Opportunistic Interference Alignment Research Articles

Distributed Opportunistic Interference Alignment Using Threshold-Based Beamforming in MIMO Overlay Cognitive Radio

To achieve the full multiplexing gain of a K-multiuser multiple-input-multiple-output (MIMO) overlay cognitive radio (CR) network, a distributed opportunistic interference alignment (DOIA) technique using a new beamforming algorithm, namely, threshold-based beamforming (TBF), is proposed. The MIMO overlay CR system consists of one primary user (PU) and K secondary users (SUs) where the local channel state information is available at both the transmitters and receivers of SUs. Assuming that the receiver and the transmitter of the PU have perfect knowledge of their own channel matrix, the PU uses a maximum eigenmode beamforming (MEB) scheme for its data transmission to release some of its eigenmodes for the SUs. For this virtual cooperation, the SUs align their transmitted signals to the spatial directions (SDs) associated with the unused PU's eigenmodes to ensure orthogonality between the links of the PU and the SUs. In addition, the MEB scheme overcomes the limitation of the conventional water-filling power allocation (WPA) in releasing the PU's eigenmodes for the SUs at high signal-to-noise ratios (SNRs). A noniterative and distributed power-allocation strategy, namely, TBF, is proposed, in which the SUs' links with a maximum eigenvalue above a certain threshold transmit data at full power, and the rest remain silent. This protocol, along with the MEB scheme, enables the MIMO overlay CR system to enhance the throughput of the network described as the average sum rate of both the PU and SUs. The proposed DOIA-TBF protocol allows the opportunistic SUs to use the same frequency band of a preexisting PU and guarantees that no interference is imposed on the PU's performance for such a MIMO overlay CR system.

Energy-Efficient Opportunistic Interference Alignment With MMSE Receiver

This paper introduces a refined opportunistic interference alignment (OIA) technique that uses minimum mean square error (MMSE) detection at the receivers in multiple-input multipleoutput multi-cell uplink networks. In the OIA scheme under consideration, each user performs the optimal transmit beamforming and power control to minimize the level of interference generated to the other-cell base stations, as in the conventional energy-efficient OIA. The result showed that owing to the enhanced receiver structure, the OIA scheme shows much higher sum-rates than those of the conventional OIA with zero-forcing detection for all signal-to-noise ratio regions.

Energy-Efficient Opportunistic Interference Alignment

We introduce an energy-efficient distributed opportunistic interference alignment (OIA) scheme that greatly improves the sum-rates in multiple-cell uplink networks while reducing the transmit power consumption compared to the conventional OIA scheme. In the proposed scheme, each user employs optimal transmit vector design and power control strategy in the sense of minimizing the amount of generated interference to other-cell base stations while satisfying a given required signal quality. Our main result indicates that owing to the reduced interference level, the proposed OIA method attains larger sum-rates than those of OIA with no power control (i.e., with full transmit power) for almost all signal-to-noise ratio regions, thus resulting in improved energy efficiency.

Blind Opportunistic Interference Alignment in MIMO Cognitive Radio Systems

Opportunistic interference alignment (OIA) is a technique that enables the multiple-input multiple-output (MIMO) secondary user (SU) to exploit the inherent spatial spectrum holes of the MIMO primary user's (PU) communication link while the PU transmissions remain interference free, thus generalizing the concept of interweave cognitive radio (CR) systems. A typical characteristic of an interweave technique is that, in general, no interaction between the PU and the SU systems is assumed, thus rendering infeasible, in many cases, the channel state information (CSI) requirements of the existing OIA techniques. The goal of the present paper is to propose a MIMO SU transceiver system that applies an OIA technique in a manner completely oblivious to the PU system so that both the alignment technique and the corresponding CSI estimation scheme require no interaction with the PU system. To this end, at first, a new improved OIA technique is proposed. The resulting technique requires CSI that can be estimated blindly at the SU ends and achieves better performance in several cases as it aligns the PU and SU signals to orthogonal sub-spaces at both the PU and the SU receivers. Then, a novel blind CSI estimation scheme is developed for the new OIA technique. The exact theoretical ergodic capacity of the new OIA technique is derived for the perfect CSI case. Some insightful theoretical results are also derived for the imperfect CSI case which, to the best of our knowledge, are some of the first ones in the OIA/IA literature. The performance of the proposed schemes is verified via extensive simulations.

