Opportunistic Interference Mitigation Achieves Optimal Degrees-of-Freedom in Wireless Multi-Cell Uplink Networks

Abstract

We introduce an opportunistic interference mitigation (OIM) protocol, where a user scheduling strategy is utilized in K-cell uplink networks with time-invariant channel coefficients and base stations (BSs) having M antennas. Each BS opportunistically selects a set of users who generate the minimum interference to the other BSs. Two OIM protocols are shown according to the number S of simultaneously transmitting users per cell: opportunistic interference nulling (OIN) and opportunistic interference alignment (OIA). Then, their performance is analyzed in terms of degrees-of-freedom (DoFs). As our main result, it is shown that KM DoFs are achievable under the OIN protocol with M selected users per cell, if the total number N of users in a cell scales at least as SNR (K−1)M . Similarly, it turns out that the OIA scheme with S(< M ) selected users achieves KS DoFs, if N scales faster than SNR (K−1)S . These results indicate that there exists a trade-off between the achievable DoFs and the minimum required N . By deriving the corresponding upper bound on the DoFs, it is shown that the OIN scheme is DoF-optimal. Finally, numerical evaluation, a two-step scheduling method, and the extension to multi-carrier scenarios are shown. Index TermsBase station (BS), channel state information, cellular network, degrees-of-freedom (DoFs), interference, opportunistic interference alignment (OIA), opportunistic interference mitigation (OIM), opportunistic interference nulling (OIN), uplink, user scheduling. Recently, as an alternative approach to show Shannon-theoretic limits, interference alignment (IA) was proposed by fundamentally solving the interference problem when there are two communication pairs [7]. It was shown in [8] that the IA scheme can achieve the optimal degrees-of-freedom (DoFs), which are equal to K/2, in the K-user interference channel with time-varying channel coefficients. The basic idea of the scheme is to confine all the undesired interference from other communication links into a pre-defined subspace, whose dimension approaches that of the desired signal space. Hence, it is possible for all users to achieve one half of the DoFs that we could achieve in the absence of interference. Since then, interference management schemes based on IA have been further developed and analyzed in various wireless network environments: multiple-input multiple-output (MIMO) interference network [9] [16]. These constraints need to be relaxed in order to apply IA to more practical systems. In [9], a distributed IA scheme was constructed for the MIMO interference channel with time-invariant coefficients. It requires only local CSI at each node that can be acquired from all received channel links via pilot signaling, and thus is more feasible to implement than the original one [8]. However, a great number of iterations should be performed until designed transmit/receive beamforming (BF) vectors converge prior to data transmission. Now we would like to consider practical wireless uplink networks with K-cells, each of which h...

Interference Mitigation and Sum Rate Optimization for MIMO Downlink Small Cells

“…Authors in [18] studied OIA techniques for uplink MIMO multi-cells in homogeneous networks. A user scheduling strategy for multi-cell uplink networks was investigated in [9]. However, the BS transmits only one data stream to its scheduled user, and homogeneous wireless networks are assumed.…”

“…Thus, we design the SBS precoders as a cascade of two precoders. One precoder is used to cancel interference from the SBSs to the MUE while the other unitary precoder is generated according to the isotropic distribution [9]. Since SBSs use space-division multiple access, apart from cross-tier interference, co-tier interference will adversely affect the system performance if multiple small cell UEs (SUEs) in the same cell transmit at the same time.…”

“…Additionally, the SBSs can generate the random matrices B B B ,k ∈ C N −d 0, π (0) ×d , k and broadcast them to their users. Alternatively, the pre-defined pseudorandom matrices can be used and are known to all users in the network [9], [16]. On the other hand, to mitigate co-tier interference at the SUEs, the -th SBS will opportunistically select a user among its associated F users to communicate with.…”

Cognitive Interference Alignment for Spectral Coexistence

“…The DoF regions are characterized for several wireless channels such as MIMO BC, interference channels (ICs), including X and multihop ICs, and the CR channels [68]. The DoF metric has been extensively used for interference mitigation and alignment objectives in various wireless networks such as interference mitigation in multicell networks [10,31], interference mitigation in two-cell MIMO interfering BCs [63], IA in CR networks [14,34,57]. The main limitation of the DoF metric is that it does not provide much insight to optimally manage interference when all signals are not comparable, since it forces all channels to be equally strong.…”

Performance Evaluation of Interference Alignment Technique in Wireless LAN Environment

“…적인 빔형성 기법 연구 [3] , 편광 안테나를 사용함으로 써 가정하는 가시선 (line-of-sight) 채널에서의 간섭정 렬 방식 구현 [4] , 다중안테나 사용 시 반복적으로 송/수 신단 빔 형성기를 업데이트하는 간섭정렬 기법 개발 [5] 과 같은 연구가 수행되었으며 [6][7] [2,8] , X 네트워크 [9] , 셀룰라 네트워크 [6,7,10,11] 을 포함한다. …”