Resource allocation with interference mitigation in OFDMA femtocells for co-channel deploymenta

Femtocells have been considered as a promising technology to provide better indoor coverage and spatial reuse gains. However, the co-channel deployment of macrocells and femtocells is still facing challenges arising from potentially severe inter-cell interference. In this article, we investigate the uplink resource allocation problem of femtocells in co-channel deployment with macrocells. We first model the uplink power and subchannel allocation in femtocells as a non-cooperative game, where inter-cell interference is taken into account in maximizing the femtocell capacity and uplink femto-to-macro interference is alleviated by charging each femto user a price proportional to the interference that it causes to the macrocell. Based on the non-cooperative game, we then devise a semi-distributed algorithm for each femtocell to first assign subchannels to femto users and then allocate power to subchannels. Simulation results show that the proposed interference-aware femtocell uplink resource allocation algorithm is able to provide improved capacities for not only femtocells, but also the macrocell, as well as comparable or even better tiered fairness in the two-tier network, as compared with existing unpriced subchannel assignment algorithm and modified iterative water filling-based power allocation algorithm. Introduction Nowadays above 50% of voice services and 70% of data traffics occur indoors [1]. Insufficient indoor coverage of macrocells has led to increasing interest in femtocells, which have been considered in major wireless communication standards such as 3GPP LTE/LTE-Advanced [2]. Dedicated-channel deployment of femtocells, where femtocells and macrocells are assigned with different (or orthogonal) frequency bands, may not be preferred by operators due to the scarcity of spectrum resources and difficulties in implementation. While in co-channel deployment, where femtocells and macrocells share the same spectrum, cross-tier interference could be severe [3], especially when femtocell base stations (FBSs) are deployed close to a macrocell base station (MBS) [4]. Due to the fundamental role of macrocells in providing blanket *Correspondence: [email protected] 1Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing 100876, China 2Institute of Telecommunications, King’s College London, London WC2R 2LS, UK Full list of author information is available at the end of the article cellular coverage, their capacities and coverage should not be affected by co-channel deployment of femtocells. Power control has widely been used to mitigate intercell interference in co-channel deployment of femtocells. For alleviating uplink interference caused by co-channel femto users to macrocells, a distributed femtocell power control algorithm is developed based on non-cooperative game theory in [5], while in [6] femto users are priced for causing interference to macrocells in the power allocation based on a Stackelberg model. In [7], cross-tier interference is mitigated through both open-loop and closed-loop uplink power controls. In [8], a distributed power control scheme is proposed based on a supermodular game. A lot of work has also been done on subchannel allocation in co-channel deployment of femtocells. In [9], a hybrid frequency assignment scheme is proposed for femtocells deployed within coverage of a macrocell. In [10], distributed channel selection schemes are proposed for femtocells to avoid inter-cell interference, at the cost of reduced frequency reuse efficiency. In [11], a subchannel allocation algorithm based on a potential game © 2012 Zhang et al; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Zhang et al. EURASIP Journal onWireless Communications and Networking 2012, 2012:289 Page 2 of 9 http://jwcn.eurasipjournals.com/content/2012/1/289 model is proposed to mitigate both co-tier and cross-tier interferences. Recently, several studies considering both power and subchannel allocation in femtocells have been reported. In [12], a joint power and subchannel allocation algorithm is proposed to maximize the total capacity of densely deployed femtocells, but the interference caused by femtocells tomacrocells is not considered. In the collaborative resource allocation scheme [13], cross-tier interference is approximated as additive white Gaussian noise (AWGN). In the Lagrangian dual decomposition-based resource allocation scheme [14], constraints on cross-tier interference are used in power allocation, but subchannels are assigned randomly to femto users. In [15], a distributed downlink resource allocation scheme based on a potential game and convex optimization is proposed to increase the total capacity of macrocells and femtocells, but at the price of reduced femtocell