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# Energy-efficient resource allocation for OFDMA two-way relay networks with imperfect CSI

- Zheng Chang
^{1}, - Qianqian Zhang
^{2}, - Xijuan Guo
^{2}Email author and - Tapani Ristaniemi
^{1}

**2015**:225

https://doi.org/10.1186/s13638-015-0455-6

© Chang et al. 2015

**Received:**18 November 2014**Accepted:**23 September 2015**Published:**9 October 2015

## Abstract

Most of the existed works on the radio resource allocation (RRA) problem commonly assume the channel-state information (CSI) can be perfectly obtained by the transmission source. However, such assumption is not practical in the realistic wireless systems. In this work, we consider the practical implementation issues of resource allocation in orthogonal frequency division multiple access (OFDMA) two-way relay networks: the inaccuracy of channel-state information (CSI) available to the source. Instead, only the estimated channel status is known by the source. In this context, a joint optimization of subcarrier pairing and allocation, relay selection, and transmit power allocation is formulated in OFDMA two-way amplify-and-forward relay networks. Moreover, the objective of this work is to minimize the energy consumption of the overall system. Further, to ensure the quality of service (QoS) or data rate requirement, the energy consumption must be minimized without compromising the QoS. Therefore, by applying convex optimization techniques, energy-efficient algorithms are developed with the objective to minimize the total transmit power with guaranteeing the required data rates. Through simulation studies, energy consumption performance of the systems under the proposed schemes is investigated. It can be observed that our proposed scheme can improve the energy consumption performance of the considered system.

## Keywords

- OFDMA
- Two-way relay
- Subcarrier pairing
- Radio resource allocation
- Imperfect channel-state information
- Energy efficiency

## 1 Introduction

The demand for high-speed data transmission has been significantly increased due to the fast-growing wireless multimedia service market in the last decade. Orthogonal frequency division multiple access (OFDMA) is known as an effective technique exploiting the features of OFDM in combating channel fading and multipath effects and providing high data rate. Meanwhile, relay-assisted communication is regarded as a promising technology, as it obtains better and reliable system performance in terms of spectrum and energy efficiency [1, 2]. Therefore, OFDMA wireless network with cooperative relays is foreseen as a promising structure for providing high-speed data transmission and reaching many desirable objectives in the context of future wireless networks development.

In addition, there has been increasing attention paid for studying the two-way (bidirectional) relay networks (TWRN), where two data nodes exchange information via several assisting relay nodes (RNs). Comparing with the traditional one-way relay schemes that need four time slots to finish information exchange, the TWRN only requires two time slots [3]. In the first time slot, two TWRN users can transmit their signals simultaneously to the available RNs. Then, in the second time slot, with the assumption of perfect synchronization, RNs broadcast the processed version of the received signal to the two users to complete information exchange. Processing of signal at RN relies on different processing functions, such as amplify-and-forward (AF), decode-and-forward (DF), etc., among which AF is most likely to be realized and most widely used in practical system. Therefore, in the paper, we focus on the OFDMA wireless networks with AF two-way relays.

