes use different carrier frequency, different values of ( ) will be obtained. For the RM j, the decoded set gives a set of relay nodes which will correctly decode the original message from the source in RM j, the decoded set is given by, = {i| ˜(i, j) ≥ ( )} (4) where denotes the maximum transmit power of a relay and ( ) is the required SNR that meets the target bit error probability, , with bits/symbol; [9]for M-QAM, the required SNR is given by (5) (6) where c1 = 0.2 and c2 = 1.5.

The channel gain for each RM k for the link between relay to destination (RD) is estimated by G(i,k) and based on this a best relay node is selected. This selected relay is used to forward the message from source to destination.

III.

=

+α

(7)

Where the reference circuit power consumption of equipment’s is , is a reference bandwidth, and α is a proportionality constant (in mW). The RF chain power consumption, The power consumption for the RF chain, PRF is considered to be a constant. Thus, the total power consumption by the circuit is given by = + + + (8) Superscripts “tx” and “rx” denotes the transmitter and the receiver section. The basic RF chain power consumption by the transmitter and receiver end is modelled as = +2 + + and = +3 + + + [26] where, , , , , , are the power consumption for the D/A and A/D converters, filter, local oscillator, mixer, and low noise amplifier, respectively.

IV.

BEST RELAYING METHOD

In this section, the best select relaying energy efficiency with multi-radio nodes is derived. By using relay i having RM j for link between source and relay (SR) link and RM k for the RD link for transmission of L bits. The energy efficiency (in bits/Joule) is given by,

(9)

CIRCUIT DESIGN MODEL

The total power consumption is divided into two parts: power consumed by the power amplifier (PA) and the power consumed by the remaining part of the circuitry amplifier power consumption is given by /ρ whose efficiency is denoted by ρ.

We consider mostly the circuit power consumption because the power consumed by the amplifier

ISSN: 2231-2803

cannot be much controlled due to its variation with distance between relay. The circuit power consumption can be divided into power consumed by the circuit components and the power consumed by the RF chain which excludes the power consumption by the PA. The circuit power consumption model is based on bandwidth utilisation, as the bandwidth increases more base band processing is required i.e., more signal processing and use of memory for processing. The power consumed by the circuit component , is designed as,

Where and represents the required transmit power for link between source and relay which uses RM j and for the link between relay and destination which uses RM k, respectively.

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International Journal of Computer Trends and Technology (IJCTT) – volume 7 number 3– Jan 2014

and represents the required transmission time for each link. The total circuit power consumption for the SR link and the RD link transmissions are (j) and (k), respectively. Dividing by (k) and factoring out B(k),

VI.

ADAPTIVE TECHNIQUE

MODULATION

In order to improve energy efficiency in an effective way we use adaptive modulation technique which uses joint analysis of the modulation size of the relay and RM selection.

Here the end-to-end delay constraint, Tmax is considered to be maximum. Then, the optimization problem becomes

(10)

V.

RADIO MODE SELECTION USING BEST RELAYING

The constellation size of both the source to relay and relay to destination link are considered to be same, = = b. The energy efficiency can then be simplified as (11) where

and .

Here (i, j) and (i,k) are the required transmission energies and the circuit energy consumption. Then, for a fixed constellation size b with a given relay i, the maximum value of (11) is equivalent to the minimum value of the total consumption for each link, (i, j) and (i,k), separately. Then, the suitable RM for the SR link is (12) Where the “decoded radio mode set” of relay i is , which is the set of radio modes for which relay i which correctly decodes the source message and is given by, Si = { j| γ˜(i, j) ≥ (b)} (13) For the link between relay and destination, the optimization problem with the presence of maximum power constraint is (14) Such that

Then, the optimal relay which minimizes the total energy consumption for a given optimal pair of RMs i∗= argmin( (i, j∗)+ (i,k∗)) (15)

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(16) Where,

1. Fixed Constellation size For fixed RMs j and k of relay i, the suitable constellation sizes b∗SR and b∗RD is obtained by numerical search. In this case, first the bSR is made fixed and then the corresponding optimal b∗RD is found. Then, all values of bSR is searched which satisfy the constraints to find the suitable constellation size for both links. Thus, (16) is equivalent to (17) s.t.

where are the maximum constellation sizes are given by bSR max and bRDmax that satisfy the target bit error probability for a given channel gain.

here the minimum constellation size for the RD link is bRDmin to meet the delay constraint for a given bSR.

where which guarantees that the SR link transmission time is less than Tmax, and bmin2 is the minimum bSR such that .

2. Variable constellation size Here we consider three cases.

2.1 case 1: The constellation size of each link is processed independently in this case. In order to get the optimal b∗ SR,

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(18)

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International Journal of Computer Trends and Technology (IJCTT) – volume 7 number 3– Jan 2014

where . Then, the best constraints is given using (18) as,

(19) where bmin = bmin1, bmax = bSRmax, and ˜b = ˜bSR. Similarly, ˜bRD is the solution of the unconstrained optimization problem for a given b∗SR as (20) where 2.2 case 2: Here we restrict the constellation sizes of both links to be equal, i.e., bSR = bRD = b. Then, the suitable solution, b∗, has a form similar to (19),

These results can be easily extended for cases where the power consumptions at the transmitter and the receiver are different. RM 1 is assumed to be the reference system in the simulation.

