Abstract:
This paper proposes a linear interference alignment (IA) scheme which can be used for uplink channels in a general multicell multiuser MIMO cellular network. The proposed scheme aims to align interference caused by signals from a set of transmitters into a subspace which is established by the signals from only a subset of those transmitters, thereby effectively reducing the number of interfering transmitters. The total degrees of freedom (DoF) achievable by the proposed scheme is given in closed-form expression, and a numerical analysis shows that the proposed scheme can achieve the optimal DoF in certain scenarios and provides a higher total DoF than other related schemes in most cases.

Abstract:
In this paper, we consider the problem of power allocation in MIMO wiretap channel for secrecy in the presence of multiple eavesdroppers. Perfect knowledge of the destination channel state information (CSI) and only the statistical knowledge of the eavesdroppers CSI are assumed. We first consider the MIMO wiretap channel with Gaussian input. Using Jensen's inequality, we transform the secrecy rate max-min optimization problem to a single maximization problem. We use generalized singular value decomposition and transform the problem to a concave maximization problem which maximizes the sum secrecy rate of scalar wiretap channels subject to linear constraints on the transmit covariance matrix. We then consider the MIMO wiretap channel with finite-alphabet input. We show that the transmit covariance matrix obtained for the case of Gaussian input, when used in the MIMO wiretap channel with finite-alphabet input, can lead to zero secrecy rate at high transmit powers. We then propose a power allocation scheme with an additional power constraint which alleviates this secrecy rate loss problem, and gives non-zero secrecy rates at high transmit powers.

Abstract:
This paper investigates the sum-rate gains brought by power allocation strategies in multicell massive multipleinput multiple-output systems, assuming time-division duplex transmission. For both uplink and downlink, we derive tractable expressions for the achievable rate with zero-forcing receivers and precoders respectively. To avoid high complexity joint optimization across the network, we propose a scheduling mechanism for power allocation, where in a single time slot, only cells that do not interfere with each other adjust their transmit powers. Based on this, corresponding transmit power allocation strategies are derived, aimed at maximizing the sum rate per-cell. These schemes are shown to bring considerable gains over equal power allocation for practical antenna configurations (e.g., up to a few hundred). However, with fixed number of users (N), these gains diminish as M turns to infinity, and equal power allocation becomes optimal. A different conclusion is drawn for the case where both M and N grow large together, in which case: (i) improved rates are achieved as M grows with fixed M/N ratio, and (ii) the relative gains over the equal power allocation diminish as M/N grows. Moreover, we also provide applicable values of M/N under an acceptable power allocation gain threshold, which can be used as to determine when the proposed power allocation schemes yield appreciable gains, and when they do not. From the network point of view, the proposed scheduling approach can achieve almost the same performance as the joint power allocation after one scheduling round, with much reduced complexity.

Abstract:
We study the converse and achievability for the degrees of freedom of the multicellular multiple-input multiple-output (MIMO) multiple access channel (MAC) with constant channel coefficients. We assume L>1 homogeneous cells with K>0 users per cell where the users have M antennas and the base stations are equipped with N antennas. The degrees of freedom outer bound for this L-cell and K-user MIMO MAC is formulated. The characterized outer bound uses insight from a limit on the total degrees of freedom for the L-cell heterogeneous MIMO network. We also show through an example that a scheme selecting a transmitter and performing partial message sharing outperforms a multiple distributed transmission strategy in terms of the total degrees of freedom. Simple linear schemes attaining the outer bound (i.e., those achieving the optimal degrees of freedom) are explores for a few cases. The conditions for the required spatial dimensions attaining the optimal degrees of freedom are characterized in terms of K, L, and the number of transmit streams. The optimal degrees of freedom for the two-cell MIMO MAC are examined by using transmit zero forcing and null space interference alignment and subsequently, simple receive zero forcing is shown to provide the optimal degrees of freedom for L>1. Interestingly, it can be shown that the developed linear schemes characterize the optimal degrees of freedom with the minimum possible numbers of transmit and receive antennas when assuming a single stream per user. By the uplink and downlink duality, the degrees of freedom results in this paper are also applicable to the downlink. In the downlink scenario, we study the degrees of freedom of L-cell MIMO interference channel exploring multiuser diversity. Strong convergence modes of the instantaneous degrees of freedom as the number of users increases are characterized.

Abstract:
In this work, we study the problem of the optimal dissemination of channel state information (CSI) among K spatially distributed transmitters (TXs) jointly cooperating to serve K receivers (RXs). One of the particularities of this work lies in the fact that the CSI is distributed in the sense that each TX obtains its own estimate of the global multi-user MIMO channel with no further exchange of information being allowed between the TXs. Although this is well suited to model the cooperation between non-colocated TXs, e.g., in cellular Coordinated Multipoint (CoMP) schemes, this type of setting has received little attention so far in the information theoretic society. We study in this work what are the CSI requirements at every TX, as a function of the network geometry, to ensure that the maximal number of degrees-of-freedom (DoF) is achieved, i.e., the same DoF as obtained under perfect CSI at all TXs. We advocate the use of the generalized DoF to take into account the geometry of the network in the analysis. Consistent with the intuition, the derived DoF maximizing CSI allocation policy suggests that TX cooperation should be limited to a specific finite neighborhood around each TX. This is in sharp contrast with the conventional (uniform) CSI dissemination policy which induces CSI requirements that grow unbounded with the network size. The proposed CSI allocation policy suggests an alternative to clustering which overcomes fundamental limitations such as (i) edge interference and (ii) unbounded increase of the CSIT requirements with the cluster size. Finally, we show how finite neighborhood CSIT exchange translates into finite neighborhood message exchange so that finally global interference management is possible with only local cooperation