Nevertheless, in order to fully realize the aforementioned benefits, OFDMA TWRN calls for a cautious radio resource allocation (RRA) design comparing with traditional network infrastructure, as there are many different radio resources, such as relays, subcarriers, and transmit power. This involves a careful design and coordination of the power and subcarrier allocation, selection of relay(s) across different hops. Most of the related works on the RRA for TWRN assume the channel-state information (CSI) is perfectly known to the nodes in the system [3–5]. However, in reality, the CSI cannot be perfectly obtained. Instead, the transmission source only knows partial/imperfect CSI. Therefore, the development of practical resource allocation schemes requires consideration of the inaccuracy of CSI. The RRA schemes with imperfect CSI has received much attention when considering the one-way relay dual-hop wireless networks. In [6], authors considered the RRA algorithm for conventional OFDMA networks without relays. The authors of [7] focused on the relay selection scheme for TWRN with imperfect CSI. In addition, the author also presented a power allocation scheme that minimizes the outage probability. Some recent work in this line, e.g., [8] and [9], investigated the issue of joint RRA and relay selection with imperfect CSI, where throughput maximization is the optimization objective. Under the consideration of channel uncertainty, the relay selection and power allocation schemes are proposed to minimize the uplink transmit power of the network by taking each user’s target data rate as the quality of service (QoS) constraint in [10]. Another recent work about RRA for OFDMA relay networks with imperfect CSI was introduced in [11], where only power allocation algorithm was introduced. In [12], resource allocation scheme was presented for the selected relays. Meanwhile, only limited research work, e.g. [13] and [14], focused on the RRA for TWRN with imperfect CSI. In [13], authors analyzed the outage performance of TWRN with imperfect CSI and proposed a power allocation scheme. Similarly, authors of [14] also proposed power allocation and user selection scheme for TWRN with outdated CSI. Similarly, the authors of [15] also proposed power allocation and user selection scheme for TWRN with outdated CSI.

- 1.
We present an energy-efficient resource allocation scheme with joint consideration of relay selection, subcarrier pairing, and power allocation. For each selected relay, one subcarrier pair containing two subcarriers is allocated with the objective to reduce the transmit power consumption with minimum data rate guarantee.

- 2.
When imperfect CSI is assumed, the closed-form expressions of optimal power allocation, relay selection, and subcarrier pairing are derived.

- 3.
The proposed scheme is validated through extensive simulations. The performance manifests that our presented scheme is able to reduce the energy consumption with minimum data rate guarantee.

The remainder of this paper is organized as follows. The system and imperfect CSI models are given in Section 2. In Section 3, the relay selection and resource allocation problem is formulated as an optimization problem which can be decomposed into *N* independent subproblems. In the Section 4, we focused on solving these subproblems and by applying Karush-Kuhn-Tucker (KKT) conditions, the closed-form expressions of optimal power allocation, relay selection, and subcarrier assignment are derived. In the Section 5, the simulation results and performance analysis are given. We finally conclude the paper in Section 6.

## 2 System model

*S*

_{1}and

*S*

_{2},

*K*half-duplex RNs, and

*N*subcarriers. The applicability of this model is ubiquitous in different practical scenarios, e.g., cellular networks and wireless mesh/sensor networks, with the assumption that two nodes need to exchange information with each other and there is no direct path between them. Hence, the transmission should be finished via the RNs that are located between the sources. Due to the nature of half-duplex RNs that can not simultaneously receive and send data, 1/2 spectrum efficiency loss is brought. Thus, in this work, we adopt physical layer network coding to overcome such problem and information exchange can be finished in two time slots. In the considered system, all nodes operate in a time-division duplexing (TDD) manner. It can be noticed that the amount of correlation between different subcarriers relies on the relation of channel coherence bandwidth and subcarrier spacing. We assume that OFDM symbol duration is smaller compared with the channel coherence time. Therefore, we consider a quasi-static fading channel for which the channels are constant within one frame but change independently from one to another. Assuming channel reciprocity, the channel gain between

*S*

_{ j }and

*R*

*N*

_{ i }is the same as the channel gain between

*R*

*N*

_{ i }and

*S*

_{ j }on a certain subcarrier. The channel coefficient on the subcarrier

*m*between

*S*

_{1}and

*R*

*N*

_{ i }, and

*S*

_{2}and

*R*

*N*

_{ i }are denoted by \(h_{1,i}^{m}\) and \(h_{2,i}^{m}\), respectively, and the path loss between

*S*

_{1}and

*R*

*N*

_{ i }, and

*S*

_{2}and

*R*

*N*

_{ i }are denoted by

*L*

_{1,i }and

*L*

_{2,i }, respectively. Meanwhile, the zero mean additive Gaussian noise at

*S*

_{1},

*S*

_{2}, and

*R*

*N*

_{ i }on the subcarrier

*n*are denoted by \({\nu _{1}^{n}}, {\nu _{2}^{n}}\), and \({z_{i}^{n}}\). It is assumed that the noise follows \(\mathcal {N}\left (0, {\sigma _{w}^{2}}\right)\).

where *e*
_{1} and *e*
_{2} are the MMSE estimation errors and follow zero mean complex Gaussian distribution with variance \(\sigma _{e_{1}}^{2}\) and \(\sigma _{e_{2}}^{2}\), respectively, and the estimation errors are independent with the channel estimation results [11].

