Massive MIMO Full-Duplex Relaying with Optimal Power Allocation for Independent Multipairs

With the help of an in-band full-duplex relay station, it is possible to simultaneously transmit and receive signals from multiple users. The performance of such system can be greatly increased when the relay station is equipped with a large number of antennas on both transmitter and receiver sides. In this paper, we exploit the use of massive arrays to effectively suppress the loopback interference (LI) of a decode-and-forward relay (DF) and evaluate the performance of the end-to-end (e2e) transmission. This paper assumes imperfect channel state information is available at the relay and designs a minimum mean-square error (MMSE) filter to mitigate the interference. Subsequently, we adopt zero-forcing (ZF) filters for both detection and beamforming. The performance of such system is evaluated in terms of bit error rate (BER) at both relay and destinations, and an optimal choice for the transmission power at the relay is shown. We then propose a complexity efficient optimal power allocation (OPA) algorithm that, using the channel statistics, computes the minimum power that satisfies the rate constraints of each pair. The results obtained via simulation show that when both MMSE filtering and OPA method are used, better values for the energy efficiency are attained.Comment: Accepted to the 16th IEEE International Workshop on Signal Processing Advances in Wireless Communications - SPAWC, Stockholm, Sweden 201

Massive MIMO full-duplex relaying with optimal power allocation for independent multipairs

With the help of an in-band full-duplex relay station, it is possible to simultaneously transmit and receive signals from multiple users. The performance of such system can be greatly increased when the relay station is equipped with a large number of antennas on both transmitter and receiver sides. In this paper, we exploit the use of massive arrays to effectively suppress the loopback interference (LI) of a decode-and-forward relay (DF) and evaluate the performance of the end-to-end (e2e) transmission. This paper assumes imperfect channel state information is available at the relay and designs a minimum mean-square error (MMSE) filter to mitigate the interference. Subsequently, we adopt zero-forcing (ZF) filters for both detection and beamforming. The performance of such system is evaluated in terms of bit error rate (BER) at both relay and destinations, and an optimal choice for the transmission power at the relay is shown. We then propose a complexity efficient optimal power allocation (OPA) algorithm that, using the channel statistics, computes the minimum power that satisfies the rate constraints of each pair. The results obtained via simulation show that when both MMSE filtering and OPA method are used, better values for the energy efficiency are attained.info:eu-repo/semantics/acceptedVersio

Full-Duplex Relaying in MIMO-OFDM Frequency-Selective Channels with Optimal Adaptive Filtering

In-band full-duplex transmission allows a relay station to theoretically double its spectral efficiency by simultaneously receiving and transmitting in the same frequency band, when compared to the traditional half-duplex or out-of-band full-duplex counterpart. Consequently, the induced self-interference suffered by the relay may reach considerable power levels, which decreases the signal-to-interference-plus-noise ratio (SINR) in a decode-and-forward (DF) relay, leading to a degradation of the relay performance. This paper presents a technique to cope with the problem of self-interference in broadband multiple-input multiple-output (MIMO) relays. The proposed method uses a time-domain cancellation in a DF relay, where a replica of the interfering signal is created with the help of a recursive least squares (RLS) algorithm that estimates the interference frequency-selective channel. Its convergence mean time is shown to be negligible by simulation results, when compared to the length of a typical orthogonal-frequency division multiplexing (OFDM) sequences. Moreover, the bit-error-rate (BER) and the SINR in a OFDM transmission are evaluated, confirming that the proposed method extends significantly the range of self-interference power to which the relay is resilient to, when compared with other mitigation schemes

Multi-pair massive MIMO relay networks: power scaling laws and user scheduling strategy

This study studies a multi-pair massive multiple-input multiple-output (MIMO) relaying network, where multiple pairs of users are served by a single relay station with a large number of antennas, and the amplify-and-forward protocol and zero-forcing (ZF) beamforming are used at the relay. The authors investigate the ergodic achievable rates for the users and obtain tight approximations in closed form for finite number of antennas. The rate performance and power efficiency are studied based on the analytical results for asymptotic scenarios, and the effect of scaling factors of transmit powers for users and relay are discussed. The closed-form expressions enable us to determine the optimal user scheduling which maximizes the ergodic sum-rate for the selected pairs. A simplified user scheduling algorithm is proposed which greatly reduces the average complexity of the optimal use pair search without any rate loss. Moreover, the complexity reduction for the proposed algorithm increases nonlinearly with the increase of the number of user pairs, which indicates that the simplified scheduling algorithm has notable advantages when the number of users is increased. The tightness for the analytical approximations and the superiority of the proposed algorithm are verified by Monte-Carlo simulation results

