Limited Feedback-based Block Diagonalization for the MIMO Broadcast Channel

Block diagonalization is a linear precoding technique for the multiple antenna broadcast (downlink) channel that involves transmission of multiple data streams to each receiver such that no multi-user interference is experienced at any of the receivers. This low-complexity scheme operates only a few dB away from capacity but requires very accurate channel knowledge at the transmitter. We consider a limited feedback system where each receiver knows its channel perfectly, but the transmitter is only provided with a finite number of channel feedback bits from each receiver. Using a random quantization argument, we quantify the throughput loss due to imperfect channel knowledge as a function of the feedback level. The quality of channel knowledge must improve proportional to the SNR in order to prevent interference-limitations, and we show that scaling the number of feedback bits linearly with the system SNR is sufficient to maintain a bounded rate loss. Finally, we compare our quantization strategy to an analog feedback scheme and show the superiority of quantized feedback.Comment: 20 pages, 4 figures, submitted to IEEE JSAC November 200

Achievable throughput with Block Diagonalization on OFDM indoor demonstrator

The proceeding at: 21st European Signal Processing Conference (EUSIPCO 2013), took place 2013, September 09-13, in Marrakech, Septiembre 2013.Block Diagonalization (BD) is a linear precoding transmission technique able to achieve full multiplexing gain in multiple antenna systems. In this work we present a Multiple-Input Multiple-Output (MIMO) implementation based on Orthogonal Frequency Division Multiplexing (OFDM) made up of a transmitter with 4 antennas and 2 users equipped with 2 antennas each one, which allows us to evaluate the performance of BD in indoor scenarios. First, the theoretic achievable rates are obtained for the measured channel in an offline evaluation. After that, the bit error rate performance is evaluated regarding the system sum throughput. To the best of our knowledge, this is the first time that BD performance is validated using a multiuser MIMO testbed.This work has been partially funded by research projects COMONSENS (CSD2008-000 1 0), and GRE3N (TEC20 11-29006-C03-02).Publicad

Group Sparse Precoding for Cloud-RAN with Multiple User Antennas

Cloud radio access network (C-RAN) has become a promising network architecture to support the massive data traffic in the next generation cellular networks. In a C-RAN, a massive number of low-cost remote antenna ports (RAPs) are connected to a single baseband unit (BBU) pool via high-speed low-latency fronthaul links, which enables efficient resource allocation and interference management. As the RAPs are geographically distributed, the group sparse beamforming schemes attracts extensive studies, where a subset of RAPs is assigned to be active and a high spectral efficiency can be achieved. However, most studies assumes that each user is equipped with a single antenna. How to design the group sparse precoder for the multiple antenna users remains little understood, as it requires the joint optimization of the mutual coupling transmit and receive beamformers. This paper formulates an optimal joint RAP selection and precoding design problem in a C-RAN with multiple antennas at each user. Specifically, we assume a fixed transmit power constraint for each RAP, and investigate the optimal tradeoff between the sum rate and the number of active RAPs. Motivated by the compressive sensing theory, this paper formulates the group sparse precoding problem by inducing the $\ell_0$-norm as a penalty and then uses the reweighted $\ell_1$ heuristic to find a solution. By adopting the idea of block diagonalization precoding, the problem can be formulated as a convex optimization, and an efficient algorithm is proposed based on its Lagrangian dual. Simulation results verify that our proposed algorithm can achieve almost the same sum rate as that obtained from exhaustive search

Cooperative Precoding with Limited Feedback for MIMO Interference Channels

Multi-antenna precoding effectively mitigates the interference in wireless networks. However, the resultant performance gains can be significantly compromised in practice if the precoder design fails to account for the inaccuracy in the channel state information (CSI) feedback. This paper addresses this issue by considering finite-rate CSI feedback from receivers to their interfering transmitters in the two-user multiple-input-multiple-output (MIMO) interference channel, called cooperative feedback, and proposing a systematic method for designing transceivers comprising linear precoders and equalizers. Specifically, each precoder/equalizer is decomposed into inner and outer components for nulling the cross-link interference and achieving array gain, respectively. The inner precoders/equalizers are further optimized to suppress the residual interference resulting from finite-rate cooperative feedback. Further- more, the residual interference is regulated by additional scalar cooperative feedback signals that are designed to control transmission power using different criteria including fixed interference margin and maximum sum throughput. Finally, the required number of cooperative precoder feedback bits is derived for limiting the throughput loss due to precoder quantization.Comment: 23 pages; 5 figures; this work was presented in part at Asilomar 2011 and will appear in IEEE Trans. on Wireless Com

Multiuser Diversity for Secrecy Communications Using Opportunistic Jammer Selection -- Secure DoF and Jammer Scaling Law

In this paper, we propose opportunistic jammer selection in a wireless security system for increasing the secure degrees of freedom (DoF) between a transmitter and a legitimate receiver (say, Alice and Bob). There is a jammer group consisting of $S$ jammers among which Bob selects $K$ jammers. The selected jammers transmit independent and identically distributed Gaussian signals to hinder the eavesdropper (Eve). Since the channels of Bob and Eve are independent, we can select the jammers whose jamming channels are aligned at Bob, but not at Eve. As a result, Eve cannot obtain any DoF unless it has more than $KN_j$ receive antennas, where $N_j$ is the number of jammer's transmit antenna each, and hence $KN_j$ can be regarded as defensible dimensions against Eve. For the jamming signal alignment at Bob, we propose two opportunistic jammer selection schemes and find the scaling law of the required number of jammers for target secure DoF by a geometrical interpretation of the received signals.Comment: Accepted with minor revisions, IEEE Trans. on Signal Processin

On channel quantization for multi-cell cooperative systems with limited feedback

Coherent multi-cell cooperative transmission, also referred to as coordinated multi-point transmission (CoMP), is a promising strategy to provide high spectral efficiency for universal frequency reuse cellular systems. To report the required channel information to the transmitter in frequency division duplexing systems, limited feedback techniques are often applied. Considering that the average channel gains from multiple base stations (BSs) to one mobile station are different and the number of cooperative BSs may be dynamic, it is neither flexible nor compatible to employ a large codebook to directly quantize the CoMP channel. In this paper, we employ per-cell codebooks for quantizing local and cross channels. We first propose a codeword selection criterion, aiming at maximizing an estimated data rate for each user. The proposed criterion can be applied for an arbitrary number of receive antennas at each user and also for an arbitrary number of data streams transmitted to each user. Considering that the resulting optimal per-cell codeword selection for CoMP channel is of high complexity, we propose a serial codeword selection method that has low complexity but yields comparable performance to that of the optimal codeword selection. We evaluate the proposed codeword selection criterion and method using measured CoMP channels from an urban environment as well as simulations. The results demonstrate significant performance gain as compared to an existing low-complexity method