*m*. The transmit power of

*S*

_{1}on subcarrier

*m*is denoted as \(P_{s,1}^{m}\), and the transmit power of

*S*

_{2}on subcarrier

*m*is assumed to be \(P_{s,2}^{m}\). With the assumption of perfect synchronization at RNs, the signal received at the relay node

*R*

*N*

_{ i }is expressed as [3]

*S*

_{1}and

*S*

_{2}on subcarrier

*m*, respectively. In the second time slot,

*R*

*N*

_{ i }adopts the AF protocol and amplifies the received signal by an amplification factor \({\beta _{i}^{n}}\) on subcarrier

*n*. The amplification coefficient can be expressed as

*R*

*N*

_{ i }on subcarrier

*n*. In addition,

*ω*

_{ i }and \(\rho _{i}^{m,n}\) are defined as the relay selection indicator and subcarrier pairing indicator, respectively, i.e.,

*S*

_{1}and

*S*

_{2}on the subcarrier

*n*are given as

*S*

_{1}and

*S*

_{2}on the subcarrier

*n*can be written as

## 3 Problem formulation and simplification

In this section, we aim to propose an energy-efficient relay selection and resource allocation scheme when considering imperfect CSI. The objective is to find the optimal subcarrier pairing indicator variable set ρ={*ρ*
^{
m,n
},∀*m*,*n*}, relay selection indicator set ω={*ω*
_{
i
},∀*i*}, and the power allocation variables \(\mathbf {P} = \left \{ P_{s,1}^{m}, P_{s,2}^{m}, P_{r,i}^{n}, \forall i, m,n\right \}\) that are able to minimize the total transmission power without sacrificing the required data rate.

### 3.1 Problem formulation

*S*

_{1}to

*S*

_{2}and \(\bar {R}_{2}\) as the required minimum data rate for transmission from

*S*

_{2}to

*S*

_{1}, then the resource allocation optimization problem can be expressed as

*S*

_{1}to

*S*

_{2}and from

*S*

_{2}to

*S*

_{1}on the subcarrier pair \(\mathcal {I}\) containing subcarrier

*m*in the first time slot and

*n*in the second time slot. The \(r_{1}^{\mathcal {I}}\) and \(r_{2}^{\mathcal {I}}\) can be expressed as

### 3.2 Problem simplification

*S*

_{1}and \(\bar {r_{2}}\) be the one of the transmission started by

*S*

_{2}. Thus, on per-subcarrier pair basis, the subproblem can be expressed as

The total transmit power is the sum of the transmission powers on each subcarrier pair. Decomposing the problem (13) into several independent per-subcarrier pair subproblems can guarantee the accuracy with lower complexity.

*S*

_{1}and

*S*

_{2}on subcarrier

*m*can be expressed as

*i*can be expressed as in (21), where [.]

^{+}= max{0,[.]}. We can notice that the power allocation at data nodes and RN depend on the estimation error \(\sigma _{e_{1}}^{2}\) and \(\sigma _{e_{2}}^{2}\).

*R*

*N*

_{ i }participates in the transmission, it is observed that at least one subcarrier pair should be assigned to relay node

*R*

*N*

_{ i }. Therefore, the subcarrier pairing and relay selection have a certain relationship when proper RN is selected, i.e.

