Q2Maintaining high energy efficiency is essential for increasing the lifetime of wireless sensor networks (WSNs), where the battery of the sensor nodes cannot be routinely replaced. Nevertheless, the energy budget of the WSN strictly relies on the communication parameters, where the choice of both the transmit power as well as of the modulation and coding schemes (MCSs) plays a significant role in maximising the network lifetime (NL). In this study, the authors optimise the NL of WNSs by analysing the impact of the physical layer parameters as well as of the signal processing power (SPP) P sp on the NL. They characterise the underlying trade-offs between the NL and bit error ratio (BER) performance for a predetermined set of target signal-to-interference-plus-noise ratio (SINR) values and for different MCSs using periodic transmit-time slot (TS) scheduling in interference-limited WSNs. The NL maximisation is formulated as a non-linear optimisation problem taking into account the lower-bounded SINR, the energy consumption constraint, the maximum transmit power per link and again, periodic transmit-TS scheduling for all active TSs. The non-linear energy consumption constraint encountered is relaxed by employing a change of variables, which converts the problem into a linear form. Hence they can obtain the globally optimal solution of the original problem by solving a linear programming problem with the aid of the interior point method. The author's results demonstrate that for a per-link target BER requirement (PLBR) of 10 −3 , a 'continuous-time' NL of 4.99 years (yr) is achieved by 1/2-rate convolutional coded soft-decoded quadrature phase-shift keying for an additive white Gaussian noise channel, when ignoring the SPP, which is reduced to 0.89 yr because of the SPP. By contrast, the best NL that is achieved by 1/2-rate serially concatenated coding after ten iterations at a PLBR of 10 −3 in a Rayleigh fading channel, which is reduced from 1.55 to 0.58 yr because of the SPP.