In this paper, we analyze the impact of channel estimation errors in an amplify-and-forward (AF)-based two-way relaying network (TWRN) where adaptive modulation (AM) is employed in individual relaying path. In particular, the performance degradation caused by channel estimation error is investigated over Nakagami-m fading channels. We first derive an end-to-end signal-to-noise ratio (SNR), a cumulative distribution function, and a probability density function in the presence of channel estimation error for the AF-based TWRN with adaptive modulation (TWRN-AM). By utilizing the derived SNR statistics, we present accurate expressions of the average spectral efficiency and bit error rates with an outage-constraint in which transmission does not take place during outage events of bidirectional communications. Based on our derived analytical results, an optimal power allocation scheme for TWRN-AM is proposed to improve the average spectral efficiency by minimizing system outages.

In this paper, we consider a two-hop relay network with a decode-and-forward (DF) relaying protocol where a multi-input/multi-output (MIMO) relay station (RS) is deployed in a cell edge to extend cell coverage of a base station (BS). We propose two MIMO relaying schemes to improve the quality of the BS-RS link, which is a key to improve data rates in the DF relaying: 1) spatial multiplexed MIMO antenna relaying (SM-MAR) with a uniform channel decomposition (UCD) precoder, and 2) MIMO relaying with section diversity (SD-MAR). In the SM-MAR, we greatly simplify user allocation by the UCD precoder and propose a sophisticated rate maximization technique to resolve the non-convexity of rate maximization problems. Through simulations, we show that the proposed UCD based power allocation exhibits up to two times higher achievable throughput than other techniques. In addition, the proposed SD-MAR supports the BS with a single transmit antenna and increases the signal quality of the BS-RS link with the selection diversity at the RS, which is much simpler to be implemented. For the SD-MAR, we derive a closed form expression for the achievable throughput and show that the selection diversity plays more important role on the achievable throughput than the multiuser diversity.