*m*,

*n*) is assigned to the relay

*R*

*N*

_{ i }. Hence, relay selection indicator is able to be removed, and modified subcarrier pairing indicator can be used for simplicity. The problem can be simplified as

*α*

_{1}and

*α*

_{2}can be expressed as follows:

To this end, we have simplified the original optimization problem with *K*(2*N*+1)+2*N* variables to the subproblem only containing 2*K* variables. If problem (23) is solvable, we can reach the expressions of transmit power of data nodes and RN on subcarrier pair (*m*,*n*). Then, the transmit power on other subcarrier pairs can be obtained in the same way, and the total power consumption can be achieved by the summation of the transmit power consumption on all subcarrier pairs.

## 4 Optimization of per-subproblem

One can notice that the formulated problem is a mixed integer programming problem, which considers the minimum power consumption on the subcarrier pair. It is known that the global optimal solution for formulated resource allocation problem can be reached by the exhaustive searching for the optimal value in the subcarrier pairing indicator set \(\left \{\rho _{i}^{m,n}, \forall i,m,n\right \}\) and the amplification coefficient set \(\left \{{\beta _{i}^{n}}, \forall i,n\right \}\). Then, the optimal transmission power can be achieved when the optimal relay and subcarrier pair are determined. However, such exhaustive search or branch-and-bound method is needed to obtain the global optimal solution which is computationally infeasible.

To reduce the computational complexity and make the problem tractable, we consider a opportunistic subcarrier assignment, where each subcarrier is assigned to a unique RN. Therefore, each subproblem can be solved via the joint optimization of relay selection, subcarrier pairing, and power allocation.

### 4.1 Relay selection for given subcarrier pairing

*K*RNs to ensure the minimum transmission power on the given subcarrier pairing, namely

### 4.2 Subcarrier pairing

*m*at the first time slot for the transmission from source to RN and the subcarrier

*n*at the second time slot for the transmission from RN to source with objective of minimizing the energy consumption. For the the optimal relay \(\phantom {\dot {i}\!}{RN}_{d^{*}}\), the optimal subcarrier pair can be determined as follows:

### 4.3 Power allocation

*m*,

*n*) is uniquely assigned to relay

*R*

*N*

_{ i }, \(\rho _{i}^{m,n}\) can be expressed as follows:

*m*,

*n*) for the selected relay node

*R*

*N*

_{ d }. Substitute the optimal amplification coefficient into the amplification coefficient (3) and (18), (19), the closed-form expressions of transmission power allocated to sources

*S*

_{1},

*S*

_{2}and relay

*R*

*N*

_{ d }can be expressed as follows:

### 4.4 Algorithm description

We have proposed an energy-efficient radio resource allocation scheme which jointly considers relay selection, subcarrier pairing, and power allocation problem in the OFDMA TWRNs. The objective is to find the optimal RNs and subcarrier pairings under minimum data rate constraints in order to minimize the power consumption of mutual communication between two sources. The complexity of solving problem of relay selection and subcarrier pairing at two hops is \(\mathcal {O}(KN^{2})\). Realization of the resource allocation is given in Algorithm 1.

## 5 Performance analysis

### 5.1 Simulation setting

The path loss model is \( L_{i,j}=20 \mathop {log}d_{i,j}+20 \mathop {log} f_{c}-28\), where *d*
_{
i,j
} is the distance between node *i*, and node *j* and *f*
_{
c
} is the center carrier frequency, which considered to be 2 GHz in the simulation. We assume that the spectral density of noise is equal to −174 dBm/Hz and the bandwidth of one subcarrier is 15 KHz. The distance between two sources is 0.5 km, and RNs are randomly distributed between them. We discuss the performance gain of the proposed resource allocation algorithm with symmetric link rate and asymmetric link rate; meanwhile, we also examine the impact of the imperfect CSI as well as the number of RNs on the system performance.

where *P*
_{
total
} is the overall transmit power under required link rate; the coefficient 1/2 stands for the required two time slots for completing the transmission.

