Low complexity multiuser MIMO scheduling with chordal distance

The sum capacity of a Gaussian broadcast MIMO channel can be achieved with dirty paper coding (DPC). However, algorithms that approach the DPC sum capacity do not appear viable in the forseeable future, which motivates lower complexity interference suppression techniques. Block diagonalization (BD) is a linear preceding technique for downlink multiuser MIMO systems. With perfect channel knowledge at the transmitter, BD can eliminate other users' interference at each receiver. In this paper, we study the sum capacity of BD with and without receive antenna selection. We analytically compare BD without receive antenna selection to DPC for a set of given channels. It is shown that (1) if the user channels are orthogonal to each other, then BD achieves the same sum capacity as DPC; (2) if the user channels lie in the same subspace, then the gain of DPC over BD can be upper bounded by the minimum of the number of transmit and receive antennas. These observations also hold for BD with receive antenna selection. Further, we study the ergodic sum capacity of BD with and without receive antenna selection in a Rayleigh fading channel. Simulations show that BD can achieve a significant part of the total throughput of DPC. An upper bound on the ergodic sum capacity gain of DPC over BD is proposed for easy estimation of the gap between the sum capacity of DPC and BD without receive antenna selection.

In this paper, an undesired fact for multiuser (MU) MIMO (MU-MIMO) systems using block diagonalization is presented, i.e., the increment of user number (K) results in the degradation of sum rate. This fact is caused by the opposition between two main factors determining the sum rate, namely, MU gain and transmit diversity. The MU gain guarantees a high order of degrees of freedom (DoFs) on system level but decreases the rate per user, while, for the transmit diversity, it is exactly opposite. Therefore, the tradeoff between the two factors is established to quantify how the two factors impact on the sum rate. Based on the tradeoff, the optimal K that maximizes the sum rate is further obtained. Additionally, it is pointed out that the sum rate can be improved substantially by only adding a few antennas at the base station when the system is fully loaded. The derivations are under large-scale system assumption, and being implemented on different precoders. Numerical simulations verify the tightness and accuracy of our asymptotic results for both large-scale and conventional systems.

In multiuser MIMO uplink, different pairs of transmitter and receiver may have different time delays and carrier frequency offsets (CFOs). This causes the time delay and CFO estimations much more difficult than those for a single input single output (SISO) system. It is a challenging problem to resolve the time delays and CFOs in the MIMO uplink. In this paper, an asynchronous multiuser MIMO system with multipath channels and CFOs is remodeled into another system. A blind method based on second order statistics is then used for estimating the shaped channels with ambiguity. Based on the shaped channels, specially designed pilots are proposed to find the CFOs. The same pilots are also used for resolving the time delays and the ambiguity in the estimated channels. Only upper bounds for the channel orders and time delays are needed for implementing the algorithms, which makes them applicable to practical multiuser MIMO systems.

Among the linear precoding techniques block diagonalization (BD) based schemes are well-known transmit strategies employed in the downlink of multiuser MIMO (MUMIMO) systems. Employing BD type precoding algorithms at the transmit side suppresses multi-user interference (MUI) by converting a MU-MIMO broadcast channel into multiple single-user MIMO (SU-MIMO) channels and then decomposing the SU-MIMO channels into multiple independent parallel sub-channels. Substantial work has been done in designing linear precoding algorithms. However, the use of these techniques in the implementation of WLAN standards is an open question. In this paper both the traditional as well as the recent techniques for precoding are investigated and schemes proposed for their implementation in the framework of 802.11ac WLAN standard.

Block diagonalization (BD) as a low complexity MIMO technique has been considered for inter-cell interference mitigation based on the perfect channel state information (CSI) in many previous works. However, the imperfect CSI feedback is more practical and beneficial for lower complexity in real situation. Thus, in this paper, the performance of BD for inter-cell interference mitigation is investigated under the constraint of imperfect CSI feedback. Simulation results demonstrated that BD algorithm still can work efficiently with limited feedback for the inter-cell interference cancellation.