Codebook-Based Opportunistic Interference Alignment

For the multiple-input multiple-output interfering multiple-access channels (IMACs), opportunistic interference alignment (OIA) using the singular value decomposition (SVD)-based beamforming at each user fundamentally reduces the user scaling condition required to achieve any target DoF, compared to that for the single-input multiple-output IMAC. In this paper, we tackle two practical challenges of the existing SVD-based OIA: 1) the need of full feedforward of the selected users' beamforming weight vectors and 2) a low rate achieved based on the exiting zero-forcing receiver. We first propose a codebook-based OIA, in which the weight vectors are chosen from a predefined codebook with a finite size so that information of the weight vectors can be sent to the belonging BS with limited feedforward. We derive the codebook size required to achieve the same user scaling condition as the SVD-based OIA case for both Grassmannian and random codebooks. Surprisingly, it is shown that the derived codebook size is the same for the two codebook methods. Second, we introduce an enhanced receiver at the base stations (BSs) in pursuit of further improving the achievable rate. Assuming no collaboration between the BSs, the interfering links between a BS and the selected users in neighboring cells are difficult to be acquired at the belonging BS. We propose the use of a simple minimum Euclidean distance receiver operating with no information of the interfering links. With the help of the OIA, we show that this new receiver asymptotically achieves the channel capacity as the number of users increases.

Interference Alignment in a Poisson Field of MIMO Femtocells

The need for bandwidth and the incitation to reduce power consumption lead to the reduction of cell size in wireless networks. This allows reducing the distance between a user and the base station, thus increasing the capacity. A relatively inexpensive way of deploying small-cell networks is to use femtocells. However, the reduction in cell size causes problems for coordination and network deployment, especially due to the intra- and cross-tier interference. In this paper, we consider a two-tier multiple-input multiple-output (MIMO) network in the downlink, where a single macrocell base station with multiple transmit antennas coexists with multiple closed-access MIMO femtocells. With multiple receive antennas at both the macrocell and femtocell users, we propose an opportunistic interference alignment scheme to design the transmit and receive beamformers in order to mitigate intra- (or inter-) and cross-tier interference. Moreover, to reduce the number of macrocell and femtocell users coexisting in the same spectrum, we apply a random spectrum allocation on top of the opportunistic interference alignment. Using stochastic geometry, we analyze the proposed scheme in terms of the distribution of a received signal-to-interference-plus-noise ratio, spatial average capacity, network throughput, and energy efficiency. In the presence of imperfect channel state information, we further quantify the performance loss in spatial average capacity. Numerical results show the effectiveness of our proposed scheme in improving the performance of random MIMO femtocell networks.

Opportunistic Interference Alignment for MIMO Interfering Multiple-Access Channels

We consider the K-cell multiple-input multiple-output (MIMO) interfering multiple-access channel (IMAC) with time-invariant channel coefficients, where each cell consists of a base station (BS) with M antennas and N users having L antennas each. In this paper, we propose two opportunistic interference alignment (OIA) techniques utilizing multiple transmit antennas at each user: antenna selection-based OIA and singular value decomposition (SVD)-based OIA. Their performance is analyzed in terms of user scaling law required to achieve KS degrees-of-freedom (DoF), where S(≤ M) denotes the number of simultaneously transmitting users per cell. We assume that each selected user transmits a single data stream at each time-slot. It is shown that the antenna selection-based OIA does not fundamentally change the user scaling condition if L is fixed, compared with the single-input multiple-output (SIMO) IMAC case, which is given by SNR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(K-1)S</sup> , where SNR denotes the signal-to-noise ratio. In addition, we show that the SVD-based OIA can greatly reduce the user scaling condition to SNR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(K-1)S-L+1</sup> through optimizing a weight vector at each user. Simulation results validate the derived scaling laws of the proposed OIA techniques. The sum-rate performance of the proposed OIA techniques is compared with the conventional techniques in MIMO IMAC channels and it is shown that the proposed OIA techniques outperform the conventional techniques.

On the Achievable DoF and User Scaling Law of Opportunistic Interference Alignment in 3-Transmitter MIMO Interference Channels

In this paper, we propose opportunistic interference alignment (OIA) schemes for three-transmitter multiple-input multiple-output (MIMO) interference channels (ICs). In the proposed OIA, each transmitter has its own user group and selects a single user who has the most aligned interference signals. The user dimensions provided by multiple users are exploited to align interfering signals. Contrary to conventional IA, perfect channel state information of all channel links is not required at the transmitter, and each user just feeds back one scalar value to indicate how well the interfering channels are aligned. We prove that each transmitter can achieve the same degrees of freedom (DoF) as the interference free case via user selection in our system model that the number of receive antennas is twice of the number of transmit antennas. Using the geometric interpretation, we find the required user scaling to obtain an arbitrary non-zero DoF. Two OIA schemes are proposed and compared with various user selection schemes in terms of achievable rate/DoF and complexity.