### 5.2 Simulation results

*K*=5,

*N*=64. As one can observe, when data rate increases, the consumed energy goes higher as well. The energy consumption is relatively high when the variance of channel estimation error is getting stronger. For example, when \(\sigma _{e_{1}}^{2} = 0.1, \sigma _{e_{2}}^{2} = 0.5 \), the energy consumption is about 1 dB higher than the one when there is perfect CSI at source. It can be also noticed that when \(\bar {R}_{1} =\bar {R}_{2} = 1.8\) Mbps, the power consumption difference between CSI perfection and imperfect is up to 0.6 dB. However, the difference is increased to 2.5 dB when \(\bar {R}_{1} =\bar {R}_{2} = 2\) Mbps.Therefore, from Fig. 2, we can conclude that the imperfect CSI at source leads to a higher energy consumption and with the increase of the link rate, CSI imperfection requires more energy consumption.

*%*performance gain when \(\sigma _{e_{1}}^{2} = \sigma _{e_{2}}^{2} = 0.5\). It can be also well observed that as the number of RNs increases, the CSI imperfection has less impact on the power consumption as well as ECI performance performance. For example, when there are 10 RNs in the system, the power consumption gap is less than 0.3 dB between the cases of imperfect CSI and perfect CSI, while such gap increases to more than 1 dB when there are only 5 RNs. Same phenomena can also be observed in Fig. 4, which is mainly due to the fact that there are more choices for relay selection.

*S*

_{1}and RNs. Similarly, the results also show that the energy consumption and ECI performance can be improved along with the increase of the number of RNs, which again confirms that deploying more RNs can significantly reduce the energy consumption. For instance, when \(\sigma _{e_{1}}^{2} = \sigma _{e_{2}}^{2} = 0.5\), the system with 10 RNs has about 0.5 dB less power consumption than the one with 8 RNs. In addition, the optimal performance is obtained while \(\bar {R_{1}}=\bar {R_{2}}\), which indicates that the efficiency of symmetric rate is better than asymmetric rate. Hence, for the sake of energy conservation and efficiency, we need to ensure the consistence of bidirectional link rate in the practical transmission.

*S*

_{1}and RNs is normalized to the distance between data nodes and varies from 0.1 to 0.9. In addition, we also consider different estimation error variances. It can be found the power consumption reaches its lowest when the RNs are deployed roughly in the middle of data nodes. Moreover, the influence of imperfect CSI can be easily observed.

## 6 Conclusions

In this paper, we have studied the radio resource allocation scheme in an OFDMA two-way relay networks with imperfect CSI. The relays adopt AF protocol and can assist the transmission between two source nodes in the system. Different from most of the existed works, we consider a realistic setting: the imperfection of CSI. Without considering direct link between two data source nodes, an energy-efficient resource allocation with joint relay selection, subcarrier pairing and allocation, and power allocation is proposed to achieve the minimum transmit power consumption with required data rate. Through theoretical analysis, the resource allocation problem in this paper can be decomposed into several independent subproblems, and the closed-form expressions of power allocation at two data nodes and relays are derived. The simulations illustrate the impact of imperfect CSI on the system performance and show that the scheme proposed in this paper can obtain performance improvement in terms of energy efficiency compared with other recent proposed schemes.

## Declarations

### Acknowledgements

This work is partially supported by the Academy of Finland (Decision No. 284748, 288473). The authors also would like to thank the editor and the anonymous reviewers for their kind comments.

