Interference alignment (IA) is a promising technology for eliminating interferences while it still achieves the optimal capacity scaling. However, in practical systems, the IA feasibility limit and the heavy signaling overhead obstructs employing IA to large-scale networks. In order to jointly consider these issues, we propose the feedback overhead-aware IA clustering algorithm which comprises two parts: adaptive feedback resource assignment and dynamic IA clustering. Numerical results show that the proposed algorithm offers significant performance gains in comparison with conventional approaches.

Multicell cooperation is a promising technique to mitigate the inter-cell interference and improve the sum rate in cellular systems. Limited feedback design is of great importance to base station cooperation as it provides the quantized channel state information (CSI) of both the desired and interfering channels to the transmitters. Most studies on multicell limited feedback deal with scenarios of a single receive antenna at the mobile user. This paper, however, applies limited feedback to cooperative multicell multiple-input multiple-output (MIMO) systems where both base stations and users are equipped with multiple antennas. An optimized feedback strategy with random vector quantization (RVQ) codebook is proposed for interference aware coordinated beamforming that approximately maximizes the lower bound of the sum rate. By minimizing the upper-bound on the mean sum-rate loss induced by the quantization errors, we present a feedback-bit allocation algorithm to divide the available feedback bits between the desired and interfering channels for arbitrary number of transmit and receive antennas under different interfering signal strengths. Simulation results demonstrate that the proposed scheme utilizes the feedback resource effectively and achieves sum-rate performance reasonably close to the full CSI case.

Multi-cell cooperation is a promising technique to mitigate inter-cell interference arising from universal frequency reuse in cellular networks. Sharing channel state information (CSI) in neighboring cells can help enhance the overall system capacity at the cost of high feedback burden. In this paper, an asymmetric CSI feedback strategy is proposed for multi-cell cooperation beamforming. In order to improve the overall system performance, we optimize the limited feedback bandwidth based on the average received power from both serving and neighboring cells. Simulation results show that the proposed strategy utilizes the limited feedback bandwidth more efficiently, thereby achieving a higher sum rate.

In the Coordinated Multi-Point (CoMP) system under the condition of limited feedback, a reasonable coordinated set relies heavily on the splitting factor that is used to divide the total feedback bits into channel direction information (CDI) feedback bits and channel quality information (CQI) feedback bits. The relation of splitting factor and coordinated set is examined in this paper. After defining a penalty factor, we derive the net ergodic capacity optimization problem, whose variables to be optimized are the number of coordinated BSs, the divided area's radius and the splitting factor. According to an existing codebook and the quantized channel error model, the downlink received signal model is updated after adding the splitting factor. Through random matrix knowledge, the stochastic property of this model is obtained. A close approximate expression including the splitting factor to be optimized related to coordinated set is given. In addition, a revised adaptive feedback scheme is proposed to split the feedback bits. Simulation results show that the proposed scheme provides a significant performance gain, especially as the user velocity is high.

In this letter, we propose a non-cooperative limited feedback precoding and subchannel selection scheme for non-reciprocal multiple-input multiple-output (MIMO) interference channels. At each iteration of the proposed scheme, each user updates its precoder selection for each subchannel and then chooses the predetermined number of subchannels in a distributed and non-cooperative way. We present simulation results to verify the performance of the proposed scheme.

A leakage-aware Coordinated Scheduling/Coordinated Beamforming (CS/CB) scheme for heterogeneous networks with layered limited feedback is proposed. In particular, all pico cells cooperatively select an optimal beamforming vector for the macro cell within a CoMP cluster so as to minimizing leakage power from the macro cell. Simulations show that the proposed scheme outperforms the conventional non-CoMP scheme with perfect channel state information at teansmitter (CSIT). Furthermore, the feedback amount and scheduler complexity is decreased greatly.

In this letter, a quantization error-aware Tomlinson-Harashinma Precoding (THP) is proposed based on the equivalent zero-forcing (ZF) criterion in Multiuser Multiple-Input Single-Output (MU-MISO) systems with limited feedback, where the transmitter has only quantized channel direction information (CDI). This precoding scheme is robust to the channel uncertainties arising from the quantization error and the lack of channel magnitude information (CMI). Our simulation results show that the new THP scheme outperforms the conventional precoding scheme in limited feedback systems with respect to Bit Error Ratio (BER).

This letter proposes a robust joint linear precoding scheme based on the minimum mean squared error (MMSE) criterion for amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay broadcast systems with limited feedback, where only the quantized channel direction information (CDI) of the forward channel is available for the base station (BS) and the relay station (RS). The proposed scheme employs an iterative algorithm which alternately optimizes the BS and RS precoders to jointly minimize the expected MSE conditioned on the quantized CDI.

In this letter, we study the performance of multi-antenna relay networks with limited feedback beamforming in decode-and-forward (DF) relaying. Closed-form expression for both outage probability and symbol error rate are derived by using the moment generation function (MGF) of the combined signal-to-noise ratio (SNR) at the destination. Subjected to a total power constraint, we also explore adaptive power allocation between source and relay to optimize the performance. Simulations are given to verify the correctness of our theoretical derivations. Results show that the proposed adaptive power allocation solution significantly outperforms the uniform power allocation method.