Abstract:
Training-based transmission over Rayleigh block-fading multiple-input multiple-output (MIMO) channels is investigated. As a training method a combination of a pilot-assisted scheme and a biased signaling scheme is considered. The achievable rates of successive decoding (SD) receivers based on the linear minimum mean-squared error (LMMSE) channel estimation are analyzed in the large-system limit, by using the replica method under the assumption of replica symmetry. It is shown that negligible pilot information is best in terms of the achievable rates of the SD receivers in the large-system limit. The obtained analytical formulas of the achievable rates can improve the existing lower bound on the capacity of the MIMO channel with no channel state information (CSI), derived by Hassibi and Hochwald, for all signal-to-noise ratios (SNRs). The comparison between the obtained bound and a high SNR approximation of the channel capacity, derived by Zheng and Tse, implies that the high SNR approximation is unreliable unless quite high SNR is considered. Energy efficiency in the low SNR regime is also investigated in terms of the power per information bit required for reliable communication. The required minimum power is shown to be achieved at a positive rate for the SD receiver with no CSI, whereas it is achieved in the zero-rate limit for the case of perfect CSI available at the receiver. Moreover, numerical simulations imply that the presented large-system analysis can provide a good approximation for not so large systems. The results in this paper imply that SD schemes can provide a significant performance gain in the low-to-moderate SNR regimes, compared to conventional receivers based on one-shot channel estimation.

Abstract:
Interference alignment (IA), given uncorrelated channel components and perfect channel state information, obtains the maximum degrees of freedom in an interference channel. Little is known, however, about how the sum rate of IA behaves at finite transmit power, with imperfect channel state information, or antenna correlation. This paper provides an approximate closed-form signal-to-interference-plus-noise-ratio (SINR) expression for IA over multiple-input-multiple-output (MIMO) channels with imperfect channel state information and transmit antenna correlation. Assuming linear processing at the transmitters and zero-forcing receivers, random matrix theory tools are utilized to derive an approximation for the post-processing SINR distribution of each stream for each user. Perfect channel knowledge and i.i.d. channel coefficients constitute special cases. This SINR distribution not only allows easy calculation of useful performance metrics like sum rate and symbol error rate, but also permits a realistic comparison of IA with other transmission techniques. More specifically, IA is compared with spatial multiplexing and beamforming and it is shown that IA may not be optimal for some performance criteria.

Abstract:
In this paper, we investigate methods for reducing the likelihood that a message transmitted between two multiantenna nodes is intercepted by an undetected eavesdropper. In particular, we focus on the judicious transmission of artificial interference to mask the desired signal at the time it is broadcast. Unlike previous work that assumes some prior knowledge of the eavesdropper's channel and focuses on maximizing secrecy capacity, we consider the case where no information regarding the eavesdropper is available, and we use signal-to-interference-plus-noise-ratio (SINR) as our performance metric. Specifically, we focus on the problem of maximizing the amount of power available to broadcast a jamming signal intended to hide the desired signal from a potential eavesdropper, while maintaining a prespecified SINR at the desired receiver. The jamming signal is designed to be orthogonal to the information signal when it reaches the desired receiver, assuming both the receiver and the eavesdropper employ optimal beamformers and possess exact channel state information (CSI). In practice, the assumption of perfect CSI at the transmitter is often difficult to justify. Therefore, we also study the resulting performance degradation due to the presence of imperfect CSI, and we present robust beamforming schemes that recover a large fraction of the performance in the perfect CSI case. Numerical simulations verify our analytical performance predictions, and illustrate the benefit of the robust beamforming schemes.

Abstract:
This paper re-examines the well-known fundamental tradeoffs between rate and reliability for the multi-antenna, block Rayleigh fading channel in the high signal to noise ratio (SNR) regime when (i) the transmitter has access to (noiseless) one bit per coherence-interval of causal channel state information (CSI) and (ii) soft decoding delays together with worst-case delay guarantees are acceptable. A key finding of this work is that substantial improvements in reliability can be realized with a very short expected delay and a slightly longer (but bounded) worst-case decoding delay guarantee in communication systems where the transmitter has access to even one bit per coherence interval of causal CSI. While similar in spirit to the recent work on communication systems based on automatic repeat requests (ARQ) where decoding failure is known at the transmitter and leads to re-transmission, here transmit side-information is purely based on CSI. The findings reported here also lend further support to an emerging understanding that decoding delay (related to throughput) and codeword blocklength (related to coding complexity and delays) are distinctly different design parameters which can be tuned to control reliability.

Abstract:
Time Reversal (TR) technique is an attractive solution for a scenario where the transmission system employs low complexity receivers with multiple antennas at both transmitter and receiver sides. The TR technique can be combined with a high data rate MIMO-UWB system as TR-MIMO-UWB system. In spite of TR's good performance in MIMO-UWB systems, it suffers from performance degradation in an imperfect Channel State Information (CSI) case. In this paper, at first a robust TR pre-filter is designed together with a MMSE equalizer in TR-MIMO-UWB system where is robust against channel imperfection conditions. We show that the robust pre-filter optimization technique, considerably improves the BER performance of TR-MIMO-UWB system in imperfect CSI, where temporal focusing of the TR technique is kept, especially for high SNR values. Then, in order to improve the system performance more than ever, a power loading scheme is developed by minimizing the average symbol error rate in an imperfect CSI. Numerical and simulation results are presented to confirm the performance advantage attained by the proposed robust optimization and power loading in an imperfect CSI scenario.