capacity. In [16], the distributed power and subchannel allocation for co-channel deployed femtocells is modeled as a non-cooperative game, for which a Nash Equilibrium is obtained based on a timesharing subchannel allocation, but the constraint on maximum femto-user transmit power is ignored in solving the non-cooperative game. In this article, we focus on the uplink power and subchannel allocation problem of orthogonal frequency division multiple access (OFDMA)-based femtocells in cochannel deployment with macrocells. We first model the uplink power and subchannel allocation in femtocells as a non-cooperative game, where inter-cell interference is taken into account in maximizing femtocell capacity and uplink interference from femto users to the macrocell is alleviated by charging each femto user a price proportional to the amount of interference that it causes to the macrocell. Based on the non-cooperative game, we then devise a semi-distributed algorithm for each femtocell to first assign subchannels to femto users and then allocate power to subchannels accordingly. Simulation comparisons with existing unpriced subchannel assignment and modified iterative water filling (MIWF)-based power allocation algorithms show that the proposed interferenceaware femtocell uplink resource allocation algorithm is able to provide improved capacities for not only femtocells, but also the macrocell, as well as comparable or even better tiered fairness in a co-channel two-tier network. The rest of this article is organized as follows. The system model and problem formulation are presented in “System model and problem formulation” section. In “Interference-aware resource allocation” section, the interference-aware femtocell uplink resource allocation algorithm is proposed. Performance of the proposed algorithm is evaluated by simulations in “Simulation results and discussion” section. Finally, “Conclusion” section concludes the article. Systemmodel and problem formulation Systemmodel As shown in Figure 1, we consider a two-tier OFDMA network where K co-channel FBSs are randomly overlaid on a macrocell. We focus on resource allocation in the uplink of femtocells, that is, the subchannel assignment to femto users and the power allocation on subchannels in femtocells. Let M and F denote the numbers of active macro users camping on the macrocell and active femto users camping on each femtocell, respectively. Users are uniformly distributed in the coverage area of their serving cell. All femtocells are assumed to be closed access [17]. The OFDMA system has a bandwidth of B, which is divided into N subchannels. Channel fading on each subcarrier is assumed the same within a subchannel, but may vary across different subchannels. We assume that channel fading is composed of path loss and frequency-flat Rayleigh fading. We denote gMF k,u,n and g FF j,k,u,n as the channel gains on subchannel n from femto user u in femtocell k to the MBS and FBS j, respectively, where j, k ∈ {1, 2, . . . ,K}, u ∈ {1, 2, . . . , F}, and n ∈ {1, 2, . . . ,N}; denote gM w,n and gFM k,w,n as the channel gains on subchannel n from macro user w(∈ {1, 2, . . . ,M}) to the MBS and FBS k, respectively; denote pk,u,n and p M w,n as the transmit power levels on subchannel n of femto user u in femtocell k and macro user w, respectively. Then, we define Pn = [ pk,u,n]K×F as the power allocation matrix of the K femtocells on subchannel n, and An = [ ak,u,n]K×F as the subchannel assignment indication matrix for the K femtocells on subchannel n, where ak,u,n = 1 if subchannel n is assigned to femto user u in femtocell k, and ak,u,n = 0 otherwise. The received signal-to-interference and noise ratio (SINR) for femto user u on the nth subchannel in the kth femtocell is given by γ F k,u,n = ak,u,npk,u,ng FF k,k,u,n (K ,F) ∑ (j,v) =(k,u) aj,v,npj,v,ng k,j,v,n + pMw,ng k,w,n + σ 2 (1) where ∑(K ,F) (j,v) =(k,u) aj,v,np F j,v,ng k,j,v,n = ∑K j=1 ∑F v=1 aj,v,npj,v,n gFF k,j,v,n − ak,u,npk,u,ng k,k,u,n is the interference caused by other co-channel femtocells, pw,ng k,w,n is the interference caused by the macrocell, and σ 2 is the AWGN power. The SINR for macro user w using the nth subchannel is given by γM w,n = pw,ng w,n K ∑ j=1 F ∑ v=1 aj,v,npj,v,ng MF j,v,n + σ 2 (2) Based on Shannon’s capacity formula, the capacities on subchannel n of femto user u in femtocell k and macro Zhang et al. EURASIP Journal onWireless Communications and Networking 2012, 2012:289 Page 3 of 9 http://jwcn.eurasipjournals.com/content/2012/1/289 Figure 1 Topology of the two-tier network comprising by a macrocell and K co-channel femtocells. user w are given, respectively, by CF k,u,n = B N log2(1+ γ F k,u,n) (3) CM w,n = B N log2(1+ γM w,n) (4) Problem formulation The maximization of the total capacity of the K femtocells is formulated as follows.