In this paper, a comprehensive comparison analysis in terms of outage probability and average symbol error ratio (SER) is presented for cooperative cognitive multiple-input and multiple-output (CC-MIMO) multiuser systems with amplify-and-forward (AF) protocol. Specially, we consider two scenarios where the CC-MIMO multiuser systems have the perfect and imperfect channel state information (CSI). The CC-MIMO multiuser systems consist of one multi-antenna source, one single-antenna relay, and multiple multi-antenna destinations. At the secondary source and destinations, the maximal ratio transmission (MRT) and maximal ratio combining (MRC) are employed, respectively. For such CC-MIMO multiuser systems, we first obtain the exact closed-form expressions of outage probability under the two cases where the CC-MIMO multiuser systems have the perfect and imperfect CSI. Then, to reduce the implementation complexity, the tight lower bounds of outage probability and average SER are derived. Finally, to obtain insight, by using the high signal-to-noise ratio (SNR) approximation, the asymptotic estimations of outage probability are achieved. The numerical results show that the derivations are agreed with the simulations, which validate our derivations. At the same time, the results show that, for the systems without perfect CSI, the achievable diversity order reduces to one, regardless of the number of antennas at the cognitive source and destinations as well as the number of the cognitive destinations. Nevertheless, these key parameters affect the coding gain of the CC-MIMO multiuser systems. When the systems have the perfect CSI (or without feedback delay), the achievable diversity gain is determined by the minimum between the number of source’s antennas and the product of the number of destinations and the number of destination’s antennas. For the effect of PU’s parameters, our results indicate that primary systems only affect the coding gain but not the diversity gain.

For the poor transmission reliability of data, this paper focuses on the precoding techniques of the multi-user MIMO system in the broadcast phase in, and the single-user MIMO and multi-user MIMO precoding techniques have been studied. In the multi-user MIMO system, BD-MMSE-VP coding algorithm is proposed to improve the BER performance of the system by using the MMSE criterion to optimize the perturbation vector, and the system uses QR technique to decompose BD channel matrix. Simulation results verify the effective of the proposed precoding algorithm.

It is well known that accurate direction of arrival (DOA) estimation can help to improve the performance of MIMO systems. However, when large scale MIMO systems are considered, the DOA estimation becomes very difficult due to the large dimension of DOAs. Based on the observation that correlation exists between the neighboring antennas due to the limited size of the antenna array, we propose a correlation based DOA estimation method for the large scale multi-user (MU) MIMO system in this paper. It is verified that the proposed DOA estimation method can obtain a better performance than the existing methods with a much lower computational complexity.

The design procedure of hybrid beamforming is investigated considering multi-user MIMO communication systems taking into account the number of independent data streams for each user. Hybrid precoding and combining are utilized at the transmitter and receiver sides of millimeter-wave multi-user massive MIMO. The obtained results indicate the trade-off in performance based on the ratio of the number of antennas to the number of data streams at the transmitter as well as the receiver. The optimization of the number of parallel data streams per user allows the increase of transmitted data rate while keeping the levels of error vector magnitude (EVM) at acceptable levels.

The capacity of frequency-flat multiuser MIMO downlinks is achieved with nonlinear dirty paper coding (DPC). Linear processing techniques, such as block diagonalization (BD), offer relatively low computational cost with respect to DPC and can also achieve capacity in certain cases. However, BD is not easily translated to frequency-selective channels since the channel matrix has a space-time structure (unlike the space-only information in frequency-flat channels), which induces an additional inter-symbol interference (ISI) component in the received signal. In this paper, we demonstrate that BD is feasible in frequency- selective channels when the transmitted block length is sufficiently large and the number of transmit antennas is greater than or equal to the number of users. We also present three novel techniques based on BD for frequency-selective MU- MIMO systems: time-reversal-based BD (TRBD), equalized BD (EBD), and joint processing BD (JPBD). These techniques use perfect channel state information at the transmitter (and also at the receiver, in the case of JPBD) to mitigate or eliminate both ISI and inter-user interference. We demonstrate that TRBD and EBD yield zero multiplexing gain (high SNR regime) but perform well under low SNR, while JPBD has a multiplexing gain approximately equal to the number of users for a sufficiently large transmit block length. Extensive numerical simulations show that the achievable rate performance of the proposed techniques improves that of time-reversal beamforming, a common technique for frequency- selective MU-MIMO downlinks.

