This paper deals with IQ imbalance in wideband MIMO OFDM systems. In systems with a large bandwidth, the IQ imbalance will be frequency-dependent and hence cannot be described by a single parameter. Furthermore if there is a carrier-frequency offset (CFO), the IQ imbalance estimation in a MIMO system becomes a challenging task. However the CFO introduces a time-varying component to the received signal which can be exploited to estimate the model parameters using a carefully designed training sequence. This approach obtains the TX and RX IQ imbalance separately in an accurate fashion. We verify this by simulations and also show the estimated IQ imbalance in a customised hardware prototype.

Considerable research efforts have been made into 5G systems, in which wireless backhaul plays a key part. This paper presents a novel E-band testbed for 5G backhaul applications with wideband IQ imbalance compensation. It is based on OFDM to compensate the effect of wideband channel distortions as well as RF impairments. Moreover, line-of-sight polarization MIMO with two orthogonal polarizations is applied to enhance the data rate, which in combination with OFDM results in a simple equalization approach. In this testbed, carrier frequency offset and Tx/Rx IQ imbalance are jointly estimated and compensated. We describe how the testbed was designed. Then, we apply the IQ imbalance compensation and demonstrate that a data rate of 20 Gbps can be achieved in an actual outdoor environment distances of 900 m.

This paper deals with IQ imbalance in wideband MIMO OFDM systems. In systems with a large bandwidth, the IQ imbalance will be frequency-dependent and hence can not be described by a single parameter. Furthermore if there is a carrier-frequency offset (CFO), the IQ imbalance estimation in a MIMO system with multiple channels becomes a challenging task. However the CFO introduces a time-varying component to the received signal which we exploit to estimate the model parameters using a carefully designed training sequence. This approach derives the TX and RX IQ imbalance separately in an accurate fashion. We verify this by simulations and also show the estimated IQ imbalance in a hardware prototype we have built.

We consider a single-source, multiple-relay, and single-destination lossy network employing random linear network coding at all transmitting nodes. We address the problem of calculating the probability of successful decoding at the destination node. In contrast to some previous studies, we assume the classical random linear network coding scheme, in which the relaying nodes simply recode packets, without resorting to decoding. In addition, we consider an arbitrary field size and take into account the correlation between the relay nodes. We propose a novel upper bound for an arbitrary number of relays, which becomes exact for a single relay. Using Monte Carlo simulations, we show that the proposed bound is very accurate, exhibiting the mean square error as low as 10-6. We also demonstrate the throughput gain of the proposed scheme over alternative coding and relaying strategies.

We consider a lossy multicast network in which the reliability is provided by means of random linear network coding. Our goal is to characterize the performance of such network in terms of the probability that a source message is delivered to all destination nodes. Previous studies considered coding over large finite fields, small numbers of destination nodes or specific, often impractical, channel conditions. In contrast, we focus on a general problem, considering arbitrary field size and number of destination nodes, and a realistic channel. We propose a lower bound on the probability of successful delivery, which is more accurate than the approximation commonly used in the literature. In addition, we present a novel performance analysis of the systematic version of RLNC. The accuracy of the proposed performance framework is verified via extensive Monte Carlo simulations, where the impact of the network and code parameters are investigated. Specifically, we show that the mean square error of the bound for a ten-user network can be as low as 9 · 10-5for non-systematic RLNC.

Orthogonal Frequency Division Multiplexing based M-ary Frequency Shift Keying (OFDM-MFSK) is a non- coherent modulation scheme that was proposed for robust transmission over fast fading environments. It combines the MFSK modulation scheme with OFDM. In this paper, the Generalised Frequency Division Multiplexing (GFDM) waveform is considered to use with MFSK to take the advantages of the low out of band radiation and relaxed synchronisation requirements. Different methods to combine MFSK and GFDM are proposed and their performances are evaluated and compared with OFDM-MFSK. The mixed sub-carrier and sub-symbol method, which is one of the proposed methods, is the most promising technique. Additionally, gain margin is also seen for MFSK modulation scheme compared to ordinary OFDM or GFDM. This gain can be used to radically improve the performance for some 5G applications, such as IoT, at low Signal to Noise Ratio (SNR) values.

In this paper, error correction is introduced to the Bluetooth low energy and IEEE 802.15.4 standards by utilizing data redundancy provided by cyclic redundancy check (CRC) codes used by both protocols to detect erroneous packets. A scenario with an energy-constrained transmitter and a constraint-free infrastructure is assumed that enables additional signal processing at the receiving side, keeping the transmitter intact. CRC error correction is achieved using a novel approach of applying iterative decoding techniques. The proposed methods are evaluated based both on simulated and real packets. It is shown that by enabling CRC error correction, up to 2.5 dB of the signal to noise ratio gain can be achieved, while up to 35% of real corrupted packets can be corrected, at no extra cost for the transmitter. This results in potential range extension and longer battery life caused by a reduced number of retransmissions.

In this paper, we analyze the performance of a single-relay network in which the reliability is provided by means of Random Linear Network Coding (RLNC). We consider a scenario when both source and relay nodes can encode packets. Unlike the traditional approach to relay networks, we introduce a passive relay mode, in which the relay node simply retransmits collected packets in case it cannot decode them. In contrast with the previous studies, we derive a novel theoretical framework for the performance characterization of the considered relay network. We extend our analysis to a more general scenario, in which coding coefficients are generated from non-binary fields. The theoretical results are verified using simulation, for both binary and non-binary fields. It is also shown that the passive relay mode significantly improves the performance compared with the active-only case, offering an up to two-fold gain in terms of the decoding probability. The proposed framework can be used as a building block for the analysis of more complex network topologies.

In this paper, we investigate the application of iterative decoding algorithms to error correction of cyclic redundancy check (CRC) codes widely used in low-energy communication standards. We consider the case when traditional error correction codes are not available due to energy constraints at the transmitter. Using the CRC-24 code adopted by the Bluetooth Low Energy standard as an example, we show how two iterative techniques traditionally used for decoding of low-density parity check codes - Belief Propagation (BP) and the Alternating Direction Method of Multipliers (ADMM) - can be applied to the high-density parity check matrix of the code. The performance of both techniques is evaluated through simulation, and it is demonstrated that a gain of up to 1.7 dB in terms of the SNR per bit and a total reduction of the packet error rate by more than 70% can be achieved compared with the non-correction scenario, at no extra cost for the transmitter. We also compare the two techniques and use the standard syndrome look-up method as a benchmark. Both schemes enable the correction of multiple errors, with the ADMM-based decoder demonstrating better overall performance than BP.