Delay aware optimal resource allocation in MU MIMO-OFDM using enhanced spider monkey optimization

In multiple users MIMO- OFDM system allocates the available resources to the optimal users is a difficult task. Hence the scheduling and resource allocation become the major problem in the wireless network mainly in case of multiple input and multiple output method that has to be made efficient. There is various method introduced to give an optimal solution to the problem yet it has many drawbacks. So we propose this paper to provide an efficient solution for resource allocation in terms of delay and also added some more features such as high throughout, energy efficient and fairness. To make optimal resource allocation we introduce optimization algorithm named spider monkey with an enhancement which provides the efficient solution. In this optimization process includes the scheduling and resource allocation, the SNR values, channel state information (CSI) from the base station. To make more efficient finally we perform enhanced spider - monkey algorithm hence the resource allocation is performed based on QoS requirements. Thus the simulation results in our paper show high efficiency when compared with other schedulers and techniques

D3.2 First performance results for multi -node/multi -antenna transmission technologies

This deliverable describes the current results of the multi-node/multi-antenna technologies investigated within METIS and analyses the interactions within and outside Work Package 3. Furthermore, it identifies the most promising technologies based on the current state of obtained results. This document provides a brief overview of the results in its first part. The second part, namely the Appendix, further details the results, describes the simulation alignment efforts conducted in the Work Package and the interaction of the Test Cases. The results described here show that the investigations conducted in Work Package 3 are maturing resulting in valuable innovative solutions for future 5G systems.Fantini. R.; Santos, A.; De Carvalho, E.; Rajatheva, N.; Popovski, P.; Baracca, P.; Aziz, D.... (2014). D3.2 First performance results for multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675

Modeling and Compensation of Transceiver Non-Reciprocity in TDD Multi-Antenna Base-Station

Due to the increasing demands for higher system capacity, higher data rates and better quality of service in wireless networks, advanced techniques that improve wireless link reliability and spectral efficiency are introduced. This includes different multi-antenna technologies, in particular multi-user (MU) MIMO-OFDM. In MU MIMO-OFDM systems, base-station with multiple antennas communicates simultaneously with multiple users over a given time-frequency resource. In downlink transmission, base-station transmits multiple data streams through its antennas towards the user devices. In uplink transmission, the user equipment send in parallel multiple data streams towards the base-station. In general, channel non-reciprocity is a very important factor in cellular communications, in particular in precoded MU MIMO-OFDM systems adopting time division duplexing (TDD). Based on the channel reciprocity principle, the channel state information at base-station for the downlink transmission can be determined through estimating the uplink channels. In practice, however, there are always unavoidable frequency mismatch characteristics between transmitter and receiver. Frequency response mismatch can thus change the reciprocal nature of downlink and uplink channels. The impact of transceiver non-reciprocity at equipment on user side causes inter-stream interference which can be compensated using detection processing. The impact of transceiver non-reciprocity at base-station causes inter-user interference and degrades the system performance of MU MIMO-OFDM systems. To ensure the system reliability and high performance in case of transceiver non-reciprocity, some non-reciprocity estimation and compensation methods are required. The previous work has proposed the estimation-compensation framework that gives a flexible solution to restore the channel reciprocity. But there is a need to validate the findings and performance of the proposed estimation-compensation framework. The modeling of transceiver frequency response mismatch characteristics using actual measurement data has been carried out in this thesis research work. The actual measurement data comprises of one base-station with two antennas and two user equipment devices with single antenna. The estimated uplink and downlink channels from measurement data are used to compute the non-reciprocity matrix at base-station and at the equipment on user side after mathematical calculations. The normalized parameters for transceiver non-reciprocity matrices are extracted subcarrier-wise. The frequency-domain normalized non-reciprocity parameters are modeled as a FIR filter in the time-domain and the most energy concentrates then on few time-domain taps. The extracted parameters are mildly frequency-selective. The impact of extracted transceiver non-reciprocity is then analyzed by implementing a simulator of TDD precoded MU MIMO-OFDM system. In general, the frequency-selectivity implies that the reciprocity estimation and compensation is needed subcarrier-wise. The pilot-based estimation of non-reciprocity parameters at base-station is carried out in order to enhance the system performance. To estimate channel non-reciprocity parameters, a link between base-station and one of user equipment devices is assumed. The right choice of selecting the user is also important for noise reduction in estimation. For estimation, the DL transmission channel is modeled as a Rayleigh fading multipath channel with a given 7-tap channel power delay profile. The downlink data including sparsely located pilots at selected subcarriers is transmitted to the user through downlink channel without precoding. The downlink channel is then estimated at the user equipment side. This provides estimates only at the pilot subcarriers. Therefore, linear interpolation is used to obtain channel response estimates at the actual data subcarriers. The uplink pilot data is transmitted to base-station from user equipment through uplink channel. The uplink channel is obtained by estimated downlink channel in case of non-reciprocity parameters. Then, estimate of non-reciprocity at base-station is computed by using inverse processing and an interpolator. The estimated parameters are used as a compensator filter in order to compensate the channel non-reciprocity in the system. The simulated results show that the performance deviates from the ideal linear precoded MU MIMO-OFDM system because of non-reciprocity in case of both error control coded and uncoded channels. The compensated results in terms of coded and uncoded channel schemes have been evaluated which are closer to ideal linear precoded MU-MIMO OFDM system. These results show that the impact of non-reciprocity on system performance is less severe when a coded channel is deployed as compared to uncoded channel. The modeling of transceiver frequency response mismatch characteristics using actual measurement data proves that the proposed non-reciprocity model in the previous research work is close to reality