The user selection method based on chordal distance is widely used in multiuser multiple‐input multiple‐output (MU‐MIMO) systems with block diagonalisation. It has throughput close to the capacity based method with low complexity. In this Letter, a user selection method with higher throughput and much lower complexity is proposed. To investigate the performance in a more practical channel scenario, 3D MIMO channels are used in simulations. Compared with existing user selection algorithms, the proposed method achieves good throughput performance and the lowest complexity order.

The diversity-multiplexing tradeoff has become a powerful tool to analyze MIMO fading channels. In this paper, we first derive the diversity-multiplexing tradeoff for the case that the transmitter and receiver are connected by multiple parallel and independent MIMO channels, each of which may be utilized for some limiting fraction of the total time. Our main result in this respect is an elegant geometric characterization of the tradeoff curve in terms of the Zheng-Tse tradeoff for a single MIMO channel. We then apply this result to compute bounds on the DMT for a three phase bi-directional cooperation (or two-way relay) protocol. These bounds are shown to be tight in the case of single antenna nodes and the optimal relative time duration of each phase that maximizes the diversity of the end-users is determined. The DMT derived here may also be of importance to problems where a node can be seen to receive information over channels that can be decomposed into parallel independent components, which is often the case in protocols for half-duplex cooperative networks.

The combination of millimeter wave (mmW) with massive MIMO is a promising approach to achieve the multi Gb/s required by future wireless systems. Fully digital architectures are not feasible due to hardware limitations, and thus, the design of signal processing techniques for hybrid analog-digital architectures is of paramount importance. In this paper, we propose a new hybrid iterative block space-time receiver structure for multiuser mmW massive MIMO systems. We consider low-complexity user terminals employing analog-only random precoding and a single RF chain. At the base station, a hybrid analog-digital equalizer/detector is designed to efficiently remove the multiuser interference. The analog and digital parts of the equalizer are jointly optimized using as a metric the average bit-error-rate. The specificities of the analog domain impose several constraints in the joint optimization. To efficiently handle these constraints, the analog part is selected from a dictionary based on the array response vectors. We also propose a simple, yet an accurate semi-analytical approach for obtaining the performance of the proposed hybrid receiver structure. The results show that the performance of the hybrid iterative equalizer is close to the fully digital counterpart after only a few iterations. Moreover, it clearly outperforms the linear receivers recently considered for hybrid mmW massive MIMO architectures.

Hybrid precoding has been recognized as a promising technology for millimeter wave-based massive MIMO systems. As an improved scheme for conventional hybrid precoding structures, the adaptively-connected structure requires low hardware cost and has attractive system performance. In this paper, we propose an adaptive hybrid precoding (AHP) scheme for multi-user massive MIMO systems. The hybrid precoder design is formulated as minimizing the difference between the hybrid precoder and the full digital precoder, and a rough design and revision based AHP (RDR-AHP) algorithm is developed to seek for a near-optimal solution. The proposed RDR-AHP algorithm is achieved by a three-step process including rough design of baseband precoder based on singular value unification, stepwise design of radio frequency precoder and baseband precoder revision. Simulation results demonstrate that the proposed scheme achieves higher spectral efficiency than existing schemes with same hardware cost in millimeter wave channel.

To fully utilize the spatial multiplexing gains or array gains of massive MIMO, the channel state information must be obtained at the transmitter side (CSIT). However, conventional CSIT estimation approaches are not suitable for FDD massive MIMO systems because of the overwhelming training and feedback overhead. In this paper, we consider multi-user massive MIMO systems and deploy the compressive sensing (CS) technique to reduce the training as well as the feedback overhead in the CSIT estimation. The multi-user massive MIMO systems exhibits a hidden joint sparsity structure in the user channel matrices due to the shared local scatterers in the physical propagation environment. As such, instead of naively applying the conventional CS to the CSIT estimation, we propose a distributed compressive CSIT estimation scheme so that the compressed measurements are observed at the users locally, while the CSIT recovery is performed at the base station jointly. A joint orthogonal matching pursuit recovery algorithm is proposed to perform the CSIT recovery, with the capability of exploiting the hidden joint sparsity in the user channel matrices. We analyze the obtained CSIT quality in terms of the normalized mean absolute error, and through the closed-form expressions, we obtain simple insights into how the joint channel sparsity can be exploited to improve the CSIT recovery performance.