Achievable rates of two different transmission schemes of the two-cell cooperative single user (CSU) multi-input multi-output (MIMO) system with hybrid feedback is studied, in which one cell has the channel state information (CSI) from a mobile station (MS) and the other has channel covariance information (CCI) from it. Disjoint encoding over two base stations (BSs) is shown to achieve the capacity of the CSU-MIMO with hybrid feedback. Rather than finding an optimal transmission scheme, a suboptimal one is proposed such that the transmit directions of the BSs with CSI and CCI are eigen directions of the instantaneous channel correlation matrix and transmit covariance matrix respectively. The optimum power allocation for these transmit directions is derived as an iterative power allocation (IPA) similar to that of the MIMO multiple access channel (MAC) with CCI only. We also propose a simple disjoint power allocation (DPA). The simulation results show that the proposed transmit directions and IPA for the CSU-MIMO with hybrid feedback outperforms the MIMO-MAC with CCI only, while the DPA achieves almost the same performance as the IPA, only when the SNR is low.

This paper considers an optimized limited feedback design for a multi-antenna system serving multiple users under different types of channels: Rayleigh distributed and line-of-sight distributed channels. Since the users are asymmetric, we propose an optimized feedback bandwidth allocation scheme for users under a total feedback rate constraint. The allocation scheme is designed according to the long-term channel type information of users, and thus it can be efficiently implemented. Numerical results verify the effectiveness of our proposed scheme.

Precoding techniques can be introduced into relay systems due to the similarity between relay systems and traditional multi-input-multi-output (MIMO) systems. A channel state information feedback scheme is firstly presented for the MIMO relay system in this letter, where the zero-forcing relaying protocol is proposed to be used so that the information of the equivalent channel and the relaying noise can be compressed into two coefficients. With the proposed feedback scheme, the distributed precoding is presented to be applied through two continuous transmitted vectors of the source node while the co-channel interference cancellation equalizer is used in the destination node. The system outage probability can be improved with the precoding in the source node. Furthermore, various spatial data rates can be conveniently supported by the proposed distributed spatial-temporal precoding method.

In this letter, a closed form of the sum rate for multiple random beamforming is derived. A numerical evaluation verifies the tightness of the proposed solution to sample average of the sum rate.

This letter analyzes the outage probability of limited feedback beamforming systems with receive antenna selection. Tight analytical closed-form expressions of outage performance are derived for both cases, with and without spatial fading correlation, which allow for evaluation of the performance as a function of the codebook size, the level of fading correlation, and the number of transmit and receive antennas. Simulation results are also provided to verify the analysis.

Transmit beamforming can exploit the spatial diversity afforded by multiple-input multiple-output (MIMO) systems with low complexity. To apply this technique in more practical systems with the constraint of limited feedback, codebook based beamforming and vector quantization technique have been considered in various papers. On the other hand, multi-user scheduling is able to achieve another form of diversity arising from the independence of fading for different users, however, has not been fully taken into account in existing codebook based beamforming schemes. In this letter, a multi-codebook based beamforming and scheduling scheme is proposed, which exploits both spatial diversity and multi-user diversity by switching the codebook for different resource blocks. Meanwhile, the multi-codebook design issue is addressed, the corresponding theoretical analysis is provided, and the performance gain of proposed scheme is simulated. Furthermore, the impacts of related parameters on the performance gain are also investigated.

Recently, it has been shown in the literature that in a relaying network utilizing multiple relay precoding techniques, the signal-to-noise ratio (SNR) at each destination node will scale linearly with the number of relays K, which is referred to as the distributed array gain (DAG) K. In this paper, we focus on the performance of multiple relay precoding based on limited channel state information (CSI) feedback, which is different from the prior studies that assume perfect CSI at each of the relay nodes. Our analysis shows that the conventional limited feedback scheme fails to obtain the DAG K, which is a consequence of the phase ambiguity introduced by the channel quantization function. Based on the theoretical analysis, we propose a novel feedback and precoding procedure, and prove that the proposed procedure can obtain the DAG K with only one additional feedback bit for quantizing each relay-destination channel compared with the conventional scheme. Simulation results verify that with the proposed procedure, the SNR performance is effectively improved when the number of relays K is small, and scales linearly with K in relatively large K regime.

Prior studies on limited feedback (LFB) beamforming in multiple-antenna orthogonal frequency division multiplexing (OFDM) have resorted to Monte-Carlo simulations to evaluate the system performance. This letter proposes a novel analytical framework, based on which the averaged signal-to-noise ratio and the ergodic capacity performance of clustering-based LFB beamforming in multiple-antenna OFDM systems are studied. Simulations are also provided to verify the analysis.

In this letter, we analyze the performance of limited feedback beamforming in a distributed antenna system. We propose a novel codebook design scheme to maximize a lower bound of the averaged effective signal-to-noise ratio (SNR), which is a function of the power of the signal and noise, the number of antennas, and the number of total feedback bits for characterizing the quantized channel vector. Simulations verify that the proposed scheme can provide effective capacity improvement.

In this letter, we study the performance of the multiple-input multiple-output macrodiversity transmission with limited feedback. We modify the model of the quantized channel by Jindal [9] such that the phase ambiguity in the vector quantization procedure can be characterized. Using the modified model, we show that the conventional limited feedback methods cannot obtain the macrodiversity gain even with asymptotically large codebook size, and that the macrodiversity gain can be attained by adding only one bit of phase feedback.

Prior studies have shown that the performance of amplify-and-forward (AF) relay systems can be considerably improved by using multiple antennas and low complexity linear processing at the relay nodes. However, there is still a lack of performance analysis for the cases where the processing is based on limited feedback (LFB). Motivated by this, we derive the closed-form expression of the outage probability of AF relay systems with LFB beamforming in this letter. Simulation results are also provided to confirm the analytical studies.