An important challenge of wireless networks is to boost the cell edge performance and enable multi-stream transmissions to cell edge users. Interference mitigation techniques relying on multiple antennas and coordination among cells are nowadays heavily studied in the literature. Typical strategies in OFDMA networks include coordinated scheduling, beamforming and power control. In this paper, we propose a novel and practical type of coordination for OFDMA downlink networks relying on multiple antennas at the transmitter and the receiver. The transmission ranks, i.e. the number of transmitted streams, and the user scheduling in all cells are jointly optimized in order to maximize a network utility function accounting for fairness among users. A distributed coordinated scheduler motivated by an interference pricing mechanism and relying on a masterslave architecture is introduced. The proposed scheme is operated based on the user report of a recommended rank for the interfering cells accounting for the receiver interference suppression capability. It incurs a very low feedback and backhaul overhead and enables efficient link adaptation. It is moreover robust to channel measurement errors and applicable to both open-loop and closed-loop MIMO operations. A 20% cell edge performance gain over uncoordinated LTE-A system is shown through system level simulations.

Accurate channel direction information is essential to achieve considerable capacity gains in multiple-input multiple-output (MIMO) wireless communication systems. Limited feedback using a polar-cap differential codebook which utilizes the temporal correlation in multiple-input single-output (MISO) channels is presented in this paper. We first describe the general properties of the polar-cap differential codebook and then explain the design methodology of the size of the polar-cap given the temporal correlation coefficient. We also propose an enhancement of the polar-cap differential codebook which is suitable for a spatially correlated channel. We compare the polar-cap differential codebook with a rotation-based differential codebook in terms of the chordal distance to demonstrate the superiority of the polar-cap differential codebook. Monte Carlo simulation results show that the polar-cap differential codebook facilitates a significant performance gain in both temporally and spatially correlated channels.

An important challenge of wireless networks is to boost the cell edge performance and enable multi-streams transmissions to cell edge users. Interference mitigation techniques relying on multiple antennas and coordination among cells are nowadays heavily studied in the literature. In this paper, we propose a novel type of coordination for OFDMA networks relying on multiple antennas at the transmitter and the receiver where the transmission ranks, i.e. the number of transmitted streams, and the user scheduling in all cells are jointly optimized in order to maximize a network utility function accounting for fairness among users. A distributed coordinated scheduler relying on an interference pricing mechanism and a master-slave architecture is introduced. The proposed scheme is operated based on the user report of a recommended rank for the interfering cells. It incurs a very low feedback overhead and enables an efficient link adaptation. It is moreover robust to practical system impairments and is applicable to both open-loop and closed-loop MIMO operations. A cell edge performance gain of 20% over uncoordinated LTE-Advanced is shown through system level simulations.

We consider a system with precoding in the half duplex Decode-Forward (DF) relay networks, where multiple antennas are adopted at the source, the destination and the relay. Based on the channel state information (CSI), a few feedback bits are fed back from the destination to the source and the relay to select the source and the relay precoders. A suboptimal precoder selection criterion for the symbol vector error minimization and an optimal precoder selection criterion for the capacity maximization are proposed for the practical situation where relays are placed between the source and the destination. We analyze the diversity performance of the criteria and show that the full diversity is achieved when the rank one precoder sets span the vector channel space formed by the transmit antennas of the source and the those of the relay.

SU and MU-MIMO performance relies on accurate link adaptation in order to benefit from multi-user scheduling, beamforming, adaptive coding and modulation. Such accuracy highly depends on the type of the channel state information feedback. LTE-Advanced has defined two major types of feedback, i.e. implicit and explicit feedback. Implicit feedback makes some assumptions on the transmit precoding and receiver processing at the time of CSI and CQI feedback. The CSI is expressed in terms of a recommended precoder, commonly denoted as PMI. Explicit feedback refers to the feedback of channel information without making any assumption on the transmit and receiver processing. In this paper, we discuss pros and cons of such feedback mechanisms for both SU and MU-MIMO and compare performance of both approaches using system level simulations compliant with LTE-A system. It is shown that implicit feedback is the preferred feedback framework for both SU and MU-MIMO.