In Fig. 2, the energy efficiency (EE) of best-select (BS) relaying with a fixed 2 bits/symbol for both links. A normalized destination distance is used where the reference distance d0 = 1 meter.

Optimal-BS denotes the optimal Best Select scheme and Conventional BS as the conventional Best Select which ignores the circuit power consumption (PC = 0) and only considers the channel gain and transmission power amplify. The energy efficiency of sub optimal best-select relaying scheme(BS Sub3 2bit) is compared with other methodology for transmission using 2bits/symbol.

Also, the EE of direct communications with RM adaptation (Direct Communication) is plotted.

and bmin = L/BTmax.

.

2.3 case 3: In this scheme, for a fixed modulation size, the suitable relay and RMs are obtained, and the optimal constellation size for each link is found by numerical search.

VII.

RESULT

The parameters used in the simulation are given in Table 1. It is assumed that there are M =5 relay nodes located equidistant from the source and the destination nodes. The proportionality constant, α = 20 mW, has been deduced from [10] where the baseband power consumption is projected for current and future wireless communication systems. Let Ptx RF≈ PrxRF = PRF and PtxBB≈ PrxBB = PBB. Table 1 System Parameters 35% Amplifier efficiency, ρ Path-loss exponent, β

3.5

Maximum power constraint,

20 dBm

Noise power spectral density,

-174 dBm/Hz

Target bit error probability, Proportionality constant,

20mW

Carrier frequency of RM-1/RM-2/RM-3, f (GHz) Bandwidth of RM-1/RM-2/RM-3, B (GHz)

3.0/3.5/6.0

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3.0/7.0/10.0

Fig.2 Energy Distance

Efficiency

Vs

Normalized

Fig 2 shows the EE of BS and DC with adaptive modulation for μ = 0.5. The figure shows that adaptive modulation significantly improves the EE compared with a fixed constellation size.

Interestingly, it can be seen that BS-Sub3 with 2 bits/symbol performs better than that Conventional Best select. The reason is as follows: For a fixed constellation size, the RM having the largest bandwidth is selected to minimize the circuit power consumption. Thus, with 2 bits/symbol, RM 3, supporting a 10-MHz bandwidth, is likely to be selected for short distances. However, the selected link with the larger bandwidth and path loss leads to a smaller maximum constellation size, which limits the degrees of freedom for adaptive modulation compared to that of the selected link with 4 bits/symbol. For large distances, using a larger constellation size for the selection increases the outage probability, degrading the energy efficiency. In general, BS-O benefits from

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International Journal of Computer Trends and Technology (IJCTT) – volume 7 number 3– Jan 2014 recognizing the different circuit power consumption characteristics of different radio modes and taking them into account during relay and radio mode selection. Thus, for a fixed circuit power consumption for different radio modes, increasing the number of relay nodes or the maximum power constraint improves the energy efficiency of both schemes, typically for large distances. However, it does not change the relative performance between them. The performance of BS-O only converges to that of BSC when Pre f >>α BBre f or α ≈ 0, for which the circuit power consumption difference between RMs is negligible.

Fig 3

Probability of selected radio modes of optimal best-select relaying with direct communication

through direct communication and best select optimal scheme.

Fig. 5 Comparison of packet loss for various optimal schemes Fig 5 shows a comparison between the amount of packet that is lost during the transmission of data at 4bits/symbol through various optimal schemes. The amount of packets that is lost through direct communication is greater than the optimal and sub optimal schemes. The loss of packet through the sub optimal best select scheme is much less when compared to that of direct communication optima scheme and that of optimal best select scheme.

VIII.

Fig.3, shows the corresponding probability of the RM that is selected for transmission for BSO. For short distances, even for larger noise power and with path loss, the RM having the higher bandwidth is selected to reduce the circuit power consumption. However, as the distance increases, the optimal scheme is likely to choose the RM supporting a lower bandwidth, operating on a lower frequency, to meet the target SNR.

Fig. 4 Comparison of throughput for various optimal schemes Fig 4, shows a comparison between the amount of throughput that can be obtained through various radio modes of transmission. The throughput obtained through the Sub optimal Best select scheme is greater than those obtained

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CONCLUSION

Optimal best select method benefits from recognizing the different circuit power consumption characteristics of different radio modes and taking them into account during relay and radio mode selection. Thus, for a fixed circuit power consumption of different radio modes, increasing the number of relay nodes or the maximum power constraint improves the energy efficiency typically for large distances. Optimal relay and radio mode selection in heterogeneous cooperative radio access networks was considered, and demonstrated that it is critical to take the circuit power consumption into account in the selection algorithm design to improve the energy efficiency. The throughput is achievable at greater rate in the proposed sub optimal scheme when compared to optimal scheme and direct communication. The loss of packets during transmission is also reducible through the proposed sub optimal scheme. It is found that the energy efficiency can be further improved by employing adaptive modulation. The proposed several suboptimal schemes showed that performance close to the optimum is achievable.

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International Journal of Computer Trends and Technology (IJCTT) – volume 7 number 3– Jan 2014

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