**Open Access** This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

## Authors’ Affiliations

## References

- R Pabst, B Walk, D Schultz, Relay-based deployment concepts for wireless and mobile broadband radio. IEEE Commun. Mag. 42(9), 80–89 (2004).View ArticleGoogle Scholar
- X Zhang, X Tao, Y Li, J Lu, QoS-aware scheduling with optimization of base-station power allocation in downlink cooperative OFDMA systems. EURASIP J. Wirel. Commun. Netw. 2013, 247 (2013). doi:http://dx.doi.org/10.1186/1687-1499-2013-247.View ArticleGoogle Scholar
- M Zhou, Q Cui, R Jantti, R Tao, Energy-efficient relay selection and power allocation for two-way relay channel with analog network coding. IEEE Commun. Lett. 16(6), 816–819 (2012).View ArticleGoogle Scholar
- K Jitvanichphaibool, R Zhang, YC Liang, Optimal resource allocation for two-way relay-assisted OFDMA. IEEE Trans. Veh. Technol. 58(7), 3311–3321 (2009).View ArticleGoogle Scholar
- M Zhou, Q Cui, M Valkama, X Tao, Energy-efficient resource allocation for OFDMA-based two-way relay channel with physical-layer network coding. EURASIP J. Wireless Comm. and Networking. 2012, 66 (2012).View ArticleGoogle Scholar
- MK Awad, V Mahinthan, M Mehrjoo, X Shen, JW Mark, A dual-decomposition-based resource allocation for OFDMA networks with imperfect CSI. IEEE Trans. Veh. Technol. 59(5), 2394–2403 (2010).View ArticleGoogle Scholar
- MJ Taghiyar, S Muhaidat, Relay selection with imperfect CSI in bidirectional cooperative networks. IEEE Commun. Lett. 16(1), 57–59 (2012).View ArticleGoogle Scholar
- Z Chang, T Ristaniemi, in
*2012 IEEE Militory Communications Conference*. Resource Allocation for Cooperative Relay-assisted OFDMA Networks with Imperfect CSI (IEEEOrlando, FL, 2012), pp. 1–6. doi:http://dx.doi.org/10.1109/MILCOM.2012.6415882.View ArticleGoogle Scholar - Z Chang, T Ristaniemi, Z Niu, Radio resource allocation for collaborative OFDMA relay networks with imperfect channel state information. IEEE Trans. Wirel. Commun. 13(5), 2824–2835 (2014).View ArticleGoogle Scholar
- S Mallick, MM Rashid, VK Bhargava, Joint relay selection power allocation for decode-and-forward cellular relay network with channel uncertainty. IEEE Trans. Wirel. Commun. 11(10), 3496–3508 (2012).View ArticleGoogle Scholar
- R Devarajan, A Punchihewa, VK Bhargava, Energy-aware power allocation in cooperative communication systems with imperfect CSI. IEEE Trans. Wirel. Commun. 61(5), 1633–1639 (2013).View ArticleGoogle Scholar
- S Mallick, R Devarajan, MM Rashid, VK Bhargava, Resource allocation for selective relaying based cellular wireless system with imperfect CSI. IEEE Trans. Wirel. Commun. 61(5), 1822–1834 (2013).View ArticleGoogle Scholar
- Y Jia, A Vosoughi, Outage probability and power allocation of two-way amplify-and-forward relaying with channel estimation errors. IEEE Trans. Wirel. Commun. 11(6), 1985–1990 (2012).View ArticleGoogle Scholar
- L Fan, X Lei, P Fan, RQ Hu, Outage probability analysis and power allocation for two-way relay networks with user selection and outdated channel state information. IEEE Commun. Lett. 64(5), 638–641 (2012).View ArticleGoogle Scholar
- A Rao, MD Nisar, MS Alouini, Robust power allocation for multicarrier amplify-and-forward relaying systems. IEEE Trans. Veh. Technol. 62(7), 3475–3481 (2013).View ArticleGoogle Scholar
- S Boyd, L Vandenberghe,
*Convex Optimization*(Cambridge University Press, Cambridge UK, 2004).MATHView ArticleGoogle Scholar - G Auer, O Blume, V Giannini, I Godor, M Imran, Y Jading, E Katranaras, M Olsson, D Sabella, P Skillermark, W Wajda, Energy efficiency analysis of the reference systems, areas of Improvements and target breakdown. EARTH Proj. D2.3, 39–40 (2010).Google Scholar