Multi-User (MU) Muliple Input-Multiple Output (MIMO) has become an essential technology to achieve IMT advanced requirements. Performance of limited feedback Multi-User MIMO in spatially and time correlated channels are investigated in this paper. A special attention is drawn to the case where users have the opportunity to adapt their codebooks as a function of their own channel statistics (i.e. transmit correlation, time correlation or channel imbalance in dual-polarized scenarios). New codebook designs are provided for various propagation conditions. We show by analytical derivations (e.g. sum-rate analysis) and confirm by simulations how those channel statistics can be efficiently exploited in the design of Multi-User MIMO schemes with very low feedback overhead and low complexity. Those approaches are currently strong candidates to boost performance of IEEE 802.16m way beyond IEEE 802.16e and 3GPP LTE.

We consider regularized channel inversion (RI) precoding in the multiuser multiple input multiple output (Mu-MIMO) broadcast channels. To make the RI operate in quantized channel feedback condition, we analyze the quantization error variance and its effect on the signal to interference plus noise power ratio (SINR) of the user signals. The regularization parameter ¿ is optimized to balance the additive noise, the multiuser interference and the interference due to the quantization error and to maximize SINR. Analysis and simulations show that regularization enhances the performance of zero forcing beam forming (ZFBF) over the whole signal to noise power ratio (SNR) range. This is contrasting to the perfect channel status information (CSI) case, where the enhancement is observed in the low SNR region.

Given a contraint on the total amount of feedback overhead, we investigate the allocation of feedback bits (i.e. codebook sizes) among users in a limited feedback Zero Forcing Beamforming-based MU-MIMO scheme where users have the opportunity to adapt their codebooks as a function of their own channel statistics. We consider both single-polarized and dual- polarized scenarios. Using upper bounds on the total rate loss incurred by quantization (previously derived by the authors), the optimal bit allocation strategy among users is derived as a function of the users channel statistics and SNR. Closed form solutions of the optimal bit allocation at low and high SNR are also derived. It is shown that in single-polarized scenarios (resp. dual-polarized scenarios) at high SNR it is beneficial to allocate more bits to users experiencing rank deficient transmit correlation matrices (resp. low cross-polarization discrimination XPD) than to users experiencing well conditioned correlation matrices (resp. large XPD), while an opposite allocation should be done at low SNR. Simulation results are shown to confirm analytical derivations.

We investigate the performance of limited feedback zero forcing beamforming-based MU-MIMO in correlated channels when users have the opportunity to adapt their codebooks as a function of their own channel statistics (CDIT). An upper bound on the rate loss is derived in terms of the amount of feedback and the statistics of the channel. In order to maintain a constant rate loss with respect to the perfect CSIT case, it is shown that the number of feedback bits should scale linearly with the SNR (in dB) with a slope proportional to the rank of the user transmit correlation matrix and logarithmically with the ratio of the second to the first largest eigenvalue of the transmit correlation matrix. Simulation results confirm analytical derivations and suggest that a channel statistics-based codebook is a reasonable simple approach to boost the throughput in correlated channels while incurring only a small overhead.

The impact of transmit correlation on the performance of limited feedback multi-user MIMO is investigated. Correlated fading is shown to highly influence the probability of scheduling orthogonal users and the ability to achieve small quantization errors. Correlated fading is indeed beneficial to MU- MIMO performance as it can potentially reduce the quantization error, if an appropriate codebook is used. Grassmanian line packing is very much inappropriate for MU-MIMO in correlated fading environments, while DFT-based codebooks and channel statistics-based codebooks are promising candidates. Additionally correlated fading is very beneficial to the scheduler. User correlation is shown to decrease more quickly in transmit correlated channels than in i.i.d. channels as the number of active users increases. However, correlated fading is also shown to be detrimental to the scheduler performance when the number of active users is rather small and cell sectorization is performed.