동적 셀 선택 기반 기회적 간섭 정렬

An opportunistic interference alignment based on dynamic cell selection is proposed. Since the proposed method can switch the desired signal space and the interference space of received signals, an additional selective diversity gain increases. The performance analysis using probabilistic models provides a mathematical expression for the sum-rate capacity. Simulation examples show that the proposed method achieves the higher sum-rate capacity than that of the conventional opportunistic interference alignment.

A Novel Joint Precoding and Scheduling Scheme with Opportunistic Interference Alignment for CoMP

A Novel Joint Precoding and Scheduling Scheme with Opportunistic Interference Alignment for CoMP

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

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 of simultaneously transmitting users per cell, S: 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 of users in a cell, N, scales at least as SNR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(K-1)M</sup> . Similarly, it turns out that the OIA scheme with S(<;M) selected users achieves KS DoFs, if N scales faster than SNR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(K-1)S</sup> . 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.

Opportunistic Interference Alignment for Interference-Limited Cellular TDD Uplink

We introduce an opportunistic interference alignment (OIA) for cellular networks, where a user scheduling strategy is utilized in time-division duplexing uplink communication environments with time-invariant channel coefficients and multi-antenna base stations (BSs). In the OIA scheme, each BS opportunistically selects users who generate the minimum interference to the other BSs. More specifically, each BS broadcasts its pre-designed interference directions, e.g., orthonormal random vectors, to all the users in other cells. Then, each user computes the amount of its generating interference, affecting the other BSs, and feedbacks it to its home cell BS. Note that the proposed OIA does not require global channel state information, time/frequency expansion, and a number of iterations, thereby resulting in easier implementation. Simulation results show that the proposed scheme provides significant improvement in terms of sum rates.

Opportunistic Spatial Orthogonalization and Its Application in Fading Cognitive Radio Networks

Opportunistic Spatial Orthogonalization (OSO) is a cognitive radio scheme that allows the existence of secondary users and hence increases the sum throughput, even if the primary user occupies all the frequency bands all the time. The key idea is to exploit the spatial dimensions to orthogonalize users and hence minimize interference. However, unlike the time and frequency dimensions, there is no universal basis for the set of all multi-dimensional spatial channels, which motivated the development of OSO. On one hand, OSO can be viewed as a multi-user diversity scheme that exploits the channel randomness and independence. On the other hand, OSO can be interpreted as an opportunistic interference alignment scheme for asymmetric users, where the interference from multiple secondary users is opportunistically aligned at the direction that is orthogonal to the primary user's signal space. In the case of multiple-input multiple-output (MIMO) channels, the OSO scheme can be interpreted as “riding the peaks” over the eigen-channels, and ill-conditioned MIMO channel, which is traditionally viewed as detrimental, is shown to be beneficial with respect to the sum throughput. Throughput advantages are thoroughly studied, both analytically and numerically.

From Spectrum Pooling to Space Pooling: Opportunistic Interference Alignment in MIMO Cognitive Networks

We describe a noncooperative interference alignment (IA) technique which allows an opportunistic multiple input multiple output (MIMO) link (secondary) to harmlessly coexist with another MIMO link (primary) in the same frequency band. Assuming perfect channel knowledge at the primary receiver and transmitter, capacity is achieved by transmiting along the spatial directions (SD) associated with the singular values of its channel matrix using a water-filling power allocation (PA) scheme. Often, power limitations lead the primary transmitter to leave some of its SD unused. Here, it is shown that the opportunistic link can transmit its own data if it is possible to align the interference produced on the primary link with such unused SDs. We provide both a processing scheme to perform IA and a PA scheme which maximizes the transmission rate of the opportunistic link. The asymptotes of the achievable transmission rates of the opportunistic link are obtained in the regime of large numbers of antennas. Using this result, it is demonstrated that depending on the signal-to-noise ratio and the number of transmit and receive antennas of the primary and opportunistic links, both systems can achieve transmission rates of the same order.