Channel estimation in massive MIMO systems

Last years were characterized by a great demand for high data throughput, good quality and spectral efficiency in wireless communication systems. Consequently, a revolution in cellular networks has been set in motion towards to 5G. Massive multiple-input multiple-output (MIMO) is one of the new concepts in 5G and the idea is to scale up the known MIMO systems in unprecedented proportions, by deploying hundreds of antennas at base stations. Although, perfect channel knowledge is crucial in these systems for user and data stream separation in order to cancel interference. The most common way to estimate the channel is based on pilots. However, problems such as interference and pilot contamination (PC) can arise due to the multiplicity of channels in the wireless link. Therefore, it is crucial to define techniques for channel estimation that together with pilot contamination mitigation allow best system performance and at same time low complexity. This work introduces a low-complexity channel estimation technique based on Zadoff-Chu training sequences. In addition, different approaches were studied towards pilot contamination mitigation and low complexity schemes, with resort to iterative channel estimation methods, semi-blind subspace tracking techniques and matrix inversion substitutes. System performance simulations were performed for the several proposed techniques in order to identify the best tradeoff between complexity, spectral efficiency and system performance

D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies

This document provides the most recent updates on the technical contributions and research challenges focused in WP3. Each Technology Component (TeC) has been evaluated under possible uniform assessment framework of WP3 which is based on the simulation guidelines of WP6. The performance assessment is supported by the simulation results which are in their mature and stable state. An update on the Most Promising Technology Approaches (MPTAs) and their associated TeCs is the main focus of this document. Based on the input of all the TeCs in WP3, a consolidated view of WP3 on the role of multinode/multi-antenna transmission technologies in 5G systems has also been provided. This consolidated view is further supported in this document by the presentation of the impact of MPTAs on METIS scenarios and the addressed METIS goals.Aziz, D.; Baracca, P.; De Carvalho, E.; Fantini, R.; Rajatheva, N.; Popovski, P.; Sørensen, JH.... (2015). D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675

Limited feedback MIMO techniques for temporally correlated channels and linear receivers

Advanced mobile wireless networks will make extensive use of multiantenna (MIMO) transceivers to comply with high requirements of data rates and reliability. The use of feedback channels is of paramount importance to achieve this goal in systems employing frequency division duplexing (FDD). The design of the feedback mechanism is challenging due to the severe constraints imposed by computational complexity and feedback bandwidth restrictions. This thesis addresses the design of transmission strategies in both single-user and multi-user MIMO systems, based on compact feedback messages. First, recursive feedback mechanisms for single-user transmission scenarios are proposed, including stochastic gradient techniques, deterministic updates based on Givens rotations and low computational complexity schemes based on partial update filtering concepts. Thereafter, channel feedback algorithms are proposed, and a convergence analysis for static channels is presented. These algorithms can be used to provide channel side information to any multi-user MIMO solution. A limited-feedback decentralized multi-user MIMO solution is proposed, which avoids the need for explicit channel feedback. A feed-forward technique is proposed, which allows our methods to operate in presence of feedback errors. The performance of all the proposed algorithms is illustrated via link-level simulations, where the effect of different parameter values is assessed. Our results show that the proposed methods outperform existing limited-feedback counterparts over a range of low to medium mobile speeds, for moderate antenna array sizes that are deemed practical for commercial deployment. The computational complexity reduction of some of the proposed algorithms is also shown to be considerable, when compared to existing techniques