Full-duplex MIMO and PLNC for the Y-network

This paper considers a multi-way wireless network with three terminals which want to exchange or share data with the help of a relay: each terminal has some information that wants to transmit to the other two. The traditional way of doing this exchange either involves time-domain multiplexing (TDMA) or dedicated frequency-domain disjoint channels, at the expense of high bandwidth inefficiency. With the advent of network coding, and later physical-layer network coding, it became possible to reduce the number of time slots required to exchange the information between all the terminals. Moreover, using multiple-input multiple-output (MIMO) terminals and relays, the time-usage efficiency can be further boosted by transferring the burden from the time-domain to the spatial-domain via spatial multiplexing. This paper proposes the concatenation of the aforementioned techniques along with loopback interference cancellation, which recently became a central topic for the next generation of the physical-layer of wireless communications. The paper shows a protocol and techniques that allow all the information exchange between terminals to be reduced from the 6 time-slots, required in traditional TDMA, to one time-slot only, provided that the information packets are not too short. The error performance of this system is shown by means of simulation using MIMO Rayleigh fading channels.info:eu-repo/semantics/acceptedVersio

Fast matrix inversion updates for massive MIMO detection and precoding

In this letter, methods and corresponding complexities for fast matrix inversion updates in the context of massive multiple-input multiple-output (MIMO) are studied. In particular, we propose an on-the-fly method to recompute the zero forcing (ZF) filter when a user is added or removed from the system. Additionally, we evaluate the recalculation of the inverse matrix after a new channel estimation is obtained for a given user. Results are evaluated numerically in terms of bit error rate (BER) using the Neumann series approximation as the initial inverse matrix. It is concluded that, with fewer operations, the performance after an update remains close to the initial one.info:eu-repo/semantics/acceptedVersio

Optimal Power Allocation for Energy Efficient MIMO Relay Systems in 5G Wireless Communication

Wireless communication has undergone a significant growth to meet the unexpected demand of wireless data traffic over the past two decades. As manifested by the revolution of the third and fourth generations and long-term evolution advanced (LTE-A), engineers and researchers have been devoted to the development of the next-generation (5G) wireless solutions to meet the anticipated demand of 2020. To this end, cooperative relay communication has been introduced as an enabling technology to increase the throughput and extend the coverage of the broadband wireless networks. Decode-and-forward (DF) has been known as an effective cooperative relaying strategy for its outstanding features. On the other hand, merging massive multi-input-multi-output (MIMO) with cooperative DF relay is considered as a key technology for 5G wireless networks to improve the quality-of-service (QoS) in a cost-effective manner. The objective of this thesis is to establish and solve a power allocation optimization problem for energy efficient multi-pair DF relay systems integrated with massive MIMO. The first part of the thesis is focused on a constrained optimization problem to minimize the total transmit power for each transmission phase of the DF relay. Due to the non-convexity characteristic, the objective function is approximated as a convex function by means of complementary geometric programming (CGP) which is then solved by a sequence of geometric programming (GP). A lower bound of average SINR is also introduced by adopting the MMSE channel state information (CSI) to relax the constraint functions in the standard GP form. Finally, we proposed a homotopy or continuation method based algorithm to solve the optimization problem via popular CVX optimization toolbox. MATLAB simulations are conducted to validate the proposed algorithm. In the second part, another optimization problem is presented for the entire two-hop transmission of the DF relay to improve the global energy efficiency (GEE) under different channel conditions. Here, we estimate the channel by maximum likelihood (ML) criterion and investigate a closed-form expression of GEE. Further, GEE is approximated in a convex form by applying CGP due to the difficulty arising from the non-convexity and a lower bound of the average SINR expression is also derived to relax the constraint functions in the GP problem. Numerical results showing a detailed comparison of GEE under ML and MMSE channel estimation conditions and the performance improvement from the proposed algorithm are provided